kinetic model framework: Topics by Science.gov

Sample records for kinetic model framework

Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System: Modeling Ion Outflow

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Barakat, A. R.; Eccles, V.; Karimabadi, H.; Omelchenko, Y.; Khazanov, G. V.; Glocer, A.; Kistler, L. M.

2014-12-01

A Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System is being developed in order to provide a rigorous approach to modeling the interaction of hot and cold particle interactions. The framework will include ion and electron kinetic species in the ionosphere, plasmasphere and polar wind, and kinetic ion, super-thermal electron and fluid electron species in the magnetosphere. The framework is ideally suited to modeling ion outflow from the ionosphere and plasmasphere, where a wide range for fluid and kinetic processes are important. These include escaping ion interactions with (1) photoelectrons, (2) cusp/auroral waves, double layers, and field-aligned currents, (3) double layers in the polar cap due to the interaction of cold ionospheric and hot magnetospheric electrons, (4) counter-streaming ions, and (5) electromagnetic wave turbulence. The kinetic ion interactions are particularly strong during geomagnetic storms and substorms. The presentation will provide a brief description of the models involved and discuss the effect that kinetic processes have on the ion outflow.
A unifying kinetic framework for modeling oxidoreductase-catalyzed reactions.

PubMed

Chang, Ivan; Baldi, Pierre

2013-05-15

Oxidoreductases are a fundamental class of enzymes responsible for the catalysis of oxidation-reduction reactions, crucial in most bioenergetic metabolic pathways. From their common root in the ancient prebiotic environment, oxidoreductases have evolved into diverse and elaborate protein structures with specific kinetic properties and mechanisms adapted to their individual functional roles and environmental conditions. While accurate kinetic modeling of oxidoreductases is thus important, current models suffer from limitations to the steady-state domain, lack empirical validation or are too specialized to a single system or set of conditions. To address these limitations, we introduce a novel unifying modeling framework for kinetic descriptions of oxidoreductases. The framework is based on a set of seven elementary reactions that (i) form the basis for 69 pairs of enzyme state transitions for encoding various specific microscopic intra-enzyme reaction networks (micro-models), and (ii) lead to various specific macroscopic steady-state kinetic equations (macro-models) via thermodynamic assumptions. Thus, a synergistic bridge between the micro and macro kinetics can be achieved, enabling us to extract unitary rate constants, simulate reaction variance and validate the micro-models using steady-state empirical data. To help facilitate the application of this framework, we make available RedoxMech: a Mathematica™ software package that automates the generation and customization of micro-models. The Mathematica™ source code for RedoxMech, the documentation and the experimental datasets are all available from: http://www.igb.uci.edu/tools/sb/metabolic-modeling. pfbaldi@ics.uci.edu Supplementary data are available at Bioinformatics online.
Qualitative analysis of a discrete thermostatted kinetic framework modeling complex adaptive systems

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-01-01

This paper deals with the derivation of a new discrete thermostatted kinetic framework for the modeling of complex adaptive systems subjected to external force fields (nonequilibrium system). Specifically, in order to model nonequilibrium stationary states of the system, the external force field is coupled to a dissipative term (thermostat). The well-posedness of the related Cauchy problem is investigated thus allowing the new discrete thermostatted framework to be suitable for the derivation of specific models and the related computational analysis. Applications to crowd dynamics and future research directions are also discussed within the paper.
A General Framework for Thermodynamically Consistent Parameterization and Efficient Sampling of Enzymatic Reactions

PubMed Central

Saa, Pedro; Nielsen, Lars K.

2015-01-01

Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> ΔGr >-2 kJ/mol), a transition region (-2> ΔGr >-20 kJ/mol) and a constant elasticity region (ΔGr <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions. PMID:25874556
Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.
VAMPnets for deep learning of molecular kinetics.

PubMed

Mardt, Andreas; Pasquali, Luca; Wu, Hao; Noé, Frank

2018-01-02

There is an increasing demand for computing the relevant structures, equilibria, and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transformation of simulated coordinates into structural features, dimension reduction, clustering the dimension-reduced data, and estimation of a Markov state model or related model of the interconversion rates between molecular structures. This handcrafted approach demands a substantial amount of modeling expertise, as poor decisions at any step will lead to large modeling errors. Here we employ the variational approach for Markov processes (VAMP) to develop a deep learning framework for molecular kinetics using neural networks, dubbed VAMPnets. A VAMPnet encodes the entire mapping from molecular coordinates to Markov states, thus combining the whole data processing pipeline in a single end-to-end framework. Our method performs equally or better than state-of-the-art Markov modeling methods and provides easily interpretable few-state kinetic models.
New theoretical framework for designing nonionic surfactant mixtures that exhibit a desired adsorption kinetics behavior.

PubMed

Moorkanikkara, Srinivas Nageswaran; Blankschtein, Daniel

2010-12-21

How does one design a surfactant mixture using a set of available surfactants such that it exhibits a desired adsorption kinetics behavior? The traditional approach used to address this design problem involves conducting trial-and-error experiments with specific surfactant mixtures. This approach is typically time-consuming and resource-intensive and becomes increasingly challenging when the number of surfactants that can be mixed increases. In this article, we propose a new theoretical framework to identify a surfactant mixture that most closely meets a desired adsorption kinetics behavior. Specifically, the new theoretical framework involves (a) formulating the surfactant mixture design problem as an optimization problem using an adsorption kinetics model and (b) solving the optimization problem using a commercial optimization package. The proposed framework aims to identify the surfactant mixture that most closely satisfies the desired adsorption kinetics behavior subject to the predictive capabilities of the chosen adsorption kinetics model. Experiments can then be conducted at the identified surfactant mixture condition to validate the predictions. We demonstrate the reliability and effectiveness of the proposed theoretical framework through a realistic case study by identifying a nonionic surfactant mixture consisting of up to four alkyl poly(ethylene oxide) surfactants (C(10)E(4), C(12)E(5), C(12)E(6), and C(10)E(8)) such that it most closely exhibits a desired dynamic surface tension (DST) profile. Specifically, we use the Mulqueen-Stebe-Blankschtein (MSB) adsorption kinetics model (Mulqueen, M.; Stebe, K. J.; Blankschtein, D. Langmuir 2001, 17, 5196-5207) to formulate the optimization problem as well as the SNOPT commercial optimization solver to identify a surfactant mixture consisting of these four surfactants that most closely exhibits the desired DST profile. Finally, we compare the experimental DST profile measured at the surfactant mixture condition identified by the new theoretical framework with the desired DST profile and find good agreement between the two profiles.
An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.
Kinetic operational models of agonism for G-protein-coupled receptors.

PubMed

Hoare, Samuel R J; Pierre, Nicolas; Moya, Arturo Gonzalez; Larson, Brad

2018-06-07

The application of kinetics to research and therapeutic development of G-protein-coupled receptors has become increasingly valuable. Pharmacological models provide the foundation of pharmacology, providing concepts and measurable parameters such as efficacy and potency that have underlain decades of successful drug discovery. Currently there are few pharmacological models that incorporate kinetic activity in such a way as to yield experimentally-accessible drug parameters. In this study, a kinetic model of pharmacological response was developed that provides a kinetic descriptor of efficacy (the transduction rate constant, k τ ) and allows measurement of receptor-ligand binding kinetics from functional data. The model assumes: (1) receptor interacts with a precursor of the response ("Transduction potential") and converts it to the response. (2) The response can decay. Familiar response vs time plots emerge, depending on whether transduction potential is depleted and/or response decays. These are the straight line, the "association" exponential curve, and the rise-and-fall curve. Convenient, familiar methods are described for measuring the model parameters and files are provided for the curve-fitting program Prism (GraphPad Software) that can be used as a guide. The efficacy parameter k τ is straightforward to measure and accounts for receptor reserve; all that is required is measurement of response over time at a maximally-stimulating concentration of agonist. The modular nature of the model framework allows it to be extended. Here this is done to incorporate antagonist-receptor binding kinetics and slow agonist-receptor equilibration. In principle, the modular framework can incorporate other cellular processes, such as receptor desensitization. The kinetic response model described here can be applied to measure kinetic pharmacological parameters than can be used to advance the understanding of GPCR pharmacology and optimize new and improved therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.
Neurobiological model of stimulated dopamine neurotransmission to interpret fast-scan cyclic voltammetry data.

PubMed

Harun, Rashed; Grassi, Christine M; Munoz, Miranda J; Torres, Gonzalo E; Wagner, Amy K

2015-03-02

Fast-scan cyclic voltammetry (FSCV) is an electrochemical method that can assess real-time in vivo dopamine (DA) concentration changes to study the kinetics of DA neurotransmission. Electrical stimulation of dopaminergic (DAergic) pathways can elicit FSCV DA responses that largely reflect a balance of DA release and reuptake. Interpretation of these evoked DA responses requires a framework to discern the contribution of DA release and reuptake. The current, widely implemented interpretive framework for doing so is the Michaelis-Menten (M-M) model, which is grounded on two assumptions- (1) DA release rate is constant during stimulation, and (2) DA reuptake occurs through dopamine transporters (DAT) in a manner consistent with M-M enzyme kinetics. Though the M-M model can simulate evoked DA responses that rise convexly, response types that predominate in the ventral striatum, the M-M model cannot simulate dorsal striatal responses that rise concavely. Based on current neurotransmission principles and experimental FSCV data, we developed a novel, quantitative, neurobiological framework to interpret DA responses that assumes DA release decreases exponentially during stimulation and continues post-stimulation at a diminishing rate. Our model also incorporates dynamic M-M kinetics to describe DA reuptake as a process of decreasing reuptake efficiency. We demonstrate that this quantitative, neurobiological model is an extension of the traditional M-M model that can simulate heterogeneous regional DA responses following manipulation of stimulation duration, frequency, and DA pharmacology. The proposed model can advance our interpretive framework for future in vivo FSCV studies examining regional DA kinetics and their alteration by disease and DA pharmacology. Copyright © 2015 Elsevier B.V. All rights reserved.
A model framework to describe growth-linked biodegradation of trace-level pollutants in the presence of coincidental carbon substrates and microbes.

PubMed

Liu, Li; Helbling, Damian E; Kohler, Hans-Peter E; Smets, Barth F

2014-11-18

Pollutants such as pesticides and their degradation products occur ubiquitously in natural aquatic environments at trace concentrations (μg L(-1) and lower). Microbial biodegradation processes have long been known to contribute to the attenuation of pesticides in contaminated environments. However, challenges remain in developing engineered remediation strategies for pesticide-contaminated environments because the fundamental processes that regulate growth-linked biodegradation of pesticides in natural environments remain poorly understood. In this research, we developed a model framework to describe growth-linked biodegradation of pesticides at trace concentrations. We used experimental data reported in the literature or novel simulations to explore three fundamental kinetic processes in isolation. We then combine these kinetic processes into a unified model framework. The three kinetic processes described were: the growth-linked biodegradation of micropollutant at environmentally relevant concentrations; the effect of coincidental assimilable organic carbon substrates; and the effect of coincidental microbes that compete for assimilable organic carbon substrates. We used Monod kinetic models to describe substrate utilization and microbial growth rates for specific pesticide and degrader pairs. We then extended the model to include terms for utilization of assimilable organic carbon substrates by the specific degrader and coincidental microbes, growth on assimilable organic carbon substrates by the specific degrader and coincidental microbes, and endogenous metabolism. The proposed model framework enables interpretation and description of a range of experimental observations on micropollutant biodegradation. The model provides a useful tool to identify environmental conditions with respect to the occurrence of assimilable organic carbon and coincidental microbes that may result in enhanced or reduced micropollutant biodegradation.
Fractal-like kinetics of intracellular enzymatic reactions: a chemical framework of endotoxin tolerance and a possible non-specific contribution of macromolecular crowding to cross-tolerance.

PubMed

Vasilescu, Catalin; Olteanu, Mircea; Flondor, Paul; Calin, George A

2013-09-14

The response to endotoxin (LPS), and subsequent signal transduction lead to the production of cytokines such as tumor necrosis factor-α (TNF-α) by innate immune cells. Cells or organisms pretreated with endotoxin enter into a transient state of hyporesponsiveness, referred to as endotoxin tolerance (ET) which represents a particular case of negative preconditioning. Despite recent progress in understanding the molecular basis of ET, there is no consensus yet on the primary mechanism responsible for ET and for the more complex cases of cross tolerance. In this study, we examined the consequences of the macromolecular crowding (MMC) and of fractal-like kinetics (FLK) of intracellular enzymatic reactions on the LPS signaling machinery. We hypothesized that this particular type of enzyme kinetics may explain the development of ET phenomenon. Our aim in the present study was to characterize the chemical kinetics framework in ET and determine whether fractal-like kinetics explains, at least in part, ET. We developed an ordinary differential equations (ODE) mathematical model that took into account the links between the MMC and the LPS signaling machinery leading to ET. We proposed that the intracellular fractal environment (MMC) contributes to ET and developed two mathematical models of enzyme kinetics: one based on Kopelman's fractal-like kinetics framework and the other based on Savageau's power law model. Kopelman's model provides a good image of the potential influence of a fractal intracellular environment (MMC) on ET. The Savageau power law model also partially explains ET. The computer simulations supported the hypothesis that MMC and FLK may play a role in ET. The model highlights the links between the organization of the intracellular environment, MMC and the LPS signaling machinery leading to ET. Our FLK-based model does not minimize the role of the numerous negative regulatory factors. It simply draws attention to the fact that macromolecular crowding can contribute significantly to the induction of ET by imposing geometric constrains and a particular chemical kinetic for the intracellular reactions.
Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data.

PubMed

Kotasidis, F A; Mehranian, A; Zaidi, H

2016-05-07

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.
Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

NASA Astrophysics Data System (ADS)

Kotasidis, F. A.; Mehranian, A.; Zaidi, H.

2016-05-01

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.
Collective thermal transport in pure and alloy semiconductors.

PubMed

Torres, Pol; Mohammed, Amr; Torelló, Àlvar; Bafaluy, Javier; Camacho, Juan; Cartoixà, Xavier; Shakouri, Ali; Alvarez, F Xavier

2018-03-07

Conventional models for predicting thermal conductivity of alloys usually assume a pure kinetic regime as alloy scattering dominates normal processes. However, some discrepancies between these models and experiments at very small alloy concentrations have been reported. In this work, we use the full first principles kinetic collective model (KCM) to calculate the thermal conductivity of Si 1-x Ge x and In x Ga 1-x As alloys. The calculated thermal conductivities match well with the experimental data for all alloy concentrations. The model shows that the collective contribution must be taken into account at very low impurity concentrations. For higher concentrations, the collective contribution is suppressed, but normal collisions have the effect of significantly reducing the kinetic contribution. The study thus shows the importance of the proper inclusion of normal processes even for alloys for accurate modeling of thermal transport. Furthermore, the phonon spectral distribution of the thermal conductivity is studied in the framework of KCM, providing insights to interpret the superdiffusive regime introduced in the truncated Lévy flight framework.
Virus Neutralisation: New Insights from Kinetic Neutralisation Curves

PubMed Central

Magnus, Carsten

2013-01-01

Antibodies binding to the surface of virions can lead to virus neutralisation. Different theories have been proposed to determine the number of antibodies that must bind to a virion for neutralisation. Early models are based on chemical binding kinetics. Applying these models lead to very low estimates of the number of antibodies needed for neutralisation. In contrast, according to the more conceptual approach of stoichiometries in virology a much higher number of antibodies is required for virus neutralisation by antibodies. Here, we combine chemical binding kinetics with (virological) stoichiometries to better explain virus neutralisation by antibody binding. This framework is in agreement with published data on the neutralisation of the human immunodeficiency virus. Knowing antibody reaction constants, our model allows us to estimate stoichiometrical parameters from kinetic neutralisation curves. In addition, we can identify important parameters that will make further analysis of kinetic neutralisation curves more valuable in the context of estimating stoichiometries. Our model gives a more subtle explanation of kinetic neutralisation curves in terms of single-hit and multi-hit kinetics. PMID:23468602
DOE Office of Scientific and Technical Information (OSTI.GOV)

Willemin, Marie-Emilie; Lumen, Annie, E-mail: Anni

Thyroid homeostasis can be disturbed due to thiocyanate exposure from the diet or tobacco smoke. Thiocyanate inhibits both thyroidal uptake of iodide, via the sodium-iodide symporter (NIS), and thyroid hormone (TH) synthesis in the thyroid, via thyroid peroxidase (TPO), but the mode of action of thiocyanate is poorly quantified in the literature. The characterization of the link between intra-thyroidal thiocyanate concentrations and dose of exposure is crucial for assessing the risk of thyroid perturbations due to thiocyanate exposure. We developed a PBPK model for thiocyanate that describes its kinetics in the whole-body up to daily doses of 0.15 mmol/kg, withmore » a mechanistic description of the thyroidal kinetics including NIS, passive diffusion, and TPO. The model was calibrated in a Bayesian framework using published studies in rats. Goodness-of-fit was satisfactory, especially for intra-thyroidal thiocyanate concentrations. Thiocyanate kinetic processes were quantified in vivo, including the metabolic clearance by TPO. The passive diffusion rate was found to be greater than NIS-mediated uptake rate. The model captured the dose-dependent kinetics of thiocyanate after acute and chronic exposures. Model behavior was evaluated using a Morris screening test. The distribution of thiocyanate into the thyroid was found to be determined primarily by the partition coefficient, followed by NIS and passive diffusion; the impact of the latter two mechanisms appears to increase at very low doses. Extrapolation to humans resulted in good predictions of thiocyanate kinetics during chronic exposure. The developed PBPK model can be used in risk assessment to quantify dose-response effects of thiocyanate on TH. - Highlights: • A PBPK model of thiocyanate (SCN{sup −}) was calibrated in rats in a Bayesian framework. • The intra-thyroidal kinetics of thiocyanate including NIS and TPO was modeled. • Passive diffusion rate for SCN{sup −} seemed to be greater than the NIS-mediated uptake. • The dose-dependent kinetics of SCN{sup −} was captured after an acute and chronic exposure. • The PBPK model of thiocyanate was successfully extrapolated to humans.« less
Comparison of detailed and reduced kinetics mechanisms of silane oxidation in the basis of detonation wave structure problem

NASA Astrophysics Data System (ADS)

Fedorov, A. V.; Tropin, D. A.; Fomin, P. A.

2018-03-01

The paper deals with the problem of the structure of detonation waves in the silane-air mixture within the framework of mathematical model of a nonequilibrium gas dynamics. Detailed kinetic scheme of silane oxidation as well as the newly developed reduced kinetic model of detonation combustion of silane are used. On its basis the detonation wave (DW) structure in stoichiometric silane - air mixture and dependences of Chapman-Jouguet parameters of mixture on stoichiometric ratio between the fuel (silane) and an oxidizer (air) were obtained.
The role of the time-kill kinetics assay as part of a preclinical modeling framework for assessing the activity of anti-tuberculosis drugs.

PubMed

Bax, Hannelore I; Bakker-Woudenberg, Irma A J M; de Vogel, Corné P; van der Meijden, Aart; Verbon, Annelies; de Steenwinkel, Jurriaan E M

2017-07-01

Novel treatment strategies for tuberculosis are urgently needed. Many different preclinical models assessing anti-tuberculosis drug activity are available, but it is yet unclear which combination of models is most predictive of clinical treatment efficacy. The aim of this study was to determine the role of our in vitro time kill-kinetics assay as an asset to a predictive preclinical modeling framework assessing anti-tuberculosis drug activity. The concentration- and time-dependent mycobacterial killing capacities of six anti-tuberculosis drugs were determined during exposure as single drugs or in dual, triple and quadruple combinations towards a Mycobacterium tuberculosis Beijing genotype strain and drug resistance was assessed. Streptomycin, rifampicin and isoniazid were most active against fast-growing M. tuberculosis. Isoniazid with rifampicin or high dose ethambutol were the only synergistic drug combinations. The addition of rifampicin or streptomycin to isoniazid prevented isoniazid resistance. In vitro ranking showed agreement with early bactericidal activity in tuberculosis patients for some but not all anti-tuberculosis drugs. The time-kill kinetics assay provides important information on the mycobacterial killing dynamics of anti-tuberculosis drugs during the early phase of drug exposure. As such, this assay is a valuable component of the preclinical modeling framework. Copyright © 2017 Elsevier Ltd. All rights reserved.
Integrated computational model of the bioenergetics of isolated lung mitochondria

PubMed Central

Zhang, Xiao; Jacobs, Elizabeth R.; Camara, Amadou K. S.; Clough, Anne V.

2018-01-01

Integrated computational modeling provides a mechanistic and quantitative framework for describing lung mitochondrial bioenergetics. Thus, the objective of this study was to develop and validate a thermodynamically-constrained integrated computational model of the bioenergetics of isolated lung mitochondria. The model incorporates the major biochemical reactions and transport processes in lung mitochondria. A general framework was developed to model those biochemical reactions and transport processes. Intrinsic model parameters such as binding constants were estimated using previously published isolated enzymes and transporters kinetic data. Extrinsic model parameters such as maximal reaction and transport velocities were estimated by fitting the integrated bioenergetics model to published and new tricarboxylic acid cycle and respirometry data measured in isolated rat lung mitochondria. The integrated model was then validated by assessing its ability to predict experimental data not used for the estimation of the extrinsic model parameters. For example, the model was able to predict reasonably well the substrate and temperature dependency of mitochondrial oxygen consumption, kinetics of NADH redox status, and the kinetics of mitochondrial accumulation of the cationic dye rhodamine 123, driven by mitochondrial membrane potential, under different respiratory states. The latter required the coupling of the integrated bioenergetics model to a pharmacokinetic model for the mitochondrial uptake of rhodamine 123 from buffer. The integrated bioenergetics model provides a mechanistic and quantitative framework for 1) integrating experimental data from isolated lung mitochondria under diverse experimental conditions, and 2) assessing the impact of a change in one or more mitochondrial processes on overall lung mitochondrial bioenergetics. In addition, the model provides important insights into the bioenergetics and respiration of lung mitochondria and how they differ from those of mitochondria from other organs. To the best of our knowledge, this model is the first for the bioenergetics of isolated lung mitochondria. PMID:29889855

Integrated computational model of the bioenergetics of isolated lung mitochondria.

PubMed

Zhang, Xiao; Dash, Ranjan K; Jacobs, Elizabeth R; Camara, Amadou K S; Clough, Anne V; Audi, Said H

2018-01-01

Integrated computational modeling provides a mechanistic and quantitative framework for describing lung mitochondrial bioenergetics. Thus, the objective of this study was to develop and validate a thermodynamically-constrained integrated computational model of the bioenergetics of isolated lung mitochondria. The model incorporates the major biochemical reactions and transport processes in lung mitochondria. A general framework was developed to model those biochemical reactions and transport processes. Intrinsic model parameters such as binding constants were estimated using previously published isolated enzymes and transporters kinetic data. Extrinsic model parameters such as maximal reaction and transport velocities were estimated by fitting the integrated bioenergetics model to published and new tricarboxylic acid cycle and respirometry data measured in isolated rat lung mitochondria. The integrated model was then validated by assessing its ability to predict experimental data not used for the estimation of the extrinsic model parameters. For example, the model was able to predict reasonably well the substrate and temperature dependency of mitochondrial oxygen consumption, kinetics of NADH redox status, and the kinetics of mitochondrial accumulation of the cationic dye rhodamine 123, driven by mitochondrial membrane potential, under different respiratory states. The latter required the coupling of the integrated bioenergetics model to a pharmacokinetic model for the mitochondrial uptake of rhodamine 123 from buffer. The integrated bioenergetics model provides a mechanistic and quantitative framework for 1) integrating experimental data from isolated lung mitochondria under diverse experimental conditions, and 2) assessing the impact of a change in one or more mitochondrial processes on overall lung mitochondrial bioenergetics. In addition, the model provides important insights into the bioenergetics and respiration of lung mitochondria and how they differ from those of mitochondria from other organs. To the best of our knowledge, this model is the first for the bioenergetics of isolated lung mitochondria.
The Characterization of Cognitive Processes Involved in Chemical Kinetics Using a Blended Processing Framework

ERIC Educational Resources Information Center

Bain, Kinsey; Rodriguez, Jon-Marc G.; Moon, Alena; Towns, Marcy H.

2018-01-01

Chemical kinetics is a highly quantitative content area that involves the use of multiple mathematical representations to model processes and is a context that is under-investigated in the literature. This qualitative study explored undergraduate student integration of chemistry and mathematics during problem solving in the context of chemical…
Microeconomics of the ideal gas like market models

NASA Astrophysics Data System (ADS)

Chakrabarti, Anindya S.; Chakrabarti, Bikas K.

2009-10-01

We develop a framework based on microeconomic theory from which the ideal gas like market models can be addressed. A kinetic exchange model based on that framework is proposed and its distributional features have been studied by considering its moments. Next, we derive the moments of the CC model (Eur. Phys. J. B 17 (2000) 167) as well. Some precise solutions are obtained which conform with the solutions obtained earlier. Finally, an output market is introduced with global price determination in the model with some necessary modifications.
Unraveling reaction pathways and specifying reaction kinetics for complex systems.

PubMed

Vinu, R; Broadbelt, Linda J

2012-01-01

Many natural and industrial processes involve a complex set of competing reactions that include several different species. Detailed kinetic modeling of such systems can shed light on the important pathways involved in various transformations and therefore can be used to optimize the process conditions for the desired product composition and properties. This review focuses on elucidating the various components involved in modeling the kinetics of pyrolysis and oxidation of polymers. The elementary free radical steps that constitute the chain reaction mechanism of gas-phase/nonpolar liquid-phase processes are outlined. Specification of the rate coefficients of the various reaction families, which is central to the theme of kinetics, is described. Construction of the reaction network on the basis of the types of end groups and reactive moieties in a polymer chain is discussed. Modeling frameworks based on the method of moments and kinetic Monte Carlo are evaluated using illustrations. Finally, the prospects and challenges in modeling biomass conversion are addressed.
Integrated modeling applications for tokamak experiments with OMFIT

NASA Astrophysics Data System (ADS)

Meneghini, O.; Smith, S. P.; Lao, L. L.; Izacard, O.; Ren, Q.; Park, J. M.; Candy, J.; Wang, Z.; Luna, C. J.; Izzo, V. A.; Grierson, B. A.; Snyder, P. B.; Holland, C.; Penna, J.; Lu, G.; Raum, P.; McCubbin, A.; Orlov, D. M.; Belli, E. A.; Ferraro, N. M.; Prater, R.; Osborne, T. H.; Turnbull, A. D.; Staebler, G. M.

2015-08-01

One modeling framework for integrated tasks (OMFIT) is a comprehensive integrated modeling framework which has been developed to enable physics codes to interact in complicated workflows, and support scientists at all stages of the modeling cycle. The OMFIT development follows a unique bottom-up approach, where the framework design and capabilities organically evolve to support progressive integration of the components that are required to accomplish physics goals of increasing complexity. OMFIT provides a workflow for easily generating full kinetic equilibrium reconstructions that are constrained by magnetic and motional Stark effect measurements, and kinetic profile information that includes fast-ion pressure modeled by a transport code. It was found that magnetic measurements can be used to quantify the amount of anomalous fast-ion diffusion that is present in DIII-D discharges, and provide an estimate that is consistent with what would be needed for transport simulations to match the measured neutron rates. OMFIT was used to streamline edge-stability analyses, and evaluate the effect of resonant magnetic perturbation (RMP) on the pedestal stability, which have been found to be consistent with the experimental observations. The development of a five-dimensional numerical fluid model for estimating the effects of the interaction between magnetohydrodynamic (MHD) and microturbulence, and its systematic verification against analytic models was also supported by the framework. OMFIT was used for optimizing an innovative high-harmonic fast wave system proposed for DIII-D. For a parallel refractive index {{n}\\parallel}>3 , the conditions for strong electron-Landau damping were found to be independent of launched {{n}\\parallel} and poloidal angle. OMFIT has been the platform of choice for developing a neural-network based approach to efficiently perform a non-linear multivariate regression of local transport fluxes as a function of local dimensionless parameters. Transport predictions for thousands of DIII-D discharges showed excellent agreement with the power balance calculations across the whole plasma radius and over a broad range of operating regimes. Concerning predictive transport simulations, the framework made possible the design and automation of a workflow that enables self-consistent predictions of kinetic profiles and the plasma equilibrium. It is found that the feedback between the transport fluxes and plasma equilibrium can significantly affect the kinetic profiles predictions. Such a rich set of results provide tangible evidence of how bottom-up approaches can potentially provide a fast track to integrated modeling solutions that are functional, cost-effective, and in sync with the research effort of the community.
Analysis and Modeling of DIII-D Experiments With OMFIT and Neural Networks

NASA Astrophysics Data System (ADS)

Meneghini, O.; Luna, C.; Smith, S. P.; Lao, L. L.; GA Theory Team

2013-10-01

The OMFIT integrated modeling framework is designed to facilitate experimental data analysis and enable integrated simulations. This talk introduces this framework and presents a selection of its applications to the DIII-D experiment. Examples include kinetic equilibrium reconstruction analysis; evaluation of MHD stability in the core and in the edge; and self-consistent predictive steady-state transport modeling. The OMFIT framework also provides the platform for an innovative approach based on neural networks to predict electron and ion energy fluxes. In our study a multi-layer feed-forward back-propagation neural network is built and trained over a database of DIII-D data. It is found that given the same parameters that the highest fidelity models use, the neural network model is able to predict to a large degree the heat transport profiles observed in the DIII-D experiments. Once the network is built, the numerical cost of evaluating the transport coefficients is virtually nonexistent, thus making the neural network model particularly well suited for plasma control and quick exploration of operational scenarios. The implementation of the neural network model and benchmark with experimental results and gyro-kinetic models will be discussed. Work supported in part by the US DOE under DE-FG02-95ER54309.
Modeling kinetic rate variation in third generation DNA sequencing data to detect putative modifications to DNA bases

PubMed Central

Schadt, Eric E.; Banerjee, Onureena; Fang, Gang; Feng, Zhixing; Wong, Wing H.; Zhang, Xuegong; Kislyuk, Andrey; Clark, Tyson A.; Luong, Khai; Keren-Paz, Alona; Chess, Andrew; Kumar, Vipin; Chen-Plotkin, Alice; Sondheimer, Neal; Korlach, Jonas; Kasarskis, Andrew

2013-01-01

Current generation DNA sequencing instruments are moving closer to seamlessly sequencing genomes of entire populations as a routine part of scientific investigation. However, while significant inroads have been made identifying small nucleotide variation and structural variations in DNA that impact phenotypes of interest, progress has not been as dramatic regarding epigenetic changes and base-level damage to DNA, largely due to technological limitations in assaying all known and unknown types of modifications at genome scale. Recently, single-molecule real time (SMRT) sequencing has been reported to identify kinetic variation (KV) events that have been demonstrated to reflect epigenetic changes of every known type, providing a path forward for detecting base modifications as a routine part of sequencing. However, to date no statistical framework has been proposed to enhance the power to detect these events while also controlling for false-positive events. By modeling enzyme kinetics in the neighborhood of an arbitrary location in a genomic region of interest as a conditional random field, we provide a statistical framework for incorporating kinetic information at a test position of interest as well as at neighboring sites that help enhance the power to detect KV events. The performance of this and related models is explored, with the best-performing model applied to plasmid DNA isolated from Escherichia coli and mitochondrial DNA isolated from human brain tissue. We highlight widespread kinetic variation events, some of which strongly associate with known modification events, while others represent putative chemically modified sites of unknown types. PMID:23093720
Modeling kinetic rate variation in third generation DNA sequencing data to detect putative modifications to DNA bases.

PubMed

Schadt, Eric E; Banerjee, Onureena; Fang, Gang; Feng, Zhixing; Wong, Wing H; Zhang, Xuegong; Kislyuk, Andrey; Clark, Tyson A; Luong, Khai; Keren-Paz, Alona; Chess, Andrew; Kumar, Vipin; Chen-Plotkin, Alice; Sondheimer, Neal; Korlach, Jonas; Kasarskis, Andrew

2013-01-01

Current generation DNA sequencing instruments are moving closer to seamlessly sequencing genomes of entire populations as a routine part of scientific investigation. However, while significant inroads have been made identifying small nucleotide variation and structural variations in DNA that impact phenotypes of interest, progress has not been as dramatic regarding epigenetic changes and base-level damage to DNA, largely due to technological limitations in assaying all known and unknown types of modifications at genome scale. Recently, single-molecule real time (SMRT) sequencing has been reported to identify kinetic variation (KV) events that have been demonstrated to reflect epigenetic changes of every known type, providing a path forward for detecting base modifications as a routine part of sequencing. However, to date no statistical framework has been proposed to enhance the power to detect these events while also controlling for false-positive events. By modeling enzyme kinetics in the neighborhood of an arbitrary location in a genomic region of interest as a conditional random field, we provide a statistical framework for incorporating kinetic information at a test position of interest as well as at neighboring sites that help enhance the power to detect KV events. The performance of this and related models is explored, with the best-performing model applied to plasmid DNA isolated from Escherichia coli and mitochondrial DNA isolated from human brain tissue. We highlight widespread kinetic variation events, some of which strongly associate with known modification events, while others represent putative chemically modified sites of unknown types.
Improving the Kinetics and Thermodynamics of Mg(BH 4) 2 for Hydrogen Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Brandon; Klebanoff, Lennie; Stavila, Vitalie

The objective of this project is to (1) combine theory, synthesis, and characterization across multiple scales to understand the intrinsic kinetic and thermodynamic limitations in MgB 2/Mg(BH 4) 2; (2) construct and apply a flexible, validated, multiscale theoretical framework for modeling (de)hydrogenation kinetics of the Mg-B-H system and related metal hydrides; and (3) devise strategies for improving kinetics and thermodynamics, particularly through nanostructuring and doping. The project has an emphasis on understanding and improving rehydrogenation of MgB 2, which has generally been less explored and is key to enabling practical use.
A dislocation-based crystal plasticity framework for dynamic ductile failure of single crystals

DOE PAGES

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

2017-08-02

We developed a framework for dislocation-based viscoplasticity and dynamic ductile failure to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. Furthermore, an averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Inmore » addition, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in [J. Wilkerson and K. Ramesh. A dynamic void growth model governed by dislocation kinetics. J. Mech. Phys. Solids, 70:262–280, 2014.], which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.« less
A Computational Fluid Dynamic Model for a Novel Flash Ironmaking Process

NASA Astrophysics Data System (ADS)

Perez-Fontes, Silvia E.; Sohn, Hong Yong; Olivas-Martinez, Miguel

A computational fluid dynamic model for a novel flash ironmaking process based on the direct gaseous reduction of iron oxide concentrates is presented. The model solves the three-dimensional governing equations including both gas-phase and gas-solid reaction kinetics. The turbulence-chemistry interaction in the gas-phase is modeled by the eddy dissipation concept incorporating chemical kinetics. The particle cloud model is used to track the particle phase in a Lagrangian framework. A nucleation and growth kinetics rate expression is adopted to calculate the reduction rate of magnetite concentrate particles. Benchmark experiments reported in the literature for a nonreacting swirling gas jet and a nonpremixed hydrogen jet flame were simulated for validation. The model predictions showed good agreement with measurements in terms of gas velocity, gas temperature and species concentrations. The relevance of the computational model for the analysis of a bench reactor operation and the design of an industrial-pilot plant is discussed.
Fluctuating bottleneck model studies on kinetics of DNA escape from α-hemolysin nanopores

NASA Astrophysics Data System (ADS)

Bian, Yukun; Wang, Zilin; Chen, Anpu; Zhao, Nanrong

2015-11-01

We have proposed a fluctuation bottleneck (FB) model to investigate the non-exponential kinetics of DNA escape from nanometer-scale pores. The basic idea is that the escape rate is proportional to the fluctuating cross-sectional area of DNA escape channel, the radius r of which undergoes a subdiffusion dynamics subjected to fractional Gaussian noise with power-law memory kernel. Such a FB model facilitates us to obtain the analytical result of the averaged survival probability as a function of time, which can be directly compared to experimental results. Particularly, we have applied our theory to address the escape kinetics of DNA through α-hemolysin nanopores. We find that our theoretical framework can reproduce the experimental results very well in the whole time range with quite reasonable estimation for the intrinsic parameters of the kinetics processes. We believe that FB model has caught some key features regarding the long time kinetics of DNA escape through a nanopore and it might provide a sound starting point to study much wider problems involving anomalous dynamics in confined fluctuating channels.
The kinetics of polyurethane structural foam formation: Foaming and polymerization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Rekha R.; Mondy, Lisa A.; Long, Kevin N.

We are developing kinetic models to understand the manufacturing of polymeric foams, which evolve from low viscosity Newtonian liquids, to bubbly liquids, finally producing solid foam. Closed-form kinetics are formulated and parameterized for PMDI-10, a fast curing polyurethane, including polymerization and foaming. PMDI- 10 is chemically blown, where water and isocyanate react to form carbon dioxide. The isocyanate reacts with polyol in a competing reaction, producing polymer. Our approach is unique, though it builds on our previous work and the polymerization literature. This kinetic model follows a simplified mathematical formalism that decouples foaming and curing, including an evolving glass transitionmore » temperature to represent vitrification. This approach is based on IR, DSC, and volume evolution data, where we observed that the isocyanate is always in excess and does not affect the kinetics. Finally, the kinetics are suitable for implementation into a computational fluid dynamics framework, which will be explored in subsequent papers.« less
The kinetics of polyurethane structural foam formation: Foaming and polymerization

DOE PAGES

Rao, Rekha R.; Mondy, Lisa A.; Long, Kevin N.; ...

2017-02-15

We are developing kinetic models to understand the manufacturing of polymeric foams, which evolve from low viscosity Newtonian liquids, to bubbly liquids, finally producing solid foam. Closed-form kinetics are formulated and parameterized for PMDI-10, a fast curing polyurethane, including polymerization and foaming. PMDI- 10 is chemically blown, where water and isocyanate react to form carbon dioxide. The isocyanate reacts with polyol in a competing reaction, producing polymer. Our approach is unique, though it builds on our previous work and the polymerization literature. This kinetic model follows a simplified mathematical formalism that decouples foaming and curing, including an evolving glass transitionmore » temperature to represent vitrification. This approach is based on IR, DSC, and volume evolution data, where we observed that the isocyanate is always in excess and does not affect the kinetics. Finally, the kinetics are suitable for implementation into a computational fluid dynamics framework, which will be explored in subsequent papers.« less
Adsorption of Azo-Dye Orange II from Aqueous Solutions Using a Metal-Organic Framework Material: Iron- Benzenetricarboxylate

PubMed Central

Rojas García, Elizabeth; López Medina, Ricardo; May Lozano, Marcos; Hernández Pérez, Isaías; Valero, Maria J.; Maubert Franco, Ana M.

2014-01-01

A Metal-Organic Framework (MOF), iron-benzenetricarboxylate (Fe(BTC)), has been studied for the adsorptive removal of azo-dye Orange II from aqueous solutions, where the effect of various parameters was tested and isotherm and kinetic models were suggested. The adsorption capacities of Fe(BTC) were much higher than those of an activated carbon. The experimental data can be best described by the Langmuir isotherm model (R2 > 0.997) and revealed the ability of Fe(BTC) to adsorb 435 mg of Orange II per gram of adsorbent at the optimal conditions. The kinetics of Orange II adsorption followed a pseudo-second-order kinetic model, indicating the coexistence of physisorption and chemisorption, with intra-particle diffusion being the rate controlling step. The thermodynamic study revealed that the adsorption of Orange II was feasible, spontaneous and exothermic process (−25.53 kJ·mol−1). The high recovery of the dye showed that Fe(BTC) can be employed as an effective and reusable adsorbent for the removal of Orange II from aqueous solutions and showed the economic interest of this adsorbent material for environmental purposes. PMID:28788289
Kinetics of heavy metal adsorption and desorption in soil: Developing a unified model based on chemical speciation

NASA Astrophysics Data System (ADS)

Peng, Lanfang; Liu, Paiyu; Feng, Xionghan; Wang, Zimeng; Cheng, Tao; Liang, Yuzhen; Lin, Zhang; Shi, Zhenqing

2018-03-01

Predicting the kinetics of heavy metal adsorption and desorption in soil requires consideration of multiple heterogeneous soil binding sites and variations of reaction chemistry conditions. Although chemical speciation models have been developed for predicting the equilibrium of metal adsorption on soil organic matter (SOM) and important mineral phases (e.g. Fe and Al (hydr)oxides), there is still a lack of modeling tools for predicting the kinetics of metal adsorption and desorption reactions in soil. In this study, we developed a unified model for the kinetics of heavy metal adsorption and desorption in soil based on the equilibrium models WHAM 7 and CD-MUSIC, which specifically consider metal kinetic reactions with multiple binding sites of SOM and soil minerals simultaneously. For each specific binding site, metal adsorption and desorption rate coefficients were constrained by the local equilibrium partition coefficients predicted by WHAM 7 or CD-MUSIC, and, for each metal, the desorption rate coefficients of various binding sites were constrained by their metal binding constants with those sites. The model had only one fitting parameter for each soil binding phase, and all other parameters were derived from WHAM 7 and CD-MUSIC. A stirred-flow method was used to study the kinetics of Cd, Cu, Ni, Pb, and Zn adsorption and desorption in multiple soils under various pH and metal concentrations, and the model successfully reproduced most of the kinetic data. We quantitatively elucidated the significance of different soil components and important soil binding sites during the adsorption and desorption kinetic processes. Our model has provided a theoretical framework to predict metal adsorption and desorption kinetics, which can be further used to predict the dynamic behavior of heavy metals in soil under various natural conditions by coupling other important soil processes.
HOW CAN BIOLOGICALLY-BASED MODELING OF ARSENIC KINETICS AND DYNAMICS INFORM THE RISK ASSESSMENT PROCESS?

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic met...
Inequality reversal: Effects of the savings propensity and correlated returns

NASA Astrophysics Data System (ADS)

Chakrabarti, Anindya S.; Chakrabarti, Bikas K.

2010-09-01

In the last decade, a large body of literature has been developed to explain the universal features of inequality in terms of income and wealth. By now, it is established that the distributions of income and wealth in various economies show a number of statistical regularities. There are several models to explain such static features of inequality in a unifying framework, and the kinetic exchange models in particular provide one such framework. Here we focus on the dynamic features of inequality. In the process of development and growth, inequality in an economy in terms of income and wealth follows a particular pattern of rising in the initial stage followed by an eventual fall. This inverted U-shaped curve is known as the Kuznets Curve. We examine the possibilities of such behavior of an economy in the context of a generalized kinetic exchange model. It is shown that under some specific conditions, our model economy indeed shows inequality reversal.
Kinklike structures in models of the Dirac-Born-Infeld type

NASA Astrophysics Data System (ADS)

Bazeia, D.; Lima, Elisama E. M.; Losano, L.

2018-01-01

The present work investigates several models of a single real scalar field, engendering kinetic term of the Dirac-Born- Infeld type. Such theories introduce nonlinearities to the kinetic part of the Lagrangian, which presents a square root restricting the field evolution and including additional powers in derivatives of the scalar field, controlled by a real parameter. In order to obtain topological solutions analytically, we propose a first-order framework that simplifies the equation of motion ensuring solutions that are linearly stable. This is implemented using the deformation method, and we introduce examples presenting two categories of potentials, one having polynomial interactions and the other with nonpolynomial interactions. We also explore how the Dirac-Born-Infeld kinetic term affects the properties of the solutions. In particular, we note that the kinklike solutions are similar to the ones obtained through models with standard kinetic term and canonical potential, but their energy densities and stability potentials vary according to the parameter introduced to control the new models.
Kinetic theory approach to modeling of cellular repair mechanisms under genome stress.

PubMed

Qi, Jinpeng; Ding, Yongsheng; Zhu, Ying; Wu, Yizhi

2011-01-01

Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR) by using mathematical framework of kinetic theory of active particles (KTAP). Firstly, we focus on illustrating the profile of Cellular Repair System (CRS) instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs) and Repair Protein (RP) generating, DSB-protein complexes (DSBCs) synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances.

Hindered rotor models with variable kinetic functions for accurate thermodynamic and kinetic predictions

NASA Astrophysics Data System (ADS)

Reinisch, Guillaume; Leyssale, Jean-Marc; Vignoles, Gérard L.

2010-10-01

We present an extension of some popular hindered rotor (HR) models, namely, the one-dimensional HR (1DHR) and the degenerated two-dimensional HR (d2DHR) models, allowing for a simple and accurate treatment of internal rotations. This extension, based on the use of a variable kinetic function in the Hamiltonian instead of a constant reduced moment of inertia, is extremely suitable in the case of rocking/wagging motions involved in dissociation or atom transfer reactions. The variable kinetic function is first introduced in the framework of a classical 1DHR model. Then, an effective temperature and potential dependent constant is proposed in the cases of quantum 1DHR and classical d2DHR models. These methods are finally applied to the atom transfer reaction SiCl3+BCl3→SiCl4+BCl2. We show, for this particular case, that a proper accounting of internal rotations greatly improves the accuracy of thermodynamic and kinetic predictions. Moreover, our results confirm (i) that using a suitably defined kinetic function appears to be very adapted to such problems; (ii) that the separability assumption of independent rotations seems justified; and (iii) that a quantum mechanical treatment is not a substantial improvement with respect to a classical one.
Stochastic effects in a discretized kinetic model of economic exchange

NASA Astrophysics Data System (ADS)

Bertotti, M. L.; Chattopadhyay, A. K.; Modanese, G.

2017-04-01

Linear stochastic models and discretized kinetic theory are two complementary analytical techniques used for the investigation of complex systems of economic interactions. The former employ Langevin equations, with an emphasis on stock trade; the latter is based on systems of ordinary differential equations and is better suited for the description of binary interactions, taxation and welfare redistribution. We propose a new framework which establishes a connection between the two approaches by introducing random fluctuations into the kinetic model based on Langevin and Fokker-Planck formalisms. Numerical simulations of the resulting model indicate positive correlations between the Gini index and the total wealth, that suggest a growing inequality with increasing income. Further analysis shows, in the presence of a conserved total wealth, a simultaneous decrease in inequality as social mobility increases, in conformity with economic data.
Rapid recipe formulation for plasma etching of new materials

NASA Astrophysics Data System (ADS)

Chopra, Meghali; Zhang, Zizhuo; Ekerdt, John; Bonnecaze, Roger T.

2016-03-01

A fast and inexpensive scheme for etch rate prediction using flexible continuum models and Bayesian statistics is demonstrated. Bulk etch rates of MgO are predicted using a steady-state model with volume-averaged plasma parameters and classical Langmuir surface kinetics. Plasma particle and surface kinetics are modeled within a global plasma framework using single component Metropolis Hastings methods and limited data. The accuracy of these predictions is evaluated with synthetic and experimental etch rate data for magnesium oxide in an ICP-RIE system. This approach is compared and superior to factorial models generated from JMP, a software package frequently employed for recipe creation and optimization.
How Can Biologically-Based Modeling of Arsenic Kinetics and Dynamics Inform the Risk Assessment Process? -- ETD

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic me...
Observations & modeling of solar-wind/magnetospheric interactions

NASA Astrophysics Data System (ADS)

Hoilijoki, Sanni; Von Alfthan, Sebastian; Pfau-Kempf, Yann; Palmroth, Minna; Ganse, Urs

2016-07-01

The majority of the global magnetospheric dynamics is driven by magnetic reconnection, indicating the need to understand and predict reconnection processes and their global consequences. So far, global magnetospheric dynamics has been simulated using mainly magnetohydrodynamic (MHD) models, which are approximate but fast enough to be executed in real time or near-real time. Due to their fast computation times, MHD models are currently the only possible frameworks for space weather predictions. However, in MHD models reconnection is not treated kinetically. In this presentation we will compare the results from global kinetic (hybrid-Vlasov) and global MHD simulations. Both simulations are compared with in-situ measurements. We will show that the kinetic processes at the bow shock, in the magnetosheath and at the magnetopause affect global dynamics even during steady solar wind conditions. Foreshock processes cause an asymmetry in the magnetosheath plasma, indicating that the plasma entering the magnetosphere is not symmetrical on different sides of the magnetosphere. Behind the bow shock in the magnetosheath kinetic wave modes appear. Some of these waves propagate to the magnetopause and have an effect on the magnetopause reconnection. Therefore we find that kinetic phenomena have a significant role in the interaction between the solar wind and the magnetosphere. While kinetic models cannot be executed in real time currently, they could be used to extract heuristics to be added in the faster MHD models.
Integrated Modeling of Time Evolving 3D Kinetic MHD Equilibria and NTV Torque

NASA Astrophysics Data System (ADS)

Logan, N. C.; Park, J.-K.; Grierson, B. A.; Haskey, S. R.; Nazikian, R.; Cui, L.; Smith, S. P.; Meneghini, O.

2016-10-01

New analysis tools and integrated modeling of plasma dynamics developed in the OMFIT framework are used to study kinetic MHD equilibria evolution on the transport time scale. The experimentally observed profile dynamics following the application of 3D error fields are described using a new OMFITprofiles workflow that directly addresses the need for rapid and comprehensive analysis of dynamic equilibria for next-step theory validation. The workflow treats all diagnostic data as fundamentally time dependent, provides physics-based manipulations such as ELM phase data selection, and is consistent across multiple machines - including DIII-D and NSTX-U. The seamless integration of tokamak data and simulation is demonstrated by using the self-consistent kinetic EFIT equilibria and profiles as input into 2D particle, momentum and energy transport calculations using TRANSP as well as 3D kinetic MHD equilibrium stability and neoclassical transport modeling using General Perturbed Equilibrium Code (GPEC). The result is a smooth kinetic stability and NTV torque evolution over transport time scales. Work supported by DE-AC02-09CH11466.
Modelling nifedipine photodegradation, photostability and actinometric properties.

PubMed

Maafi, Wassila; Maafi, Mounir

2013-11-01

The photodegradation of drugs obeying unimolecular mechanisms such as that of nifedipine (NIF) were usually characterised in the literature by zero-, first- and second-order kinetics. This approach has been met with varying success. This paper addresses this issue and proposes a novel approach for unimolecular photodegradation kinetics. The photodegradation of the cardiovascular drug nifedipine is investigated within this framework. Experimental kinetic data of nifedipine photodegradation were obtained by continuous monochromatic irradiation and DAD analysis. Fourth-order Runge-Kutta calculated kinetic data served for the validation of the new semi-empirical integrated rate-law model proposed in this study. A new model equation has been developed and proposed which faithfully describes the kinetic behaviour of NIF in solution for non-isosbestic irradiations at wavelengths where both NIF and its photoproduct absorb. NIF absolute quantum yield values were determined and found to increase with irradiation wavelength according to a defined sigmoid relationship. The effects of increasing NIF or excipients' concentrations on NIF kinetics were successfully modelled and found to improve NIF photostability. The potential of NIF for actinometry has been explored and evaluated. A new reaction order (the so-called Φ-order) has been identified and specifically proposed for unimolecular photodegradation reactions. The semi-empirical and integrated rate-law models facilitated reliable kinetic studies of NIF photodegradation as an example of AB(1Φ) unimolecular reactions. It allowed filling a gap in kinetic studies of drugs since, thus far, thermal first-order or a combination of first- and zero- order kinetic equations were generally applied for drug photoreactions in the literature. Also, a new reaction order, the "Φ-order", has been evidenced and proposed as a specific alternative for photodegradation kinetics. Copyright © 2013 Elsevier B.V. All rights reserved.
Inflection point in running kinetic term inflation

NASA Astrophysics Data System (ADS)

Gao, Tie-Jun; Xiu, Wu-Tao; Yang, Xiu-Yi

2017-04-01

In this work, we calculate the general form of the scalar potential with polynomial superpotential in the framework of running kinetic term inflation, then focus on a polynomial superpotential with two terms and obtain the inflection point inflationary model. We study the inflationary dynamics and show that the predicted value of the scalar spectral index and tensor-to-scalar ratio can lie within the 1σ confidence region allowed by the result of Planck 2015.
Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

NASA Astrophysics Data System (ADS)

Pineda, M.; Stamatakis, M.

2017-07-01

Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.
Kinetics of the mechanochemical synthesis of alkaline-earth metal amides

NASA Astrophysics Data System (ADS)

Garroni, Sebastiano; Takacs, Laszlo; Leng, Haiyan; Delogu, Francesco

2014-07-01

A phenomenological framework is developed to model the kinetics of the formation of alkaline-earth metal amides by the ball milling induced reaction of their hydrides with gaseous ammonia. It is shown that the exponential character of the kinetic curves is modulated by the increase of the total volume of the powder inside the reactor due to the substantially larger molar volume of the products compared to the reactants. It is claimed that the volume of powder effectively processed during each collision connects the transformation rate to the physical and chemical processes underlying the mechanochemical transformations.
Comparison between different adsorption-desorption kinetics schemes in two dimensional lattice gas

NASA Astrophysics Data System (ADS)

Huespe, V. J.; Belardinelli, R. E.; Pereyra, V. D.; Manzi, S. J.

2017-12-01

Monte Carlo simulation is used to study the adsorption-desorption kinetics in the framework of the kinetic lattice-gas model. Three schemes of the so-called hard dynamics and five schemes of the so called soft dynamics were used for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and non-equilibrium observable, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and non-equilibrium observables have several problems.
Mechanochemical models of processive molecular motors

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Sun, Sean X.

2012-05-01

Motor proteins are the molecular engines powering the living cell. These nanometre-sized molecules convert chemical energy, both enthalpic and entropic, into useful mechanical work. High resolution single molecule experiments can now observe motor protein movement with increasing precision. The emerging data must be combined with structural and kinetic measurements to develop a quantitative mechanism. This article describes a modelling framework where quantitative understanding of motor behaviour can be developed based on the protein structure. The framework is applied to myosin motors, with emphasis on how synchrony between motor domains give rise to processive unidirectional movement. The modelling approach shows that the elasticity of protein domains are important in regulating motor function. Simple models of protein domain elasticity are presented. The framework can be generalized to other motor systems, or an ensemble of motors such as muscle contraction. Indeed, for hundreds of myosins, our framework can be reduced to the Huxely-Simmons description of muscle movement in the mean-field limit.
Mechanistic Kinetic Modeling of Thiol-Michael Addition Photopolymerizations via Photocaged "Superbase" Generators: An Analytical Approach.

PubMed

Claudino, Mauro; Zhang, Xinpeng; Alim, Marvin D; Podgórski, Maciej; Bowman, Christopher N

2016-11-08

A kinetic mechanism and the accompanying mathematical framework are presented for base-mediated thiol-Michael photopolymerization kinetics involving a photobase generator. Here, model kinetic predictions demonstrate excellent agreement with a representative experimental system composed of 2-(2-nitrophenyl)propyloxycarbonyl-1,1,3,3-tetramethylguanidine (NPPOC-TMG) as a photobase generator that is used to initiate thiol-vinyl sulfone Michael addition reactions and polymerizations. Modeling equations derived from a basic mechanistic scheme indicate overall polymerization rates that follow a pseudo-first-order kinetic process in the base and coreactant concentrations, controlled by the ratio of the propagation to chain-transfer kinetic parameters ( k p / k CT ) which is dictated by the rate-limiting step and controls the time necessary to reach gelation. Gelation occurs earlier as the k p / k CT ratio reaches a critical value, wherefrom gel times become nearly independent of k p / k CT . The theoretical approach allowed determining the effect of induction time on the reaction kinetics due to initial acid-base neutralization for the photogenerated base caused by the presence of protic contaminants. Such inhibition kinetics may be challenging for reaction systems that require high curing rates but are relevant for chemical systems that need to remain kinetically dormant until activated although at the ultimate cost of lower polymerization rates. The pure step-growth character of this living polymerization and the exhibited kinetics provide unique potential for extended dark-cure reactions and uniform material properties. The general kinetic model is applicable to photobase initiators where photolysis follows a unimolecular cleavage process releasing a strong base catalyst without cogeneration of intermediate radical species.
A global resource allocation strategy governs growth transition kinetics of Escherichia coli

PubMed Central

Erickson, David W; Schink, Severin J.; Patsalo, Vadim; Williamson, James R.; Gerland, Ulrich; Hwa, Terence

2018-01-01

A grand challenge of systems biology is to predict the kinetic responses of living systems to perturbations starting from the underlying molecular interactions. Changes in the nutrient environment have long been used to study regulation and adaptation phenomena in microorganisms1–3 and they remain a topic of active investigation4–11. Although much is known about the molecular interactions that govern the regulation of key metabolic processes in response to applied perturbations12–17, they are insufficiently quantified for predictive bottom-up modelling. Here we develop a top-down approach, expanding the recently established coarse-grained proteome allocation models15,18–20 from steady-state growth into the kinetic regime. Using only qualitative knowledge of the underlying regulatory processes and imposing the condition of flux balance, we derive a quantitative model of bacterial growth transitions that is independent of inaccessible kinetic parameters. The resulting flux-controlled regulation model accurately predicts the time course of gene expression and biomass accumulation in response to carbon upshifts and downshifts (for example, diauxic shifts) without adjustable parameters. As predicted by the model and validated by quantitative proteomics, cells exhibit suboptimal recovery kinetics in response to nutrient shifts owing to a rigid strategy of protein synthesis allocation, which is not directed towards alleviating specific metabolic bottlenecks. Our approach does not rely on kinetic parameters, and therefore points to a theoretical framework for describing a broad range of such kinetic processes without detailed knowledge of the underlying biochemical reactions. PMID:29072300
New types of experimental data shape the use of enzyme kinetics for dynamic network modeling.

PubMed

Tummler, Katja; Lubitz, Timo; Schelker, Max; Klipp, Edda

2014-01-01

Since the publication of Leonor Michaelis and Maude Menten's paper on the reaction kinetics of the enzyme invertase in 1913, molecular biology has evolved tremendously. New measurement techniques allow in vivo characterization of the whole genome, proteome or transcriptome of cells, whereas the classical enzyme essay only allows determination of the two Michaelis-Menten parameters V and K(m). Nevertheless, Michaelis-Menten kinetics are still commonly used, not only in the in vitro context of enzyme characterization but also as a rate law for enzymatic reactions in larger biochemical reaction networks. In this review, we give an overview of the historical development of kinetic rate laws originating from Michaelis-Menten kinetics over the past 100 years. Furthermore, we briefly summarize the experimental techniques used for the characterization of enzymes, and discuss web resources that systematically store kinetic parameters and related information. Finally, describe the novel opportunities that arise from using these data in dynamic mathematical modeling. In this framework, traditional in vitro approaches may be combined with modern genome-scale measurements to foster thorough understanding of the underlying complex mechanisms. © 2013 FEBS.
Stability estimation of autoregulated genes under Michaelis-Menten-type kinetics

NASA Astrophysics Data System (ADS)

Arani, Babak M. S.; Mahmoudi, Mahdi; Lahti, Leo; González, Javier; Wit, Ernst C.

2018-06-01

Feedback loops are typical motifs appearing in gene regulatory networks. In some well-studied model organisms, including Escherichia coli, autoregulated genes, i.e., genes that activate or repress themselves through their protein products, are the only feedback interactions. For these types of interactions, the Michaelis-Menten (MM) formulation is a suitable and widely used approach, which always leads to stable steady-state solutions representative of homeostatic regulation. However, in many other biological phenomena, such as cell differentiation, cancer progression, and catastrophes in ecosystems, one might expect to observe bistable switchlike dynamics in the case of strong positive autoregulation. To capture this complex behavior we use the generalized family of MM kinetic models. We give a full analysis regarding the stability of autoregulated genes. We show that the autoregulation mechanism has the capability to exhibit diverse cellular dynamics including hysteresis, a typical characteristic of bistable systems, as well as irreversible transitions between bistable states. We also introduce a statistical framework to estimate the kinetics parameters and probability of different stability regimes given observational data. Empirical data for the autoregulated gene SCO3217 in the SOS system in Streptomyces coelicolor are analyzed. The coupling of a statistical framework and the mathematical model can give further insight into understanding the evolutionary mechanisms toward different cell fates in various systems.
A new class of enhanced kinetic sampling methods for building Markov state models

NASA Astrophysics Data System (ADS)

Bhoutekar, Arti; Ghosh, Susmita; Bhattacharya, Swati; Chatterjee, Abhijit

2017-10-01

Markov state models (MSMs) and other related kinetic network models are frequently used to study the long-timescale dynamical behavior of biomolecular and materials systems. MSMs are often constructed bottom-up using brute-force molecular dynamics (MD) simulations when the model contains a large number of states and kinetic pathways that are not known a priori. However, the resulting network generally encompasses only parts of the configurational space, and regardless of any additional MD performed, several states and pathways will still remain missing. This implies that the duration for which the MSM can faithfully capture the true dynamics, which we term as the validity time for the MSM, is always finite and unfortunately much shorter than the MD time invested to construct the model. A general framework that relates the kinetic uncertainty in the model to the validity time, missing states and pathways, network topology, and statistical sampling is presented. Performing additional calculations for frequently-sampled states/pathways may not alter the MSM validity time. A new class of enhanced kinetic sampling techniques is introduced that aims at targeting rare states/pathways that contribute most to the uncertainty so that the validity time is boosted in an effective manner. Examples including straightforward 1D energy landscapes, lattice models, and biomolecular systems are provided to illustrate the application of the method. Developments presented here will be of interest to the kinetic Monte Carlo community as well.
A nonlocal fluid closure for antiparallel reconnection

NASA Astrophysics Data System (ADS)

Ng, J.; Hakim, A.; Bhattacharjee, A.

2016-12-01

The integration of kinetic effects in fluid models is an important problem in global simulations of the Earth's magnetosphere and space weather modelling. In particular, it has been shown that ion kinetics play an important role in the dynamics of large reconnecting systems, and that fluid models can account of some of these effects[1,2] . Here we introduce a new fluid model and closure for collisionless magnetic reconnection and more general applications. Taking moments of the kinetic equation, we evolve the full pressure tensor for electrons and ions, which includes the off diagonal terms necessary for reconnection. Kinetic effects are recovered by using a nonlocal heat flux closure, which approximates linear Landau damping in the fluid framework [3]. Using the island coalescence problem as a test, we show how the nonlocal ion closure improves on the typical collisional closures used for ten-moment models and circumvents the need for a colllisional free parameter. Finally, we extend the closure to study guide-field reconnection and discuss the implementation of a twenty-moment model.[1] A. Stanier et al. Phys Rev Lett (2015)[2] J. Ng et al. Phys Plasmas (2015)[3] G. Hammett et al. Phys Rev Lett (1990)
A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used t...
DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

We developed a framework for dislocation-based viscoplasticity and dynamic ductile failure to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. Furthermore, an averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Inmore » addition, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in [J. Wilkerson and K. Ramesh. A dynamic void growth model governed by dislocation kinetics. J. Mech. Phys. Solids, 70:262–280, 2014.], which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.« less

On the modeling of epidemics under the influence of risk perception

NASA Astrophysics Data System (ADS)

de Lillo, S.; Fioriti, G.; Prioriello, M. L.

An epidemic spreading model is presented in the framework of the kinetic theory of active particles. The model is characterized by the influence of risk perception which can reduce the diffusion of infection. The evolution of the system is modeled through nonlinear interactions, whose output is described by stochastic games. The results of numerical simulations are discussed for different initial conditions.
Development of SSUBPIC code for modeling the neutral gas depletion effect in helicon discharges

NASA Astrophysics Data System (ADS)

Kollasch, Jeffrey; Sovenic, Carl; Schmitz, Oliver

2017-10-01

The SSUBPIC (steady-state unstructured-boundary particle-in-cell) code is being developed to model helicon plasma devices. The envisioned modeling framework incorporates (1) a kinetic neutral particle model, (2) a kinetic ion model, (3) a fluid electron model, and (4) an RF power deposition model. The models are loosely coupled and iterated until convergence to steady-state. Of the four required solvers, the kinetic ion and neutral particle simulation can now be done within the SSUBPIC code. Recent SSUBPIC modifications include implementation and testing of a Coulomb collision model (Lemons et al., JCP, 228(5), pp. 1391-1403) allowing efficient coupling of kineticly-treated ions to fluid electrons, and implementation of a neutral particle tracking mode with charge-exchange and electron impact ionization physics. These new simulation capabilities are demonstrated working independently and coupled to ``dummy'' profiles for RF power deposition to converge on steady-state plasma and neutral profiles. The geometry and conditions considered are similar to those of the MARIA experiment at UW-Madison. Initial results qualitatively show the expected neutral gas depletion effect in which neutrals in the plasma core are not replenished at a sufficient rate to sustain a higher plasma density. This work is funded by the NSF CAREER award PHY-1455210 and NSF Grant PHY-1206421.
KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems

PubMed Central

2014-01-01

Background The kinetic modeling of biological systems is mainly composed of three steps that proceed iteratively: model building, simulation and analysis. In the first step, it is usually required to set initial metabolite concentrations, and to assign kinetic rate laws, along with estimating parameter values using kinetic data through optimization when these are not known. Although the rapid development of high-throughput methods has generated much omics data, experimentalists present only a summary of obtained results for publication, the experimental data files are not usually submitted to any public repository, or simply not available at all. In order to automatize as much as possible the steps of building kinetic models, there is a growing requirement in the systems biology community for easily exchanging data in combination with models, which represents the main motivation of KiMoSys development. Description KiMoSys is a user-friendly platform that includes a public data repository of published experimental data, containing concentration data of metabolites and enzymes and flux data. It was designed to ensure data management, storage and sharing for a wider systems biology community. This community repository offers a web-based interface and upload facility to turn available data into publicly accessible, centralized and structured-format data files. Moreover, it compiles and integrates available kinetic models associated with the data. KiMoSys also integrates some tools to facilitate the kinetic model construction process of large-scale metabolic networks, especially when the systems biologists perform computational research. Conclusions KiMoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects. The web application implemented using Ruby on Rails framework is freely available for web access at http://kimosys.org, along with its full documentation. PMID:25115331
A hybrid model describing ion induced kinetic electron emission

NASA Astrophysics Data System (ADS)

Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.

2015-06-01

We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.
Generic analysis of kinetically driven inflation

NASA Astrophysics Data System (ADS)

Saitou, Rio

2018-04-01

We perform a model-independent analysis of kinetically driven inflation (KDI) which (partially) includes generalized G-inflation and ghost inflation. We evaluate the background evolution splitting into the inflationary attractor and the perturbation around it. We also consider the quantum fluctuation of the scalar mode with a usual scaling and derive the spectral index, ignoring the contribution from the second-order products of slow-roll parameters. Using these formalisms, we find that within our generic framework the models of KDI which possess the shift symmetry of scalar field cannot create the quantum fluctuation consistent with the observation. Breaking the shift symmetry, we obtain a few essential conditions for viable models of KDI associated with the graceful exit.
Microstructure development in Kolmogorov, Johnson-Mehl, and Avrami nucleation and growth kinetics

NASA Astrophysics Data System (ADS)

Pineda, Eloi; Crespo, Daniel

1999-08-01

A statistical model with the ability to evaluate the microstructure developed in nucleation and growth kinetics is built in the framework of the Kolmogorov, Johnson-Mehl, and Avrami theory. A populational approach is used to compute the observed grain-size distribution. The impingement process which delays grain growth is analyzed, and the effective growth rate of each population is estimated considering the previous grain history. The proposed model is integrated for a wide range of nucleation and growth protocols, including constant nucleation, pre-existing nuclei, and intermittent nucleation with interface or diffusion-controlled grain growth. The results are compared with Monte Carlo simulations, giving quantitative agreement even in cases where previous models fail.
A physics-based crystallographic modeling framework for describing the thermal creep behavior of Fe-Cr alloys

DOE PAGES

Wen, Wei; Capolungo, Laurent; Patra, Anirban; ...

2017-02-23

In this work, a physics-based thermal creep model is developed based on the understanding of the microstructure in Fe-Cr alloys. This model is associated with a transition state theory based framework that considers the distribution of internal stresses at sub-material point level. The thermally activated dislocation glide and climb mechanisms are coupled in the obstacle-bypass processes for both dislocation and precipitate-type barriers. A kinetic law is proposed to track the dislocation densities evolution in the subgrain interior and in the cell wall. The predicted results show that this model, embedded in the visco-plastic self-consistent (VPSC) framework, captures well the creepmore » behaviors for primary and steady-state stages under various loading conditions. We also discuss the roles of the mechanisms involved.« less
A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosen...
Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

NASA Astrophysics Data System (ADS)

Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

2017-06-01

Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.
Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James

2013-12-14

Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. Moremore » recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.« less
A Rational Reconstruction of the Kinetic Molecular Theory of Gases Based on History and Philosophy of Science and Its Implications for Chemistry Textbooks.

ERIC Educational Resources Information Center

Niaz, Mansoor

2000-01-01

Describes a study that was designed to develop a framework for examining the way in which chemistry textbooks describe the kinetic theory and related issues. The framework was developed by a rational reconstruction of the kinetic molecular theory of gases based on historians and philosophers of science. (Contains 102 references.)(Author/LRW)
Simulations of anti-parallel reconnection using a nonlocal heat flux closure

DOE PAGES

Ng, Jonathan; Hakim, Ammar; Bhattacharjee, A.; ...

2017-08-08

The integration of kinetic effects in fluid models is important for global simulations of the Earth's magnetosphere. In particular, it has been shown that ion kinetics play a crucial role in the dynamics of large reconnecting systems, and that higher-order fluid moment models can account for some of these effects. Here, we use a ten-moment model for electrons and ions, which includes the off diagonal elements of the pressure tensor that are important for magnetic reconnection. Kinetic effects are recovered by using a nonlocal heat flux closure, which approximates linear Landau damping in the fluid framework. Moreover, the closure ismore » tested using the island coalescence problem, which is sensitive to ion dynamics. We also demonstrate that the nonlocal closure is able to self-consistently reproduce the structure of the ion diffusion region, pressure tensor, and ion velocity without the need for fine-tuning of relaxation coefficients present in earlier models.« less
Retrieval of daytime [O3] altitude profile from measurements of 1.27 μm O2 emission in the mesosphere: a comparison of methods

NASA Astrophysics Data System (ADS)

Yankovsky, Valentine A.; Manuilova, Rada O.

2017-11-01

The altitude profiles of ozone concentration are retrieved from measurements of the volume emission rate in the 1.27 μm oxygen band in the TIMED-SABER experiment. In this study we compare the methods of retrieval of daytime [O3] altitude profile in the framework of two models: electronic-vibrational kinetics and a purely electronic kinetics of excited products of ozone and oxygen photolysis. In order to retrieve the [O3] altitude profile from the measurements of the intensity of the O2 band in the region of 1.27 μm correctly, it is necessary to use the photochemical model of the electronic-vibrational kinetics of excited products of ozone and oxygen photolysis in the mesosphere and lower thermosphere.
Kinetic Methods for Understanding Linker Exchange in Metal-Organic Frameworks

NASA Astrophysics Data System (ADS)

Morabito, Joseph V.

Exchange reactions have enabled a new level of control in the rational, stepwise preparation of metal-organic framework (MOF) materials. However, their full potential is limited by a lack of understanding of the molecular mechanisms by which they occur. This dissertation describes our efforts to understand this important class of reactions in two parts. The first reports our use of a linker exchange process to encapsulate guest molecules larger than the limiting pore aperture of the MOF. The concept is demonstrated, along with evidence for guest encapsulation and its relation to a dissociative linker exchange process. The second part describes our development of the first quantitative kinetic method for studying MOF linker exchange reactions and our application of this method to understand the solvent dependence of the reaction of ZIF-8 with imidazole. This project involved the collection of the largest set of rate data available on any MOF linker exchange reaction. The combination of this dataset with small molecule encapsulation experiments allowed us to formulate a mechanistic model that could account for all the observed kinetic and structural data. By comparison with the kinetic behavior of complexes in solution, we were able to fit the kinetic behavior of ZIF-8 into the broader family of coordination compounds. Aside from the specific use that our kinetic data may have in predicting the reactivity of ZIF linker exchange, we hope that the conceptual bridges made between MOFs and related metal?organic compounds can help reveal underlying patterns in behavior and advance the field.
Quantum kinetic expansion in the spin-boson model: Matrix formulation and system-bath factorized initial state.

PubMed

Gong, Zhihao; Tang, Zhoufei; Wang, Haobin; Wu, Jianlan

2017-12-28

Within the framework of the hierarchy equation of motion (HEOM), the quantum kinetic expansion (QKE) method of the spin-boson model is reformulated in the matrix representation. The equivalence between the two formulations (HEOM matrices and quantum operators) is numerically verified from the calculation of the time-integrated QKE rates. The matrix formulation of the QKE is extended to the system-bath factorized initial state. Following a one-to-one mapping between HEOM matrices and quantum operators, a quantum kinetic equation is rederived. The rate kernel is modified by an extra term following a systematic expansion over the site-site coupling. This modified QKE is numerically tested for its reliability by calculating the time-integrated rate and non-Markovian population kinetics. For an intermediate-to-strong dissipation strength and a large site-site coupling, the population transfer is found to be significantly different when the initial condition is changed from the local equilibrium to system-bath factorized state.
What happens in the skin? Integrating skin permeation kinetics into studies of developmental and reproductive toxicity following topical exposure.

PubMed

Dancik, Yuri; Bigliardi, Paul L; Bigliardi-Qi, Mei

2015-12-01

Animal-based developmental and reproductive toxicological studies involving skin exposure rarely incorporate information on skin permeation kinetics. For practical reasons, animal studies cannot investigate the many factors which can affect human skin permeation and systemic uptake kinetics in real-life scenarios. Traditional route-to-route extrapolation is based on the same types of experiments and requires assumptions regarding route similarity. Pharmacokinetic modeling based on skin physiology and structure is the most efficient way to incorporate the variety of intrinsic skin and exposure-dependent parameters occurring in clinical and occupational settings into one framework. Physiologically-based pharmacokinetic models enable the integration of available in vivo, in vitro and in silico data to quantitatively predict the kinetics of uptake at the site of interest, as needed for 21st century toxicology and risk assessment. As demonstrated herein, proper interpretation and integration of these data is a multidisciplinary endeavor requiring toxicological, risk assessment, mathematical, pharmaceutical, biological and dermatological expertise. Copyright © 2015 Elsevier Inc. All rights reserved.
Shock tube study of the fuel structure effects on the chemical kinetic mechanisms responsible for soot formation, part 2

NASA Technical Reports Server (NTRS)

Frenklach, M.; Clary, D. W.; Ramachandra, M. K.

1985-01-01

Soot formation in oxidation of allene, 1,3-butadiene, vinylacetylene and chlorobenzene and in pyrolysis of ethylene, vinylacetylene, 1-butene, chlorobenzene, acetylen-hydrogen, benzene-acetylene, benzene-butadiene and chlorobenzene-acetylene argon-diluted mixtures was studied behind reflected shock waves. The results are rationalized within the framework of the conceptual models. It is shown that vinylacetylene is much less sooty than allene, which indicates that conjugation by itself is not a sufficient factor for determining the sooting tendency of a molecule. Structural reactivity in the context of the chemical kinetics is the dominant factor in soot formation. Detailed chemical kinetic modeling of soot formation in pyrolysis of acetylene is reported. The main mass growth was found to proceed through a single dominant route composed of conventional radical reactions. The practically irreversible formation reactions of the fused polycyclic aromatics and the overshoot by hydrogen atom over its equilibrium concentration are the g-driving kinetic forces for soot formation.
Crystallization of isotactic polypropylene in different shear regimes

NASA Astrophysics Data System (ADS)

Spina, Roberto; Spekowius, Marcel; Hopmann, Christian

2017-10-01

The investigation of the shear-induced crystallization of isotactic polypropylene in isothermal conditions in different shear regimes is the aim of the present research. A multiscale framework is developed and implemented to compute the nucleation and growth of spherulites, based on material parameters needed to connect crystallization kinetics to the molecular material properties. The framework consists of a macro-model based on a Finite Element Method linked to a micro-model based on Cellular Automata. The main results are the evolution of the crystallization degree and spherulite space filling as a function of imposed temperature ash shear rate.
Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

PubMed

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential equations on probability distributions. We developed a C++ software, MaBoSS, that is able to simulate such a system by applying Kinetic Monte-Carlo (or Gillespie algorithm) on the Boolean state space. This software, parallelized and optimized, computes the temporal evolution of probability distributions and estimates stationary distributions. Applications of the Boolean Kinetic Monte-Carlo are demonstrated for three qualitative models: a toy model, a published model of p53/Mdm2 interaction and a published model of the mammalian cell cycle. Our approach allows to describe kinetic phenomena which were difficult to handle in the original models. In particular, transient effects are represented by time dependent probability distributions, interpretable in terms of cell populations.
Image-based modeling of tumor shrinkage in head and neck radiation therapy1

PubMed Central

Chao, Ming; Xie, Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing, Lei

2010-01-01

Purpose: Understanding the kinetics of tumor growth∕shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the “ground truth” with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy. PMID:20527569

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

PubMed

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018 Institute of Physics and Engineering in Medicine.
Role of Sink Density in Nonequilibrium Chemical Redistribution in Alloys

DOE PAGES

Martinez, Enrique Saez; Senninger, Oriane; Caro, Alfredo; ...

2018-03-08

Nonequilibrium chemical redistribution in open systems submitted to external forces, such as particle irradiation, leads to changes in the structural properties of the material, potentially driving the system to failure. Such redistribution is controlled by the complex interplay between the production of point defects, atomic transport rates, and the sink character of the microstructure. In this work, we analyze this interplay by means of a kinetic Monte Carlo (KMC) framework with an underlying atomistic model for the Fe-Cr model alloy to study the effect of ideal defect sinks on Cr concentration profiles, with a particular focus on the role ofmore » interface density. We observe that the amount of segregation decreases linearly with decreasing interface spacing. Within the framework of the thermodynamics of irreversible processes, a general analytical model is derived and assessed against the KMC simulations to elucidate the structure-property relationship of this system. Interestingly, in the kinetic regime where elimination of point defects at sinks is dominant over bulk recombination, the solute segregation does not directly depend on the dose rate but only on the density of sinks. Furthermore, this model provides new insight into the design of microstructures that mitigate chemical redistribution and improve radiation tolerance.« less
Role of Sink Density in Nonequilibrium Chemical Redistribution in Alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martinez, Enrique Saez; Senninger, Oriane; Caro, Alfredo

Nonequilibrium chemical redistribution in open systems submitted to external forces, such as particle irradiation, leads to changes in the structural properties of the material, potentially driving the system to failure. Such redistribution is controlled by the complex interplay between the production of point defects, atomic transport rates, and the sink character of the microstructure. In this work, we analyze this interplay by means of a kinetic Monte Carlo (KMC) framework with an underlying atomistic model for the Fe-Cr model alloy to study the effect of ideal defect sinks on Cr concentration profiles, with a particular focus on the role ofmore » interface density. We observe that the amount of segregation decreases linearly with decreasing interface spacing. Within the framework of the thermodynamics of irreversible processes, a general analytical model is derived and assessed against the KMC simulations to elucidate the structure-property relationship of this system. Interestingly, in the kinetic regime where elimination of point defects at sinks is dominant over bulk recombination, the solute segregation does not directly depend on the dose rate but only on the density of sinks. Furthermore, this model provides new insight into the design of microstructures that mitigate chemical redistribution and improve radiation tolerance.« less
Role of Sink Density in Nonequilibrium Chemical Redistribution in Alloys

NASA Astrophysics Data System (ADS)

Martínez, Enrique; Senninger, Oriane; Caro, Alfredo; Soisson, Frédéric; Nastar, Maylise; Uberuaga, Blas P.

2018-03-01

Nonequilibrium chemical redistribution in open systems submitted to external forces, such as particle irradiation, leads to changes in the structural properties of the material, potentially driving the system to failure. Such redistribution is controlled by the complex interplay between the production of point defects, atomic transport rates, and the sink character of the microstructure. In this work, we analyze this interplay by means of a kinetic Monte Carlo (KMC) framework with an underlying atomistic model for the Fe-Cr model alloy to study the effect of ideal defect sinks on Cr concentration profiles, with a particular focus on the role of interface density. We observe that the amount of segregation decreases linearly with decreasing interface spacing. Within the framework of the thermodynamics of irreversible processes, a general analytical model is derived and assessed against the KMC simulations to elucidate the structure-property relationship of this system. Interestingly, in the kinetic regime where elimination of point defects at sinks is dominant over bulk recombination, the solute segregation does not directly depend on the dose rate but only on the density of sinks. This model provides new insight into the design of microstructures that mitigate chemical redistribution and improve radiation tolerance.
Nanosecond Plasma Enhanced H2/O2/N2 Premixed Flat Flames

DTIC Science & Technology

2014-01-01

Simulations are conducted with a one-dimensional, multi-scale, pulsed -discharge model with detailed plasma-combustion kinetics to develop additional insight... model framework. The reduced electric field, E/N, during each pulse varies inversely with number density. A significant portion of the input energy is...dimensional numerical model [4, 12] capable of resolving electric field transients over nanosecond timescales (during each discharge pulse ) and radical
Onsager's variational principle in soft matter.

PubMed

Doi, Masao

2011-07-20

In the celebrated paper on the reciprocal relation for the kinetic coefficients in irreversible processes, Onsager (1931 Phys. Rev. 37 405) extended Rayleigh's principle of the least energy dissipation to general irreversible processes. In this paper, I shall show that this variational principle gives us a very convenient framework for deriving many established equations which describe the nonlinear and non-equilibrium phenomena in soft matter, such as phase separation kinetics in solutions, gel dynamics, molecular modeling for viscoelasticity nemato-hydrodynamics, etc. Onsager's variational principle can therefore be regarded as a solid general basis for soft matter physics.
Adding kinetics and hydrodynamics to the CHEETAH thermochemical code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fried, L.E., Howard, W.M., Souers, P.C.

1997-01-15

In FY96 we released CHEETAH 1.40, which made extensive improvements on the stability and user friendliness of the code. CHEETAH now has over 175 users in government, academia, and industry. Efforts have also been focused on adding new advanced features to CHEETAH 2.0, which is scheduled for release in FY97. We have added a new chemical kinetics capability to CHEETAH. In the past, CHEETAH assumed complete thermodynamic equilibrium and independence of time. The addition of a chemical kinetic framework will allow for modeling of time-dependent phenomena, such as partial combustion and detonation in composite explosives with large reaction zones. Wemore » have implemented a Wood-Kirkwood detonation framework in CHEETAH, which allows for the treatment of nonideal detonations and explosive failure. A second major effort in the project this year has been linking CHEETAH to hydrodynamic codes to yield an improved HE product equation of state. We have linked CHEETAH to 1- and 2-D hydrodynamic codes, and have compared the code to experimental data. 15 refs., 13 figs., 1 tab.« less
The influence of precipitation kinetics on trace element partitioning between solid and liquid solutions: A coupled fluid dynamics/thermodynamics framework to predict distribution coefficients

NASA Astrophysics Data System (ADS)

Kavner, A.

2017-12-01

In a multicomponent multiphase geochemical system undergoing a chemical reaction such as precipitation and/or dissolution, the partitioning of species between phases is determined by a combination of thermodynamic properties and transport processes. The interpretation of the observed distribution of trace elements requires models integrating coupled chemistry and mechanical transport. Here, a framework is presented that predicts the kinetic effects on the distribution of species between two reacting phases. Based on a perturbation theory combining Navier-Stokes fluid flow and chemical reactivity, the framework predicts rate-dependent partition coefficients in a variety of different systems. We present the theoretical framework, with applications to two systems: 1. species- and isotope-dependent Soret diffusion of species in a multicomponent silicate melt subjected to a temperature gradient, and 2. Elemental partitioning and isotope fractionation during precipitation of a multicomponent solid from a multicomponent liquid phase. Predictions will be compared with results from experimental studies. The approach has applications for understanding chemical exchange in at boundary layers such as the Earth's surface magmatic systems and at the core/mantle boundary.
Emergent kinetic constraints, ergodicity breaking, and cooperative dynamics in noisy quantum systems

NASA Astrophysics Data System (ADS)

Everest, B.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.

2016-11-01

Kinetically constrained spin systems play an important role in understanding key properties of the dynamics of slowly relaxing materials, such as glasses. Recent experimental studies have revealed that manifest kinetic constraints govern the evolution of strongly interacting gases of highly excited atoms in a noisy environment. Motivated by this development we explore which types of kinetically constrained dynamics can generally emerge in quantum spin systems subject to strong noise and show how, in this framework, constraints are accompanied by conservation laws. We discuss an experimentally realizable case of a lattice gas, where the interplay between those and the geometry of the lattice leads to collective behavior and time-scale separation even at infinite temperature. This is in contrast to models of glass-forming substances which typically rely on low temperatures and the consequent suppression of thermal activation.
Microbial respiration and dissolution precipitation reactions of minerals: thermo-kinetics and reactive transport modelling

NASA Astrophysics Data System (ADS)

Azaroual, M. M.; Parmentier, M.; Andre, L.; Croiset, N.; Pettenati, M.; Kremer, S.

2010-12-01

Microbial processes interact closely with abiotic geochemical reactions and mineralogical transformations in several hydrogeochemical systems. Reactive transport models are aimed to analyze these complex mechanisms integrating as well as the degradation of organic matter as the redox reactions involving successive terminal electron acceptors (TEAPs) mediated by microbes through the continuum of unsaturated zone (soil) - saturated zone (aquifer). The involvement of microbial processes in reactive transport in soil and subsurface geologic greatly complicates the mastery of the major mechanisms and the numerical modelling of these systems. The introduction of kinetic constraints of redox reactions in aqueous phase requires the decoupling of equilibrium reactions and the redefinition of mass balance of chemical elements including the concept of basis species and secondary species of thermodynamic databases used in geochemical modelling tools. An integrated methodology for modelling the reactive transport has been developed and implemented to simulate the transfer of arsenic, denitrification processes and the role of metastable aqueous sulfur species with pyrite and organic matter as electron donors entities. A mechanistic rate law of microbial respiration in various geochemical environments was used to simulate reactive transport of arsenic, nitrate and organic matter combined to the generalized rate law of mineral dissolution - precipitation reactions derived from the transition state theory was used for dissolution - precipitation of silica, aluminosilicate, carbonate, oxyhydroxide, and sulphide minerals. The kinetic parameters are compiled from the literature measurements based on laboratory constrained experiments and field observations. Numerical simulations, using the geochemical software PHREEQC, were performed aiming to identify the key reactions mediated by microbes in the framework of in the first hand the concept of the unsaturated - saturated zones of an artificial recharge of deep aquifers system and in a second hand an acid mine drainage system. A large amount of data is available on the old mine site of Cheni (France). This field data on acid mine drainage are compared to a thermokinetic model including biological kinetics, precipitation-dissolution kinetics and surface complexation on ferrihydrite. The kinetic parameters are from literature and from a fitting on batch biological experiments. The integrated approach combining reaction kinetics and biogeochemical thermodynamic constraints is successfully applied to denitrification experiments in the presence of acetate and pyrite conducted in the laboratory for batch and column systems. The powerful of this coupled approach allows a fine description of the different transition species from nitrate to nitrogen. The fitted kinetic parameters established for modelling these laboratory results are thus extended to simulate the denitrification processes in a field case where organic matter and pyrite FeS2 are the electron donors and O2, NO3, Fe(OH)3, SO4 are the electron acceptors in the framework of a continuum UZ - SZ aiming to identify the stabilized redox zones of acid mine drainage. The detailed results obtained on two actual case studies will be presented.
Construction and comparison of parallel implicit kinetic solvers in three spatial dimensions

NASA Astrophysics Data System (ADS)

Titarev, Vladimir; Dumbser, Michael; Utyuzhnikov, Sergey

2014-01-01

The paper is devoted to the further development and systematic performance evaluation of a recent deterministic framework Nesvetay-3D for modelling three-dimensional rarefied gas flows. Firstly, a review of the existing discretization and parallelization strategies for solving numerically the Boltzmann kinetic equation with various model collision integrals is carried out. Secondly, a new parallelization strategy for the implicit time evolution method is implemented which improves scaling on large CPU clusters. Accuracy and scalability of the methods are demonstrated on a pressure-driven rarefied gas flow through a finite-length circular pipe as well as an external supersonic flow over a three-dimensional re-entry geometry of complicated aerodynamic shape.
A Combined Kinetic and Volatility Basis Set Approach to Model Secondary Organic Aerosol from Toluene and Diesel Exhaust/Meat Cooking Mixtures

NASA Astrophysics Data System (ADS)

Parikh, H. M.; Carlton, A. G.; Zhang, H.; Kamens, R.; Vizuete, W.

2011-12-01

Secondary organic aerosol (SOA) is simulated for 6 outdoor smog chamber experiments using a SOA model based on a kinetic chemical mechanism in conjunction with a volatility basis set (VBS) approach. The experiments include toluene, a non-SOA-forming hydrocarbon mixture, diesel exhaust or meat cooking emissions and NOx, and are performed under varying conditions of relative humidity. SOA formation from toluene is modeled using a condensed kinetic aromatic mechanism that includes partitioning of lumped semi-volatile products in particle organic-phase and incorporates particle aqueous-phase chemistry to describe uptake of glyoxal and methylglyoxal. Modeling using the kinetic mechanism alone, along with primary organic aerosol (POA) from diesel exhaust (DE) /meat cooking (MC) fails to simulate the rapid SOA formation at the beginning hours of the experiments. Inclusion of a VBS approach with the kinetic mechanism to characterize the emissions and chemistry of complex mixture of intermediate volatility organic compounds (IVOCs) from DE/MC, substantially improves SOA predictions when compared with observed data. The VBS model includes photochemical aging of IVOCs and evaporation of POA after dilution. The relative contribution of SOA mass from DE/MC is as high as 95% in the morning, but substantially decreases after mid-afternoon. For high humidity experiments, aqueous-phase SOA fraction dominates the total SOA mass at the end of the day (approximately 50%). In summary, the combined kinetic and VBS approach provides a new and improved framework to semi-explicitly model SOA from VOC precursors in conjunction with a VBS approach that can be used on complex emission mixtures comprised with hundreds of individual chemical species.
Integration of biotic ligand models (BLM) and bioaccumulation kinetics into a mechanistic framework for metal uptake in aquatic organisms.

PubMed

Veltman, Karin; Huijbregts, Mark A J; Hendriks, A Jan

2010-07-01

Both biotic ligand models (BLM) and bioaccumulation models aim to quantify metal exposure based on mechanistic knowledge, but key factors included in the description of metal uptake differ between the two approaches. Here, we present a quantitative comparison of both approaches and show that BLM and bioaccumulation kinetics can be merged into a common mechanistic framework for metal uptake in aquatic organisms. Our results show that metal-specific absorption efficiencies calculated from BLM-parameters for freshwater fish are highly comparable, i.e. within a factor of 2.4 for silver, cadmium, copper, and zinc, to bioaccumulation-absorption efficiencies for predominantly marine fish. Conditional affinity constants are significantly related to the metal-specific covalent index. Additionally, the affinity constants of calcium, cadmium, copper, sodium, and zinc are significantly comparable across aquatic species, including molluscs, daphnids, and fish. This suggests that affinity constants can be estimated from the covalent index, and constants can be extrapolated across species. A new model is proposed that integrates the combined effect of metal chemodynamics, as speciation, competition, and ligand affinity, and species characteristics, as size, on metal uptake by aquatic organisms. An important direction for further research is the quantitative comparison of the proposed model with acute toxicity values for organisms belonging to different size classes.
An extensible framework for capturing solvent effects in computer generated kinetic models.

PubMed

Jalan, Amrit; West, Richard H; Green, William H

2013-03-14

Detailed kinetic models provide useful mechanistic insight into a chemical system. Manual construction of such models is laborious and error-prone, which has led to the development of automated methods for exploring chemical pathways. These methods rely on fast, high-throughput estimation of species thermochemistry and kinetic parameters. In this paper, we present a methodology for extending automatic mechanism generation to solution phase systems which requires estimation of solvent effects on reaction rates and equilibria. The linear solvation energy relationship (LSER) method of Abraham and co-workers is combined with Mintz correlations to estimate ΔG(solv)°(T) in over 30 solvents using solute descriptors estimated from group additivity. Simple corrections are found to be adequate for the treatment of radical sites, as suggested by comparison with known experimental data. The performance of scaled particle theory expressions for enthalpic-entropic decomposition of ΔG(solv)°(T) is also presented along with the associated computational issues. Similar high-throughput methods for solvent effects on free-radical kinetics are only available for a handful of reactions due to lack of reliable experimental data, and continuum dielectric calculations offer an alternative method for their estimation. For illustration, we model liquid phase oxidation of tetralin in different solvents computing the solvent dependence for ROO• + ROO• and ROO• + solvent reactions using polarizable continuum quantum chemistry methods. The resulting kinetic models show an increase in oxidation rate with solvent polarity, consistent with experiment. Further work needed to make this approach more generally useful is outlined.
A Hierarchy of Heuristic-Based Models of Crowd Dynamics

NASA Astrophysics Data System (ADS)

Degond, P.; Appert-Rolland, C.; Moussaïd, M.; Pettré, J.; Theraulaz, G.

2013-09-01

We derive a hierarchy of kinetic and macroscopic models from a noisy variant of the heuristic behavioral Individual-Based Model of Ngai et al. (Disaster Med. Public Health Prep. 3:191-195, 2009) where pedestrians are supposed to have constant speeds. This IBM supposes that pedestrians seek the best compromise between navigation towards their target and collisions avoidance. We first propose a kinetic model for the probability distribution function of pedestrians. Then, we derive fluid models and propose three different closure relations. The first two closures assume that the velocity distribution function is either a Dirac delta or a von Mises-Fisher distribution respectively. The third closure results from a hydrodynamic limit associated to a Local Thermodynamical Equilibrium. We develop an analogy between this equilibrium and Nash equilibria in a game theoretic framework. In each case, we discuss the features of the models and their suitability for practical use.
Assessment of methane biodegradation kinetics in two-phase partitioning bioreactors by pulse respirometry.

PubMed

Ordaz, Alberto; López, Juan C; Figueroa-González, Ivonne; Muñoz, Raúl; Quijano, Guillermo

2014-12-15

Biological methane biodegradation is a promising treatment alternative when the methane produced in waste management facilities cannot be used for energy generation. Two-phase partitioning bioreactors (TPPBs), provided with a non-aqueous phase (NAP) with high affinity for the target pollutant, are particularly suitable for the treatment of poorly water-soluble compounds such as methane. Nevertheless, little is known about the influence of the presence of the NAP on the resulting biodegradation kinetics in TPPBs. In this study, an experimental framework based on the in situ pulse respirometry technique was developed to assess the impact of NAP addition on the methane biodegradation kinetics using Methylosinus sporium as a model methane-degrading microorganism. A comprehensive mass transfer characterization was performed in order to avoid mass transfer limiting scenarios and ensure a correct kinetic parameter characterization. The presence of the NAP mediated significant changes in the apparent kinetic parameters of M. sporium during methane biodegradation, with variations of 60, 120, and 150% in the maximum oxygen uptake rate, half-saturation constant and maximum specific growth rate, respectively, compared with the intrinsic kinetic parameters retrieved from a control without NAP. These significant changes in the kinetic parameters mediated by the NAP must be considered for the design, operation and modeling of TPPBs devoted to air pollution control. Copyright © 2014 Elsevier Ltd. All rights reserved.
Kinetic modeling of secondary organic aerosol formation: effects of particle- and gas-phase reactions of semivolatile products

NASA Astrophysics Data System (ADS)

Chan, A. W. H.; Kroll, J. H.; Ng, N. L.; Seinfeld, J. H.

2007-08-01

The distinguishing mechanism of formation of secondary organic aerosol (SOA) is the partitioning of semivolatile hydrocarbon oxidation products between the gas and aerosol phases. While SOA formation is typically described in terms of partitioning only, the rate of formation and ultimate yield of SOA can also depend on the kinetics of both gas- and aerosol-phase processes. We present a general equilibrium/kinetic model of SOA formation that provides a framework for evaluating the extent to which the controlling mechanisms of SOA formation can be inferred from laboratory chamber data. With this model we examine the effect on SOA formation of gas-phase oxidation of first-generation products to either more or less volatile species, of particle-phase reaction (both first- and second-order kinetics), of the rate of parent hydrocarbon oxidation, and of the extent of reaction of the parent hydrocarbon. The effect of pre-existing organic aerosol mass on SOA yield, an issue of direct relevance to the translation of laboratory data to atmospheric applications, is examined. The importance of direct chemical measurements of gas- and particle-phase species is underscored in identifying SOA formation mechanisms.
Kinetic modeling of Secondary Organic Aerosol formation: effects of particle- and gas-phase reactions of semivolatile products

NASA Astrophysics Data System (ADS)

Chan, A. W. H.; Kroll, J. H.; Ng, N. L.; Seinfeld, J. H.

2007-05-01

The distinguishing mechanism of formation of secondary organic aerosol (SOA) is the partitioning of semivolatile hydrocarbon oxidation products between the gas and aerosol phases. While SOA formation is typically described in terms of partitioning only, the rate of formation and ultimate yield of SOA can also depend on the kinetics of both gas- and aerosol-phase processes. We present a general equilibrium/kinetic model of SOA formation that provides a framework for evaluating the extent to which the controlling mechanisms of SOA formation can be inferred from laboratory chamber data. With this model we examine the effect on SOA formation of gas-phase oxidation of first-generation products to either more or less volatile species, of particle-phase reaction (both first- and second-order kinetics), of the rate of parent hydrocarbon oxidation, and of the extent of reaction of the parent hydrocarbon. The effect of pre-existing organic aerosol mass on SOA yield, an issue of direct relevance to the translation of laboratory data to atmospheric applications, is examined. The importance of direct chemical measurements of gas- and particle-phase species is underscored in identifying SOA formation mechanisms.
Modeling of uncertainties in biochemical reactions.

PubMed

Mišković, Ljubiša; Hatzimanikatis, Vassily

2011-02-01

Mathematical modeling is an indispensable tool for research and development in biotechnology and bioengineering. The formulation of kinetic models of biochemical networks depends on knowledge of the kinetic properties of the enzymes of the individual reactions. However, kinetic data acquired from experimental observations bring along uncertainties due to various experimental conditions and measurement methods. In this contribution, we propose a novel way to model the uncertainty in the enzyme kinetics and to predict quantitatively the responses of metabolic reactions to the changes in enzyme activities under uncertainty. The proposed methodology accounts explicitly for mechanistic properties of enzymes and physico-chemical and thermodynamic constraints, and is based on formalism from systems theory and metabolic control analysis. We achieve this by observing that kinetic responses of metabolic reactions depend: (i) on the distribution of the enzymes among their free form and all reactive states; (ii) on the equilibrium displacements of the overall reaction and that of the individual enzymatic steps; and (iii) on the net fluxes through the enzyme. Relying on this observation, we develop a novel, efficient Monte Carlo sampling procedure to generate all states within a metabolic reaction that satisfy imposed constrains. Thus, we derive the statistics of the expected responses of the metabolic reactions to changes in enzyme levels and activities, in the levels of metabolites, and in the values of the kinetic parameters. We present aspects of the proposed framework through an example of the fundamental three-step reversible enzymatic reaction mechanism. We demonstrate that the equilibrium displacements of the individual enzymatic steps have an important influence on kinetic responses of the enzyme. Furthermore, we derive the conditions that must be satisfied by a reversible three-step enzymatic reaction operating far away from the equilibrium in order to respond to changes in metabolite levels according to the irreversible Michelis-Menten kinetics. The efficient sampling procedure allows easy, scalable, implementation of this methodology to modeling of large-scale biochemical networks. © 2010 Wiley Periodicals, Inc.
Modeling Non-Steady Isotopologue and Isotopomer Speciation and Fractionation during Denitrification in Soils

NASA Astrophysics Data System (ADS)

Maggi, F.; Riley, W. J.

2009-12-01

The composition and location of 15N atoms on N2O isotopomers and isotopologues during isotope speciation has been used to characterize soil biological N cycling and N2O surface emissions. Although there exist few experimental observations, no attempt has been made to model N2O isotopomer speciation. The mathematical treatment of biological kinetic reactions in isotopic applications normally makes use of first-order and quasi steady-state complexation assumptions without taking into account changes in enzyme concentration, reaction stoichiometry, and isotopologue and isotopomer speciation. When multiatomic isotopically-labeled reactants are used in a multi-molecurar reaction, these assumptions may fail since they always lead to a constant fractionation factor and cannot describe speciation of isotopologues and isotopomers. We have developed a mathematical framework that is capable of describing isotopologue and isotopmer speciation and fractionation under the assumption of non-steady complexation during biological kinetic reactions that overcome the limitations mentioned above. This framework was applied to a case study of non-steady (variable and inverse) isotopic effects observed during N2O production and consumption in soils. Our mathematical treatment has led to generalized kinetic equations which replicate experimental observations with high accuracy and help interpret non-steady isotopic effects and isotopologue and isotopomer speciation. The kinetic equations introduced and applied here have general validity in describing isotopic effects in any biochemical reactions by considering: changing enzyme concentrations, mass and isotope conservation, and reaction stoichiometry. The equations also describe speciation of any isotopologue and isotopomer product from any isotopologue and isotopmer reactant.

Kinetic theory of two-temperature polyatomic plasmas

NASA Astrophysics Data System (ADS)

Orlac'h, Jean-Maxime; Giovangigli, Vincent; Novikova, Tatiana; Roca i Cabarrocas, Pere

2018-03-01

We investigate the kinetic theory of two-temperature plasmas for reactive polyatomic gas mixtures. The Knudsen number is taken proportional to the square root of the mass ratio between electrons and heavy-species, and thermal non-equilibrium between electrons and heavy species is allowed. The kinetic non-equilibrium framework also requires a weak coupling between electrons and internal energy modes of heavy species. The zeroth-order and first-order fluid equations are derived by using a generalized Chapman-Enskog method. Expressions for transport fluxes are obtained in terms of macroscopic variable gradients and the corresponding transport coefficients are expressed as bracket products of species perturbed distribution functions. The theory derived in this paper provides a consistent fluid model for non-thermal multicomponent plasmas.
A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models.

PubMed

Miskovic, Ljubisa; Alff-Tuomala, Susanne; Soh, Keng Cher; Barth, Dorothee; Salusjärvi, Laura; Pitkänen, Juha-Pekka; Ruohonen, Laura; Penttilä, Merja; Hatzimanikatis, Vassily

2017-01-01

Recent advancements in omics measurement technologies have led to an ever-increasing amount of available experimental data that necessitate systems-oriented methodologies for efficient and systematic integration of data into consistent large-scale kinetic models. These models can help us to uncover new insights into cellular physiology and also to assist in the rational design of bioreactor or fermentation processes. Optimization and Risk Analysis of Complex Living Entities (ORACLE) framework for the construction of large-scale kinetic models can be used as guidance for formulating alternative metabolic engineering strategies. We used ORACLE in a metabolic engineering problem: improvement of the xylose uptake rate during mixed glucose-xylose consumption in a recombinant Saccharomyces cerevisiae strain. Using the data from bioreactor fermentations, we characterized network flux and concentration profiles representing possible physiological states of the analyzed strain. We then identified enzymes that could lead to improved flux through xylose transporters (XTR). For some of the identified enzymes, including hexokinase (HXK), we could not deduce if their control over XTR was positive or negative. We thus performed a follow-up experiment, and we found out that HXK2 deletion improves xylose uptake rate. The data from the performed experiments were then used to prune the kinetic models, and the predictions of the pruned population of kinetic models were in agreement with the experimental data collected on the HXK2 -deficient S. cerevisiae strain. We present a design-build-test cycle composed of modeling efforts and experiments with a glucose-xylose co-utilizing recombinant S. cerevisiae and its HXK2 -deficient mutant that allowed us to uncover interdependencies between upper glycolysis and xylose uptake pathway. Through this cycle, we also obtained kinetic models with improved prediction capabilities. The present study demonstrates the potential of integrated "modeling and experiments" systems biology approaches that can be applied for diverse applications ranging from biotechnology to drug discovery.
Design Principles of DNA Enzyme-Based Walkers: Translocation Kinetics and Photoregulation.

PubMed

Cha, Tae-Gon; Pan, Jing; Chen, Haorong; Robinson, Heather N; Li, Xiang; Mao, Chengde; Choi, Jong Hyun

2015-07-29

Dynamic DNA enzyme-based walkers complete their stepwise movements along the prescribed track through a series of reactions, including hybridization, enzymatic cleavage, and strand displacement; however, their overall translocation kinetics is not well understood. Here, we perform mechanistic studies to elucidate several key parameters that govern the kinetics and processivity of DNA enzyme-based walkers. These parameters include DNA enzyme core type and structure, upper and lower recognition arm lengths, and divalent metal cation species and concentration. A theoretical model is developed within the framework of single-molecule kinetics to describe overall translocation kinetics as well as each reaction step. A better understanding of kinetics and design parameters enables us to demonstrate a walker movement near 5 μm at an average speed of ∼1 nm s(-1). We also show that the translocation kinetics of DNA walkers can be effectively controlled by external light stimuli using photoisomerizable azobenzene moieties. A 2-fold increase in the cleavage reaction is observed when the hairpin stems of enzyme catalytic cores are open under UV irradiation. This study provides general design guidelines to construct highly processive, autonomous DNA walker systems and to regulate their translocation kinetics, which would facilitate the development of functional DNA walkers.
Excellent performance of copper based metal organic framework in adsorptive removal of toxic sulfonamide antibiotics from wastewater.

PubMed

Azhar, Muhammad Rizwan; Abid, Hussein Rasool; Sun, Hongqi; Periasamy, Vijay; Tadé, Moses O; Wang, Shaobin

2016-09-15

The increasing concerns on toxicity of sulfonamide antibiotics in water require a prompt action to establish efficient wastewater treatment processes for their removal. In this study, adsorptive removal of a model sulfonamide antibiotic, sulfachloropyridazine (SCP), from wastewater is presented for the first time using a metal organic framework (MOF). A high surface area and thermally stable MOF, HKUST-1, was synthesized by a facile method. Batch adsorption studies were systematically carried out using HKUST-1. The high surface area and unsaturated metal sites resulted in a significant adsorption capacity with faster kinetics. Most of the SCP was removed in 15min and the kinetic data were best fitted with the pseudo second order model. Moreover, isothermal data were best fitted with the Langmuir model. The thermodynamic results showed that the adsorption is a spontaneous and endothermic process. The adsorption capacity of HKUST-1 is 384mg/g at 298K which is the highest compared to most of the materials for the antibiotics. The high adsorption capacity is attributed mainly to π-π stacking, hydrogen bonding and electrostatic interactions. Copyright © 2016 Elsevier Inc. All rights reserved.
Rational Design of Glucose-Responsive Insulin Using Pharmacokinetic Modeling.

PubMed

Bakh, Naveed A; Bisker, Gili; Lee, Michael A; Gong, Xun; Strano, Michael S

2017-11-01

A glucose responsive insulin (GRI) is a therapeutic that modulates its potency, concentration, or dosing of insulin in relation to a patient's dynamic glucose concentration, thereby approximating aspects of a normally functioning pancreas. Current GRI design lacks a theoretical basis on which to base fundamental design parameters such as glucose reactivity, dissociation constant or potency, and in vivo efficacy. In this work, an approach to mathematically model the relevant parameter space for effective GRIs is induced, and design rules for linking GRI performance to therapeutic benefit are developed. Well-developed pharmacokinetic models of human glucose and insulin metabolism coupled to a kinetic model representation of a freely circulating GRI are used to determine the desired kinetic parameters and dosing for optimal glycemic control. The model examines a subcutaneous dose of GRI with kinetic parameters in an optimal range that results in successful glycemic control within prescribed constraints over a 24 h period. Additionally, it is demonstrated that the modeling approach can find GRI parameters that enable stable glucose levels that persist through a skipped meal. The results provide a framework for exploring the parameter space of GRIs, potentially without extensive, iterative in vivo animal testing. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Microkinetic modeling of the autoxidative curing of an alkyd and oil-based paint model system

NASA Astrophysics Data System (ADS)

Oakley, Lindsay H.; Casadio, Francesca; Shull, Kenneth R.; Broadbelt, Linda J.

2015-11-01

Elucidating the curing and aging mechanisms of alkyd and other oil-based paints is valuable for the fields of conservation and bio-based coatings. Recent research has demonstrated the limitations of artificial aging in predicting the actual properties of paints that are hundreds of years old. Kinetic modeling offers pathways to develop a realistic and dynamic description of the composition of these oil-based paint coatings and facilitates the exploration of the effects of various environmental conditions on their long-term chemical stability. This work presents the construction of a kinetic Monte Carlo framework from elementary steps for the cobalt-catalyzed autoxidative curing of an ethyl linoleate model system up to the formation of single cross-links. Kinetic correlations for reaction families of similar chemistry are employed to reduce the number of parameters required to calculate rate constants in Arrhenius form. The model, developed from mechanisms proposed in the literature, shows good agreement with experiment for the formation of primary products in the early stages of curing. The model has also revealed that the mechanisms proposed in the literature for the formation of secondary products, such as volatile aldehydes, are still not well established, and alternative routes are under evaluation.
Thermostatted kinetic equations as models for complex systems in physics and life sciences.

PubMed

Bianca, Carlo

2012-12-01

Statistical mechanics is a powerful method for understanding equilibrium thermodynamics. An equivalent theoretical framework for nonequilibrium systems has remained elusive. The thermodynamic forces driving the system away from equilibrium introduce energy that must be dissipated if nonequilibrium steady states are to be obtained. Historically, further terms were introduced, collectively called a thermostat, whose original application was to generate constant-temperature equilibrium ensembles. This review surveys kinetic models coupled with time-reversible deterministic thermostats for the modeling of large systems composed both by inert matter particles and living entities. The introduction of deterministic thermostats allows to model the onset of nonequilibrium stationary states that are typical of most real-world complex systems. The first part of the paper is focused on a general presentation of the main physical and mathematical definitions and tools: nonequilibrium phenomena, Gauss least constraint principle and Gaussian thermostats. The second part provides a review of a variety of thermostatted mathematical models in physics and life sciences, including Kac, Boltzmann, Jager-Segel and the thermostatted (continuous and discrete) kinetic for active particles models. Applications refer to semiconductor devices, nanosciences, biological phenomena, vehicular traffic, social and economics systems, crowds and swarms dynamics. Copyright © 2012 Elsevier B.V. All rights reserved.
MESOSCOPIC MODELING OF STOCHASTIC REACTION-DIFFUSION KINETICS IN THE SUBDIFFUSIVE REGIME

PubMed Central

BLANC, EMILIE; ENGBLOM, STEFAN; HELLANDER, ANDREAS; LÖTSTEDT, PER

2017-01-01

Subdiffusion has been proposed as an explanation of various kinetic phenomena inside living cells. In order to fascilitate large-scale computational studies of subdiffusive chemical processes, we extend a recently suggested mesoscopic model of subdiffusion into an accurate and consistent reaction-subdiffusion computational framework. Two different possible models of chemical reaction are revealed and some basic dynamic properties are derived. In certain cases those mesoscopic models have a direct interpretation at the macroscopic level as fractional partial differential equations in a bounded time interval. Through analysis and numerical experiments we estimate the macroscopic effects of reactions under subdiffusive mixing. The models display properties observed also in experiments: for a short time interval the behavior of the diffusion and the reaction is ordinary, in an intermediate interval the behavior is anomalous, and at long times the behavior is ordinary again. PMID:29046618
Communication: Role of explicit water models in the helix folding/unfolding processes

NASA Astrophysics Data System (ADS)

Palazzesi, Ferruccio; Salvalaglio, Matteo; Barducci, Alessandro; Parrinello, Michele

2016-09-01

In the last years, it has become evident that computer simulations can assume a relevant role in modelling protein dynamical motions for their ability to provide a full atomistic image of the processes under investigation. The ability of the current protein force-fields in reproducing the correct thermodynamics and kinetics systems behaviour is thus an essential ingredient to improve our understanding of many relevant biological functionalities. In this work, employing the last developments of the metadynamics framework, we compare the ability of state-of-the-art all-atom empirical functions and water models to consistently reproduce the folding and unfolding of a helix turn motif in a model peptide. This theoretical study puts in evidence that the choice of the water models can influence the thermodynamic and the kinetics of the system under investigation, and for this reason cannot be considered trivial.
Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.

The U.S. Department of Energy (DOE) has developed a vehicle framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to DOE’s Technical Targets using four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework model for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be easily estimated. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates the systems parameters required to run the storage system model. Additionally, this design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the framework model and compare it to the DOE Technical Targets. These models will be explained and exercised with existing hydrogen storage materials.« less
Complete integrability of information processing by biochemical reactions

PubMed Central

Agliari, Elena; Barra, Adriano; Dello Schiavo, Lorenzo; Moro, Antonio

2016-01-01

Statistical mechanics provides an effective framework to investigate information processing in biochemical reactions. Within such framework far-reaching analogies are established among (anti-) cooperative collective behaviors in chemical kinetics, (anti-)ferromagnetic spin models in statistical mechanics and operational amplifiers/flip-flops in cybernetics. The underlying modeling – based on spin systems – has been proved to be accurate for a wide class of systems matching classical (e.g. Michaelis–Menten, Hill, Adair) scenarios in the infinite-size approximation. However, the current research in biochemical information processing has been focusing on systems involving a relatively small number of units, where this approximation is no longer valid. Here we show that the whole statistical mechanical description of reaction kinetics can be re-formulated via a mechanical analogy – based on completely integrable hydrodynamic-type systems of PDEs – which provides explicit finite-size solutions, matching recently investigated phenomena (e.g. noise-induced cooperativity, stochastic bi-stability, quorum sensing). The resulting picture, successfully tested against a broad spectrum of data, constitutes a neat rationale for a numerically effective and theoretically consistent description of collective behaviors in biochemical reactions. PMID:27812018
Complete integrability of information processing by biochemical reactions

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Dello Schiavo, Lorenzo; Moro, Antonio

2016-11-01

Statistical mechanics provides an effective framework to investigate information processing in biochemical reactions. Within such framework far-reaching analogies are established among (anti-) cooperative collective behaviors in chemical kinetics, (anti-)ferromagnetic spin models in statistical mechanics and operational amplifiers/flip-flops in cybernetics. The underlying modeling - based on spin systems - has been proved to be accurate for a wide class of systems matching classical (e.g. Michaelis-Menten, Hill, Adair) scenarios in the infinite-size approximation. However, the current research in biochemical information processing has been focusing on systems involving a relatively small number of units, where this approximation is no longer valid. Here we show that the whole statistical mechanical description of reaction kinetics can be re-formulated via a mechanical analogy - based on completely integrable hydrodynamic-type systems of PDEs - which provides explicit finite-size solutions, matching recently investigated phenomena (e.g. noise-induced cooperativity, stochastic bi-stability, quorum sensing). The resulting picture, successfully tested against a broad spectrum of data, constitutes a neat rationale for a numerically effective and theoretically consistent description of collective behaviors in biochemical reactions.
Complete integrability of information processing by biochemical reactions.

PubMed

Agliari, Elena; Barra, Adriano; Dello Schiavo, Lorenzo; Moro, Antonio

2016-11-04

Statistical mechanics provides an effective framework to investigate information processing in biochemical reactions. Within such framework far-reaching analogies are established among (anti-) cooperative collective behaviors in chemical kinetics, (anti-)ferromagnetic spin models in statistical mechanics and operational amplifiers/flip-flops in cybernetics. The underlying modeling - based on spin systems - has been proved to be accurate for a wide class of systems matching classical (e.g. Michaelis-Menten, Hill, Adair) scenarios in the infinite-size approximation. However, the current research in biochemical information processing has been focusing on systems involving a relatively small number of units, where this approximation is no longer valid. Here we show that the whole statistical mechanical description of reaction kinetics can be re-formulated via a mechanical analogy - based on completely integrable hydrodynamic-type systems of PDEs - which provides explicit finite-size solutions, matching recently investigated phenomena (e.g. noise-induced cooperativity, stochastic bi-stability, quorum sensing). The resulting picture, successfully tested against a broad spectrum of data, constitutes a neat rationale for a numerically effective and theoretically consistent description of collective behaviors in biochemical reactions.
A Computational Framework for Identifiability and Ill-Conditioning Analysis of Lithium-Ion Battery Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

López C, Diana C.; Wozny, Günter; Flores-Tlacuahuac, Antonio

2016-03-23

The lack of informative experimental data and the complexity of first-principles battery models make the recovery of kinetic, transport, and thermodynamic parameters complicated. We present a computational framework that combines sensitivity, singular value, and Monte Carlo analysis to explore how different sources of experimental data affect parameter structural ill conditioning and identifiability. Our study is conducted on a modified version of the Doyle-Fuller-Newman model. We demonstrate that the use of voltage discharge curves only enables the identification of a small parameter subset, regardless of the number of experiments considered. Furthermore, we show that the inclusion of a single electrolyte concentrationmore » measurement significantly aids identifiability and mitigates ill-conditioning.« less
Kinetics of Thermal Unimolecular Decomposition of Acetic Anhydride: An Integrated Deterministic and Stochastic Model.

PubMed

Mai, Tam V-T; Duong, Minh V; Nguyen, Hieu T; Lin, Kuang C; Huynh, Lam K

2017-04-27

An integrated deterministic and stochastic model within the master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) framework was first used to characterize temperature- and pressure-dependent behaviors of thermal decomposition of acetic anhydride in a wide range of conditions (i.e., 300-1500 K and 0.001-100 atm). Particularly, using potential energy surface and molecular properties obtained from high-level electronic structure calculations at CCSD(T)/CBS, macroscopic thermodynamic properties and rate coefficients of the title reaction were derived with corrections for hindered internal rotation and tunneling treatments. Being in excellent agreement with the scattered experimental data, the results from deterministic and stochastic frameworks confirmed and complemented each other to reveal that the main decomposition pathway proceeds via a 6-membered-ring transition state with the 0 K barrier of 35.2 kcal·mol -1 . This observation was further understood and confirmed by the sensitivity analysis on the time-resolved species profiles and the derived rate coefficients with respect to the ab initio barriers. Such an agreement suggests the integrated model can be confidently used for a wide range of conditions as a powerful postfacto and predictive tool in detailed chemical kinetic modeling and simulation for the title reaction and thus can be extended to complex chemical reactions.
Phase field approaches of bone remodeling based on TIP

NASA Astrophysics Data System (ADS)

Ganghoffer, Jean-François; Rahouadj, Rachid; Boisse, Julien; Forest, Samuel

2016-01-01

The process of bone remodeling includes a cycle of repair, renewal, and optimization. This adaptation process, in response to variations in external loads and chemical driving factors, involves three main types of bone cells: osteoclasts, which remove the old pre-existing bone; osteoblasts, which form the new bone in a second phase; osteocytes, which are sensing cells embedded into the bone matrix, trigger the aforementioned sequence of events. The remodeling process involves mineralization of the bone in the diffuse interface separating the marrow, which contains all specialized cells, from the newly formed bone. The main objective advocated in this contribution is the setting up of a modeling and simulation framework relying on the phase field method to capture the evolution of the diffuse interface between the new bone and the marrow at the scale of individual trabeculae. The phase field describes the degree of mineralization of this diffuse interface; it varies continuously between the lower value (no mineral) and unity (fully mineralized phase, e.g. new bone), allowing the consideration of a diffuse moving interface. The modeling framework is the theory of continuous media, for which field equations for the mechanical, chemical, and interfacial phenomena are written, based on the thermodynamics of irreversible processes. Additional models for the cellular activity are formulated to describe the coupling of the cell activity responsible for bone production/resorption to the kinetics of the internal variables. Kinetic equations for the internal variables are obtained from a pseudo-potential of dissipation. The combination of the balance equations for the microforce associated to the phase field and the kinetic equations lead to the Ginzburg-Landau equation satisfied by the phase field with a source term accounting for the dissipative microforce. Simulations illustrating the proposed framework are performed in a one-dimensional situation showing the evolution of the diffuse interface separating new bone from marrow.
A Global Modeling Framework for Plasma Kinetics: Development and Applications

NASA Astrophysics Data System (ADS)

Parsey, Guy Morland

The modern study of plasmas, and applications thereof, has developed synchronously with com- puter capabilities since the mid-1950s. Complexities inherent to these charged-particle, many- body, systems have resulted in the development of multiple simulation methods (particle-in-cell, fluid, global modeling, etc.) in order to both explain observed phenomena and predict outcomes of plasma applications. Recognizing that different algorithms are chosen to best address specific topics of interest, this thesis centers around the development of an open-source global model frame- work for the focused study of non-equilibrium plasma kinetics. After verification and validation of the framework, it was used to study two physical phenomena: plasma-assisted combustion and the recently proposed optically-pumped rare gas metastable laser. Global models permeate chemistry and plasma science, relying on spatial averaging to focus attention on the dynamics of reaction networks. Defined by a set of species continuity and energy conservation equations, the required data and constructed systems are conceptually similar across most applications, providing a light platform for exploratory and result-search parameter scan- ning. Unfortunately, it is common practice for custom code to be developed for each application-- an enormous duplication of effort which negatively affects the quality of the software produced. Presented herein, the Python-based Kinetic Global Modeling framework (KGMf) was designed to support all modeling phases: collection and analysis of reaction data, construction of an exportable system of model ODEs, and a platform for interactive evaluation and post-processing analysis. A symbolic ODE system is constructed for interactive manipulation and generation of a Jacobian, both of which are compiled as operation-optimized C-code. Plasma-assisted combustion and ignition (PAC/PAI) embody the modernization of burning fuel by opening up new avenues of control and optimization. With applications ranging from engineefficiency and pollution control to stabilized operation of scramjet technology in hypersonic flows, developing an understanding of the underlying plasma chemistry is of the utmost importance. While the use of equilibrium (thermal) plasmas in the combustion process extends back to the ad- vent of the spark-ignition engine, works from the last few decades have demonstrated fundamental differences between PAC and classical combustion theory. The KGMf is applied to nanosecond- discharge systems in order to analyze the effects of electron energy distribution assumptions on reaction kinetics and highlight the usefulness of 0D modeling in systems defined by coupled and complex physics. With fundamentally different principles involved, the concept of optically-pumped rare gas metastable lasing (RGL) presents a novel opportunity for scalable high-powered lasers by taking advantage of similarities in the electronic structure of elements while traversing the periodic ta- ble. Building from the proven concept of diode-pumped alkali vapor lasers (DPAL), RGL systems demonstrate remarkably similar spectral characteristics without problems associated with heated caustic vapors. First introduced in 2012, numerical studies on the latent kinetics remain immature. This work couples an analytic model developed for DPAL with KGMf plasma chemistry to bet- ter understand the interaction of a non-equilibrium plasma with the induced laser processes and determine if optical pumping could be avoided through careful discharge selection.
Evolving cell models for systems and synthetic biology.

PubMed

Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

2010-03-01

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.
Thermodynamics of axial substitution and kinetics of reactions with amino acids for the paddlewheel complex tetrakis(acetato)chloridodiruthenium(II,III).

PubMed

Santos, Rodrigo L S R; van Eldik, Rudi; de Oliveira Silva, Denise

2012-06-18

The known paddlewheel, tetrakis(acetato)chloridodiruthenium(II,III), offers a versatile synthetic route to a novel class of antitumor diruthenium(II,III) metallo drugs, where the equatorial ligands are nonsteroidal anti-inflammatory carboxylates. This complex was studied here as a soluble starting prototype model for antitumor analogues to elucidate the reactivity of the [Ru(2)(CH(3)COO)(4)](+) framework. Thermodynamic studies on equilibration reactions for axial substitution of water by chloride and kinetic studies on reactions of the diaqua complexes with the amino acids glycine, cysteine, histidine, and tryptophan were performed. The standard thermodynamic reaction parameters ΔH°, ΔS°, and ΔV° were determined and showed that both of the sequential axial substitution reactions are enthalpy driven. Kinetic rate laws and rate constants were determined for the axial substitution reactions of coordinated water by the amino acids that gave the corresponding aqua(amino acid)-Ru(2) substituted species. The results revealed that the [Ru(2)(CH(3)COO)(4)](+) paddlewheel framework remained stable during the axial ligand substitution reactions and was also mostly preserved in the presence of the amino acids.
Particle-Size-Grouping Model of Precipitation Kinetics in Microalloyed Steels

NASA Astrophysics Data System (ADS)

Xu, Kun; Thomas, Brian G.

2012-03-01

The formation, growth, and size distribution of precipitates greatly affects the microstructure and properties of microalloyed steels. Computational particle-size-grouping (PSG) kinetic models based on population balances are developed to simulate precipitate particle growth resulting from collision and diffusion mechanisms. First, the generalized PSG method for collision is explained clearly and verified. Then, a new PSG method is proposed to model diffusion-controlled precipitate nucleation, growth, and coarsening with complete mass conservation and no fitting parameters. Compared with the original population-balance models, this PSG method saves significant computation and preserves enough accuracy to model a realistic range of particle sizes. Finally, the new PSG method is combined with an equilibrium phase fraction model for plain carbon steels and is applied to simulate the precipitated fraction of aluminum nitride and the size distribution of niobium carbide during isothermal aging processes. Good matches are found with experimental measurements, suggesting that the new PSG method offers a promising framework for the future development of realistic models of precipitation.

Predicting perturbation patterns from the topology of biological networks.

PubMed

Santolini, Marc; Barabási, Albert-László

2018-06-20

High-throughput technologies, offering an unprecedented wealth of quantitative data underlying the makeup of living systems, are changing biology. Notably, the systematic mapping of the relationships between biochemical entities has fueled the rapid development of network biology, offering a suitable framework to describe disease phenotypes and predict potential drug targets. However, our ability to develop accurate dynamical models remains limited, due in part to the limited knowledge of the kinetic parameters underlying these interactions. Here, we explore the degree to which we can make reasonably accurate predictions in the absence of the kinetic parameters. We find that simple dynamically agnostic models are sufficient to recover the strength and sign of the biochemical perturbation patterns observed in 87 biological models for which the underlying kinetics are known. Surprisingly, a simple distance-based model achieves 65% accuracy. We show that this predictive power is robust to topological and kinetic parameter perturbations, and we identify key network properties that can increase up to 80% the recovery rate of the true perturbation patterns. We validate our approach using experimental data on the chemotactic pathway in bacteria, finding that a network model of perturbation spreading predicts with ∼80% accuracy the directionality of gene expression and phenotype changes in knock-out and overproduction experiments. These findings show that the steady advances in mapping out the topology of biochemical interaction networks opens avenues for accurate perturbation spread modeling, with direct implications for medicine and drug development.
Scaling of Guide-Field Magnetic Reconnection using Anisotropic Fluid Closure

NASA Astrophysics Data System (ADS)

Ohia, O.; Egedal, J.; Lukin, V. S.; Daughton, W.; Le, A.

2012-10-01

Collisionless magnetic reconnection, a process linked to solar flares, coronal mass ejections, and magnetic substorms, has been widely studied through fluid models and fully kinetic simulations. While fluid models often reproduce the fast reconnection rate of fully kinetic simulations, significant differences are observed in the structure of the reconnection regions [1]. However, guide-field fluid simulations implementing new equations of state that accurately account for the anisotropic electron pressure [2] reproduce the detailed reconnection region observed in kinetic simulations [3]. Implementing this two-fluid simulation using the HiFi framework [4], we study the force balance of the electron layers in guide-field reconnection and derive scaling laws for their characteristics.[1ex] [1] Daughton W et al., Phys. Plasmas 13, 072101 (2006).[0ex] [2] Le A et al., Phys. Rev. Lett. 102, 085001 (2009). [0ex] [3] Ohia O, et al., Phys. Rev. Lett. In Press (2012).[0ex] [4] Lukin VS, Linton MG, Nonlinear Proc. Geoph. 18, 871 (2011)
A stochastic asymptotic-preserving scheme for a kinetic-fluid model for disperse two-phase flows with uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Shi, E-mail: sjin@wisc.edu; Institute of Natural Sciences, School of Mathematical Science, MOELSEC and SHL-MAC, Shanghai Jiao Tong University, Shanghai 200240; Shu, Ruiwen, E-mail: rshu2@math.wisc.edu

In this paper we consider a kinetic-fluid model for disperse two-phase flows with uncertainty. We propose a stochastic asymptotic-preserving (s-AP) scheme in the generalized polynomial chaos stochastic Galerkin (gPC-sG) framework, which allows the efficient computation of the problem in both kinetic and hydrodynamic regimes. The s-AP property is proved by deriving the equilibrium of the gPC version of the Fokker–Planck operator. The coefficient matrices that arise in a Helmholtz equation and a Poisson equation, essential ingredients of the algorithms, are proved to be positive definite under reasonable and mild assumptions. The computation of the gPC version of a translation operatormore » that arises in the inversion of the Fokker–Planck operator is accelerated by a spectrally accurate splitting method. Numerical examples illustrate the s-AP property and the efficiency of the gPC-sG method in various asymptotic regimes.« less
Relativistic differential-difference momentum operators and noncommutative differential calculus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mir-Kasimov, R. M., E-mail: mirkr@theor.jinr.ru

2013-09-15

The relativistic kinetic momentum operators are introduced in the framework of the Quantum Mechanics (QM) in the Relativistic Configuration Space (RCS). These operators correspond to the half of the non-Euclidean distance in the Lobachevsky momentum space. In terms of kinetic momentum operators the relativistic kinetic energy is separated as the independent term of the total Hamiltonian. This relativistic kinetic energy term is not distinguishing in form from its nonrelativistic counterpart. The role of the plane wave (wave function of the motion with definite value of momentum and energy) plays the generating function for the matrix elements of the unitary irrepsmore » of Lorentz group (generalized Jacobi polynomials). The kinetic momentum operators are the interior derivatives in the framework of the noncommutative differential calculus over the commutative algebra generated by the coordinate functions over the RCS.« less
Probing the hydrogen equilibrium and kinetics in zeolite imidazolate frameworks via molecular dynamics and quasi-elastic neutron scattering experiments.

PubMed

Pantatosaki, Evangelia; Jobic, Hervé; Kolokolov, Daniil I; Karmakar, Shilpi; Biniwale, Rajesh; Papadopoulos, George K

2013-01-21

The problem of simulating processes involving equilibria and dynamics of guest sorbates within zeolitic imidazolate frameworks (ZIF) by means of molecular dynamics (MD) computer experiments is of growing importance because of the promising role of ZIFs as molecular "traps" for clean energy applications. A key issue for validating such an atomistic modeling attempt is the possibility of comparing the MD results, with real experiments being able to capture analogous space and time scales to the ones pertained to the computer experiments. In the present study, this prerequisite is fulfilled through the quasi-elastic neutron scattering technique (QENS) for measuring self-diffusivity, by elaborating the incoherent scattering signal of hydrogen nuclei. QENS and MD experiments were performed in parallel to probe the hydrogen motion, for the first time in ZIF members. The predicted and measured dynamics behaviors show considerable concentration variation of the hydrogen self-diffusion coefficient in the two topologically different ZIF pore networks of this study, the ZIF-3 and ZIF-8. Modeling options such as the flexibility of the entire matrix versus a rigid framework version, the mobility of the imidazolate ligand, and the inclusion of quantum mechanical effects in the potential functions were examined in detail for the sorption thermodynamics and kinetics of hydrogen and also of deuterium, by employing MD combined with Widom averaging towards studying phase equilibria. The latter methodology ensures a rigorous and efficient way for post-processing the dynamics trajectory, thereby avoiding stochastic moves via Monte Carlo simulation, over the large number of configurational degrees of freedom a nonrigid framework encompasses.
Implementation of the US EPA (United States Environmental Protection Agency) Regional Oxidant Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novak, J.H.

1984-05-01

Model design, implementation and quality assurance procedures can have a significant impact on the effectiveness of long term utility of any modeling approach. The Regional Oxidant Modeling System (ROMS) is exceptionally complex because it treats all chemical and physical processes thought to affect ozone concentration on a regional scale. Thus, to effectively illustrate useful design and implementation techniques, this paper describes the general modeling framework which forms the basis of the ROMS. This framework is flexible enough to allow straightforward update or replacement of the chemical kinetics mechanism and/or any theoretical formulations of the physical processes. Use of the Jacksonmore » Structured Programming (JSP) method to implement this modeling framework has not only increased programmer productivity and quality of the resulting programs, but also has provided standardized program design, dynamic documentation, and easily maintainable and transportable code. A summary of the JSP method is presented to encourage modelers to pursue this technique in their own model development efforts. In addition, since data preparation is such an integral part of a successful modeling system, the ROMS processor network is described with emphasis on the internal quality control techniques.« less
Rapid freezing of water under dynamic compression

NASA Astrophysics Data System (ADS)

Myint, Philip C.; Belof, Jonathan L.

2018-06-01

Understanding the behavior of materials at extreme pressures is a central issue in fields like aerodynamics, astronomy, and geology, as well as for advancing technological grand challenges such as inertial confinement fusion. Dynamic compression experiments to probe high-pressure states often encounter rapid phase transitions that may cause the materials to behave in unexpected ways, and understanding the kinetics of these phase transitions remains an area of great interest. In this review, we examine experimental and theoretical/computational efforts to study the freezing kinetics of water to a high-pressure solid phase known as ice VII. We first present a detailed analysis of dynamic compression experiments in which water has been observed to freeze on sub-microsecond time scales to ice VII. This is followed by a discussion of the limitations of currently available molecular and continuum simulation methods in modeling these experiments. We then describe how our phase transition kinetics models, which are based on classical nucleation theory, provide a more physics-based framework that overcomes some of these limitations. Finally, we give suggestions on future experimental and modeling work on the liquid–ice VII transition, including an outline of the development of a predictive multiscale model in which molecular and continuum simulations are intimately coupled.
Rapid freezing of water under dynamic compression.

PubMed

Myint, Philip C; Belof, Jonathan L

2018-06-13

Understanding the behavior of materials at extreme pressures is a central issue in fields like aerodynamics, astronomy, and geology, as well as for advancing technological grand challenges such as inertial confinement fusion. Dynamic compression experiments to probe high-pressure states often encounter rapid phase transitions that may cause the materials to behave in unexpected ways, and understanding the kinetics of these phase transitions remains an area of great interest. In this review, we examine experimental and theoretical/computational efforts to study the freezing kinetics of water to a high-pressure solid phase known as ice VII. We first present a detailed analysis of dynamic compression experiments in which water has been observed to freeze on sub-microsecond time scales to ice VII. This is followed by a discussion of the limitations of currently available molecular and continuum simulation methods in modeling these experiments. We then describe how our phase transition kinetics models, which are based on classical nucleation theory, provide a more physics-based framework that overcomes some of these limitations. Finally, we give suggestions on future experimental and modeling work on the liquid-ice VII transition, including an outline of the development of a predictive multiscale model in which molecular and continuum simulations are intimately coupled.
Predictive Framework and Experimental Tests of the Kinetic Isotope Effect at Redox-Active Interfaces

NASA Astrophysics Data System (ADS)

Kavner, A.; John, S.; Black, J. R.

2013-12-01

Electrochemical reactions provide a compelling framework to study kinetic isotope effects because redox-related processes are important for a wide variety of geological and environmental processes. In the laboratory, electrochemical reaction rates can be electronically controlled and measured in the laboratory using a potentiostat. This enables variation of redox reactions rates independent of changes in chemistry and, and the resulting isotope compositions of reactants and products can be separated and analyzed. In the past years, a series of experimental studies have demonstrated a large, light, and tunable kinetic isotope effect during electrodeposition of metal Fe, Zn, Li, Cu, and Mo from a variety of solutions (e.g. Black et al., 2009, 2010, 2011). A theoretical framework based on Marcus kinetic theory predicts a voltage-dependent kinetic isotope effect (Kavner et al., 2005, 2008), however while this framework was able to predict the tunable nature of the effect, it was not able to simultaneously predict absolute reaction rates and relative isotope rates. Here we present a more complete development of a statistical mechanical framework for simple interfacial redox reactions, which includes isotopic behavior. The framework is able to predict a kinetic isotope effect as a function of temperature and reaction rate, starting with three input parameters: a single reorganization energy which describes the overall kinetics of the electron transfer reaction, and the equilibrium reduced partition function ratios for heavy and light isotopes in the product and reactant phases. We show the framework, elucidate some of the predictions, and show direct comparisons against isotope fractionation data obtained during laboratory and natural environment redox processes. A. Kavner, A. Shahar, F. Bonet, J. Simon and E. Young (2005) Geochim. Cosmochim. Acta, 69(12), 2971-2979. A. Kavner, S. G. John, S. Sass, and E. A. Boyle (2008), Geochim. Cosmochim. Acta, vol 72, pp. 1731-1741. J. R. Black, Umeda, G., Dunn, B., McDonough, W. F. and A. Kavner. (2009), J. Amer. Chem. Soc., vol. 131, No.29 2009 pp. 9904-9905 DOI: 10.1021/ja903926x. J. R. Black, S. John, E.D. Young, and A. Kavner, (2010), Geochim. Cosmochim. Acta, vol 74 (18) pp. 5187-5201. J. R. Black, J. Crawford, S. John, and A. Kavner, (2011) Redox-driven stable isotope fractionation, in Aquatic Redox Chemistry ACS Symposium Series, Vol. 1071. Tratnyek, P.G., T. J. Grundl, and S. B. Haderlein, eds. Chapter 16, pp 345-359
BEATBOX v1.0: Background Error Analysis Testbed with Box Models

NASA Astrophysics Data System (ADS)

Knote, Christoph; Barré, Jérôme; Eckl, Max

2018-02-01

The Background Error Analysis Testbed (BEATBOX) is a new data assimilation framework for box models. Based on the BOX Model eXtension (BOXMOX) to the Kinetic Pre-Processor (KPP), this framework allows users to conduct performance evaluations of data assimilation experiments, sensitivity analyses, and detailed chemical scheme diagnostics from an observation simulation system experiment (OSSE) point of view. The BEATBOX framework incorporates an observation simulator and a data assimilation system with the possibility of choosing ensemble, adjoint, or combined sensitivities. A user-friendly, Python-based interface allows for the tuning of many parameters for atmospheric chemistry and data assimilation research as well as for educational purposes, for example observation error, model covariances, ensemble size, perturbation distribution in the initial conditions, and so on. In this work, the testbed is described and two case studies are presented to illustrate the design of a typical OSSE experiment, data assimilation experiments, a sensitivity analysis, and a method for diagnosing model errors. BEATBOX is released as an open source tool for the atmospheric chemistry and data assimilation communities.
Dissolution of covalent adaptable network polymers in organic solvent

NASA Astrophysics Data System (ADS)

Yu, Kai; Yang, Hua; Dao, Binh H.; Shi, Qian; Yakacki, Christopher M.

2017-12-01

It was recently reported that thermosetting polymers can be fully dissolved in a proper organic solvent utilizing a bond-exchange reaction (BER), where small molecules diffuse into the polymer, break the long polymer chains into short segments, and eventually dissolve the network when sufficient solvent is provided. The solvent-assisted dissolution approach was applied to fully recycle thermosets and their fiber composites. This paper presents the first multi-scale modeling framework to predict the dissolution kinetics and mechanics of thermosets in organic solvent. The model connects the micro-scale network dynamics with macro-scale material properties: in the micro-scale, a model is developed based on the kinetics of BERs to describe the cleavage rate of polymer chains and evolution of chain segment length during the dissolution. The micro-scale model is then fed into a continuum-level model with considerations of the transportation of solvent molecules and chain segments in the system. The model shows good prediction on conversion rate of functional groups, degradation of network mechanical properties, and dissolution rate of thermosets during the dissolution. It identifies the underlying kinetic factors governing the dissolution process, and reveals the influence of different material and processing variables on the dissolution process, such as time, temperature, catalyst concentration, and chain length between cross-links.
Equilibrium Field Theoretic and Dynamic Mean Field Simulations of Inhomogeneous Polymeric Materials

NASA Astrophysics Data System (ADS)

Chao, Huikuan

Inhomogeneous polymeric materials is a large family of promising materials including but limited to block copolymers (BCPs), polymer nanocomposites (PNCs) and microscopically confined polymer films. The promising application of the materials originates from the materials' unique microstructures, which offer enhanced mechanical, thermal, optical and electrical properties to the materials. Due to the complex interactions and the large parameter space, behaviors of the microstructures formed by grafted nanoparticles and nanorods in PNCs are difficult to understand. Separately, because of relatively weak interactions, the microstructures are typically achieved through rapid processing that are kinetically controlled and beyond equilibrium. However, efficient simulation framework to study nonequilbrium dynamics of the materials is currently not available. To attack the first difficulty, I extended an efficient simulation framework, polymer nanocomposite field theory (PNC-FT), to incorporate grafted nanoparticles and nanorods. This extended framework is demonstrated against existing experimental studies and implemented to study how the nanoparticle design affects the nanoparticle distribution in binary homopolymer blends. The grafted nanoparticle model is also used as a platform to adopt an advanced optimization method to inversely design nanoparticles which are able to self-assemble into targeted two dimensional lattices. The nanorod model under PNC-FT framework is used to investigate the design of nanorod and block copolymer thin films to control the nanorod distribution. To attack the second difficulty, I established an efficient framework (SCMF-LD) based on a recently proposed dynamic mean field theory and used SCMF-LD to study how to kinetically control the nanoparticle distribution at the end of solvent annealing block copolymer thin films. The framework is then extended to incorporate hydrodynamics (SCMF-DPD) and the extended framework is implemented to study morphology development in phase inversion processing polymer thin films, where hydrodynamic effects play an important role. By exploring both equilibrium and nonequilibrium properties in a spectrum of inhomogeneous polymeric material systems, I successfully extended PNC-FT and established SCMF-LD and SCMF-DPD frameworks, which are expected to be efficient and powerful tools in studies of inhomogeneous polymeric material design and processing.
Maximum likelihood estimation of protein kinetic parameters under weak assumptions from unfolding force spectroscopy experiments

NASA Astrophysics Data System (ADS)

Aioanei, Daniel; Samorì, Bruno; Brucale, Marco

2009-12-01

Single molecule force spectroscopy (SMFS) is extensively used to characterize the mechanical unfolding behavior of individual protein domains under applied force by pulling chimeric polyproteins consisting of identical tandem repeats. Constant velocity unfolding SMFS data can be employed to reconstruct the protein unfolding energy landscape and kinetics. The methods applied so far require the specification of a single stretching force increase function, either theoretically derived or experimentally inferred, which must then be assumed to accurately describe the entirety of the experimental data. The very existence of a suitable optimal force model, even in the context of a single experimental data set, is still questioned. Herein, we propose a maximum likelihood (ML) framework for the estimation of protein kinetic parameters which can accommodate all the established theoretical force increase models. Our framework does not presuppose the existence of a single force characteristic function. Rather, it can be used with a heterogeneous set of functions, each describing the protein behavior in the stretching time range leading to one rupture event. We propose a simple way of constructing such a set of functions via piecewise linear approximation of the SMFS force vs time data and we prove the suitability of the approach both with synthetic data and experimentally. Additionally, when the spontaneous unfolding rate is the only unknown parameter, we find a correction factor that eliminates the bias of the ML estimator while also reducing its variance. Finally, we investigate which of several time-constrained experiment designs leads to better estimators.
A dislocation-based crystal plasticity framework for dynamic ductile failure of single crystals

NASA Astrophysics Data System (ADS)

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

2017-11-01

A framework for dislocation-based viscoplasticity and dynamic ductile failure has been developed to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. An averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Additionally, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in (Wilkerson and Ramesh, 2014), which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.
Kinetic theory of Jeans instability of a dusty plasma.

PubMed

Pandey, B P; Lakhina, G S; Krishan, V

1999-12-01

A kinetic theory of the Jeans instability of a dusty plasma has been developed in the present work. The effect of grain charge fluctuations due to the attachment of electrons and ions to the grain surface has been considered in the framework of Krook's collisional model. We demonstrate that the grain charge fluctuations alter the growth rate of the gravitational collapse of the dusty plasma. The Jeans length has been derived under limiting cases, and its dependence on the attachment frequency is shown. In the absence of gravity, we see that the damping rate of the dust acoustic mode is proportional to the electron-dust collision frequency.
Multielectron, multisubstrate molecular catalysis of electrochemical reactions: Formal kinetic analysis in the total catalysis regime.

PubMed

Costentin, Cyrille; Nocera, Daniel G; Brodsky, Casey N

2017-10-24

Cyclic voltammetry responses are derived for two-electron, two-step homogeneous electrocatalytic reactions in the total catalysis regime. The models developed provide a framework for extracting kinetic information from cyclic voltammograms (CVs) obtained in conditions under which the substrate or cosubstrate is consumed in a multielectron redox process, as is particularly prevalent for very active catalysts that promote energy conversion reactions. Such determination of rate constants in the total catalysis regime is a prerequisite for the rational benchmarking of molecular electrocatalysts that promote multielectron conversions of small-molecule reactants. The present analysis is illustrated with experimental systems encompassing various limiting behaviors.
Z' portal to Chern-Simons Dark Matter

NASA Astrophysics Data System (ADS)

Arcadi, Giorgio; Ghosh, Pradipta; Mambrini, Yann; Pierre, Mathias; Queiroz, Farinaldo S.

2017-11-01

We study the phenomenological credibility of a vectorial dark matter, coupled to a Z' portal through Chern-Simons interaction. We scrutinize two possibilities of connecting a Z' with the Standard Model: (1) through kinetic mixing and (2) from a second Chern-Simons interaction. Both scenarios are characterized by suppressed nuclear recoil scatterings, rendering direct detection searches not promising. Indirect detection experiments, on the other hand, furnish complementary limits for TeV scale masses, specially with the CTA. Searches for mono-jet and dileptons signals at the LHC are important to partially probe the kinetic mixing setup. Finally we propose an UV completion of the Chern-Simons Dark Matter framework.
An analytical study on excitation of nuclear-coupled thermal-hydraulic instability due to seismically induced resonance in BWR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirano, Masashi

1997-07-01

This paper describes the results of a scoping study on seismically induced resonance of nuclear-coupled thermal-hydraulic instability in BWRs, which was conducted by using TRAC-BF1 within a framework of a point kinetics model. As a result of the analysis, it is shown that a reactivity insertion could occur accompanied by in-surge of coolant into the core resulted from the excitation of the nuclear-coupled instability by the external acceleration. In order to analyze this phenomenon more in detail, it is necessary to couple a thermal-hydraulic code with a three-dimensional nuclear kinetics code.
A third-order gas-kinetic CPR method for the Euler and Navier-Stokes equations on triangular meshes

NASA Astrophysics Data System (ADS)

Zhang, Chao; Li, Qibing; Fu, Song; Wang, Z. J.

2018-06-01

A third-order accurate gas-kinetic scheme based on the correction procedure via reconstruction (CPR) framework is developed for the Euler and Navier-Stokes equations on triangular meshes. The scheme combines the accuracy and efficiency of the CPR formulation with the multidimensional characteristics and robustness of the gas-kinetic flux solver. Comparing with high-order finite volume gas-kinetic methods, the current scheme is more compact and efficient by avoiding wide stencils on unstructured meshes. Unlike the traditional CPR method where the inviscid and viscous terms are treated differently, the inviscid and viscous fluxes in the current scheme are coupled and computed uniformly through the kinetic evolution model. In addition, the present scheme adopts a fully coupled spatial and temporal gas distribution function for the flux evaluation, achieving high-order accuracy in both space and time within a single step. Numerical tests with a wide range of flow problems, from nearly incompressible to supersonic flows with strong shocks, for both inviscid and viscous problems, demonstrate the high accuracy and efficiency of the present scheme.
Teaching Foundational Topics and Scientific Skills in Biochemistry within the Conceptual Framework of HIV Protease

ERIC Educational Resources Information Center

Johnson, R. Jeremy

2014-01-01

HIV protease has served as a model protein for understanding protein structure, enzyme kinetics, structure-based drug design, and protein evolution. Inhibitors of HIV protease are also an essential part of effective HIV/AIDS treatment and have provided great societal benefits. The broad applications for HIV protease and its inhibitors make it a…

Activated desorption at heterogeneous interfaces and long-time kinetics of hydrocarbon recovery from nanoporous media.

PubMed

Lee, Thomas; Bocquet, Lydéric; Coasne, Benoit

2016-06-21

Hydrocarbon recovery from unconventional reservoirs (shale gas) is debated due to its environmental impact and uncertainties on its predictability. But a lack of scientific knowledge impedes the proposal of reliable alternatives. The requirement of hydrofracking, fast recovery decay and ultra-low permeability-inherent to their nanoporosity-are specificities of these reservoirs, which challenge existing frameworks. Here we use molecular simulation and statistical models to show that recovery is hampered by interfacial effects at the wet kerogen surface. Recovery is shown to be thermally activated with an energy barrier modelled from the interface wetting properties. We build a statistical model of the recovery kinetics with a two-regime decline that is consistent with published data: a short time decay, consistent with Darcy description, followed by a fast algebraic decay resulting from increasingly unreachable energy barriers. Replacing water by CO2 or propane eliminates the barriers, therefore raising hopes for clean/efficient recovery.
Steepest entropy ascent model for far-nonequilibrium thermodynamics: Unified implementation of the maximum entropy production principle

NASA Astrophysics Data System (ADS)

Beretta, Gian Paolo

2014-10-01

By suitable reformulations, we cast the mathematical frameworks of several well-known different approaches to the description of nonequilibrium dynamics into a unified formulation valid in all these contexts, which extends to such frameworks the concept of steepest entropy ascent (SEA) dynamics introduced by the present author in previous works on quantum thermodynamics. Actually, the present formulation constitutes a generalization also for the quantum thermodynamics framework. The analysis emphasizes that in the SEA modeling principle a key role is played by the geometrical metric with respect to which to measure the length of a trajectory in state space. In the near-thermodynamic-equilibrium limit, the metric tensor is directly related to the Onsager's generalized resistivity tensor. Therefore, through the identification of a suitable metric field which generalizes the Onsager generalized resistance to the arbitrarily far-nonequilibrium domain, most of the existing theories of nonequilibrium thermodynamics can be cast in such a way that the state exhibits the spontaneous tendency to evolve in state space along the path of SEA compatible with the conservation constraints and the boundary conditions. The resulting unified family of SEA dynamical models is intrinsically and strongly consistent with the second law of thermodynamics. The non-negativity of the entropy production is a general and readily proved feature of SEA dynamics. In several of the different approaches to nonequilibrium description we consider here, the SEA concept has not been investigated before. We believe it defines the precise meaning and the domain of general validity of the so-called maximum entropy production principle. Therefore, it is hoped that the present unifying approach may prove useful in providing a fresh basis for effective, thermodynamically consistent, numerical models and theoretical treatments of irreversible conservative relaxation towards equilibrium from far nonequilibrium states. The mathematical frameworks we consider are the following: (A) statistical or information-theoretic models of relaxation; (B) small-scale and rarefied gas dynamics (i.e., kinetic models for the Boltzmann equation); (C) rational extended thermodynamics, macroscopic nonequilibrium thermodynamics, and chemical kinetics; (D) mesoscopic nonequilibrium thermodynamics, continuum mechanics with fluctuations; and (E) quantum statistical mechanics, quantum thermodynamics, mesoscopic nonequilibrium quantum thermodynamics, and intrinsic quantum thermodynamics.
Derivation of the Boltzmann Equation for Financial Brownian Motion: Direct Observation of the Collective Motion of High-Frequency Traders.

PubMed

Kanazawa, Kiyoshi; Sueshige, Takumi; Takayasu, Hideki; Takayasu, Misako

2018-03-30

A microscopic model is established for financial Brownian motion from the direct observation of the dynamics of high-frequency traders (HFTs) in a foreign exchange market. Furthermore, a theoretical framework parallel to molecular kinetic theory is developed for the systematic description of the financial market from microscopic dynamics of HFTs. We report first on a microscopic empirical law of traders' trend-following behavior by tracking the trajectories of all individuals, which quantifies the collective motion of HFTs but has not been captured in conventional order-book models. We next introduce the corresponding microscopic model of HFTs and present its theoretical solution paralleling molecular kinetic theory: Boltzmann-like and Langevin-like equations are derived from the microscopic dynamics via the Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy. Our model is the first microscopic model that has been directly validated through data analysis of the microscopic dynamics, exhibiting quantitative agreements with mesoscopic and macroscopic empirical results.
Derivation of the Boltzmann Equation for Financial Brownian Motion: Direct Observation of the Collective Motion of High-Frequency Traders

NASA Astrophysics Data System (ADS)

Kanazawa, Kiyoshi; Sueshige, Takumi; Takayasu, Hideki; Takayasu, Misako

2018-03-01

A microscopic model is established for financial Brownian motion from the direct observation of the dynamics of high-frequency traders (HFTs) in a foreign exchange market. Furthermore, a theoretical framework parallel to molecular kinetic theory is developed for the systematic description of the financial market from microscopic dynamics of HFTs. We report first on a microscopic empirical law of traders' trend-following behavior by tracking the trajectories of all individuals, which quantifies the collective motion of HFTs but has not been captured in conventional order-book models. We next introduce the corresponding microscopic model of HFTs and present its theoretical solution paralleling molecular kinetic theory: Boltzmann-like and Langevin-like equations are derived from the microscopic dynamics via the Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy. Our model is the first microscopic model that has been directly validated through data analysis of the microscopic dynamics, exhibiting quantitative agreements with mesoscopic and macroscopic empirical results.
Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE PAGES

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.; ...

2018-04-07

The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less
Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.

The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less
A unified theory for ice vapor growth suitable for cloud models: Testing and implications for cold cloud evolution

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

A new microphysical model for the vapor growth and aspect ratio evolution of atmospheric ice crystals is presented. The method is based on the adaptive habit model of Chen and Lamb (1994), but is modified to include surface kinetic processes for crystal growth. Inclusion of surface kinetic effects is accomplished with a new theory that accounts for axis dependent growth. Deposition coefficients (growth efficiencies) are predicted for two axis directions based on laboratory-determined parameters for growth initiation (critical supersaturations) on each face. In essence, the new theory extends the adaptive habit approach of Chen and Lamb (1994) to ice saturation states below that of liquid saturation, where Chen and Lamb (1994) is likely most valid. The new model is used to simulate changes in crystal primary habit as a function of temperature and ice supersaturation. Predictions are compared with a detailed hexagonal growth model both in a single particle framework and in a Lagrangian parcel model to indicate the accuracy of the new method. Moreover, predictions of the ratio of the axis deposition coefficients match laboratory-generated data. A parameterization for predicting deposition coefficients is developed for the bulk microphysics frame work in Regional Atmospheric Modeling System (RAMS). Initial eddy-resolving model simulation is conducted to study the effect of surface kinetics on microphysical and dynamical processes in cold cloud development.
Selective gas capture via kinetic trapping

DOE PAGES

Kundu, Joyjit; Pascal, Tod; Prendergast, David; ...

2016-07-13

Conventional approaches to the capture of CO 2 by metal-organic frameworks focus on equilibrium conditions, and frameworks that contain little CO 2 in equilibrium are often rejected as carbon-capture materials. Here we use a statistical mechanical model, parameterized by quantum mechanical data, to suggest that metal-organic frameworks can be used to separate CO 2 from a typical flue gas mixture when used under nonequilibrium conditions. The origin of this selectivity is an emergent gas-separation mechanism that results from the acquisition by different gas types of different mobilities within a crowded framework. The resulting distribution of gas types within the frameworkmore » is in general spatially and dynamically heterogeneous. Our results suggest that relaxing the requirement of equilibrium can substantially increase the parameter space of conditions and materials for which selective gas capture can be effected.« less
Detection of kinetic change points in piece-wise linear single molecule motion

NASA Astrophysics Data System (ADS)

Hill, Flynn R.; van Oijen, Antoine M.; Duderstadt, Karl E.

2018-03-01

Single-molecule approaches present a powerful way to obtain detailed kinetic information at the molecular level. However, the identification of small rate changes is often hindered by the considerable noise present in such single-molecule kinetic data. We present a general method to detect such kinetic change points in trajectories of motion of processive single molecules having Gaussian noise, with a minimum number of parameters and without the need of an assumed kinetic model beyond piece-wise linearity of motion. Kinetic change points are detected using a likelihood ratio test in which the probability of no change is compared to the probability of a change occurring, given the experimental noise. A predetermined confidence interval minimizes the occurrence of false detections. Applying the method recursively to all sub-regions of a single molecule trajectory ensures that all kinetic change points are located. The algorithm presented allows rigorous and quantitative determination of kinetic change points in noisy single molecule observations without the need for filtering or binning, which reduce temporal resolution and obscure dynamics. The statistical framework for the approach and implementation details are discussed. The detection power of the algorithm is assessed using simulations with both single kinetic changes and multiple kinetic changes that typically arise in observations of single-molecule DNA-replication reactions. Implementations of the algorithm are provided in ImageJ plugin format written in Java and in the Julia language for numeric computing, with accompanying Jupyter Notebooks to allow reproduction of the analysis presented here.
Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.
On the estimation of cooperativity in ion channel kinetics: activation free energy and kinetic mechanism of Shaker K+ channel.

PubMed

Banerjee, Kinshuk; Das, Biswajit; Gangopadhyay, Gautam

2013-04-28

In this paper, we have explored generic criteria of cooperative behavior in ion channel kinetics treating it on the same footing with multistate receptor-ligand binding in a compact theoretical framework. We have shown that the characterization of cooperativity of ion channels in terms of the Hill coefficient violates the standard Hill criteria defined for allosteric cooperativity of ligand binding. To resolve the issue, an alternative measure of cooperativity is proposed here in terms of the cooperativity index that sets a unified criteria for both the systems. More importantly, for ion channel this index can be very useful to describe the cooperative kinetics as it can be readily determined from the experimentally measured ionic current combined with theoretical modelling. We have analyzed the correlation between the voltage value and slope of the voltage-activation curve at the half-activation point and consequently determined the standard free energy of activation of the ion channel using two well-established mechanisms of cooperativity, namely, Koshland-Nemethy-Filmer (KNF) and Monod-Wyman-Changeux (MWC) models. Comparison of the theoretical results for both the models with appropriate experimental data of mutational perturbation of Shaker K(+) channel supports the experimental fact that the KNF model is more suitable to describe the cooperative behavior of this class of ion channels, whereas the performance of the MWC model is unsatisfactory. We have also estimated the mechanistic performance through standard free energy of channel activation for both the models and proposed a possible functional disadvantage in the MWC scheme.
Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models.

PubMed

Andreozzi, Stefano; Chakrabarti, Anirikh; Soh, Keng Cher; Burgard, Anthony; Yang, Tae Hoon; Van Dien, Stephen; Miskovic, Ljubisa; Hatzimanikatis, Vassily

2016-05-01

Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and effectiveness of ORACLE for the accelerated design of microbial cell factories. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
Mechanical model of giant photoexpansion in a chalcogenide glass and the role of photofluidity

NASA Astrophysics Data System (ADS)

Buisson, Manuel; Gueguen, Yann; Laniel, Romain; Cantoni, Christopher; Houizot, Patrick; Bureau, Bruno; Sangleboeuf, Jean-Christophe; Lucas, Pierre

2017-07-01

An analytical model is developed to describe the phenomenon of giant photoexpansion in chalcogenide glasses. The proposed micro-mechanical model is based on the description of photoexpansion as a new type of eigenstrain, i.e. a deformation analogous to thermal expansion induced without external forces. In this framework, it is the viscoelastic flow induced by photofluidity which enable the conversion of the self-equilibrated stress into giant photoexpansion. This simple approach yields good fits to experimental data and demonstrates, for the first time, that the photoinduced viscous flow actually enhances the giant photoexpansion or the giant photocontraction as it has been suggested in the literature. Moreover, it highlights that the shear relaxation time due to photofluidity controls the expansion kinetic. This model is the first step towards describing giant photoexpansion from the point of view of mechanics and it provides the framework for investigating this phenomenon via numerical simulations.
Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

NASA Technical Reports Server (NTRS)

Olevsky, Eugene; German, Randall M.

2012-01-01

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.
Snoopy--a unifying Petri net framework to investigate biomolecular networks.

PubMed

Rohr, Christian; Marwan, Wolfgang; Heiner, Monika

2010-04-01

To investigate biomolecular networks, Snoopy provides a unifying Petri net framework comprising a family of related Petri net classes. Models can be hierarchically structured, allowing for the mastering of larger networks. To move easily between the qualitative, stochastic and continuous modelling paradigms, models can be converted into each other. We get models sharing structure, but specialized by their kinetic information. The analysis and iterative reverse engineering of biomolecular networks is supported by the simultaneous use of several Petri net classes, while the graphical user interface adapts dynamically to the active one. Built-in animation and simulation are complemented by exports to various analysis tools. Snoopy facilitates the addition of new Petri net classes thanks to its generic design. Our tool with Petri net samples is available free of charge for non-commercial use at http://www-dssz.informatik.tu-cottbus.de/snoopy.html; supported operating systems: Mac OS X, Windows and Linux (selected distributions).
Novel Metal-Organic Framework (MOF) Based Composite Material for the Sequestration of U(VI) and Th(IV) Metal Ions from Aqueous Environment.

PubMed

Alqadami, Ayoub Abdullah; Naushad, Mu; Alothman, Zeid Abdullah; Ghfar, Ayman A

2017-10-18

The combination of magnetic nanoparticles and metal-organic frameworks (MOFs) has demonstrated their prospective for pollutant sequestration. In this work, a magnetic metal-organic framework nanocomposite (Fe 3 O 4 @AMCA-MIL53(Al) was prepared and used for the removal of U(VI) and Th(IV) metal ions from aqueous environment. Fe 3 O 4 @AMCA-MIL53(Al) nanocomposite was characterized by TGA, FTIR, SEM-EDX, XRD, HRTEM, BET, VSM (vibrating sample magnetometry), and XPS analyses. A batch technique was applied for the removal of the aforesaid metal ions using Fe 3 O 4 @AMCA-MIL53(Al) at different operating parameters. The isotherm and kinetic data were accurately described by the Langmuir and pseudo-second-order models. The adsorption capacity was calculated to be 227.3 and 285.7 mg/g for U(VI) and Th(IV), respectively, by fitting the equilibrium data to the Langmuir model. The kinetic studies demonstrated that the equilibrium time was 90 min for each metal ion. Various thermodynamic parameters were evaluated which indicated the endothermic and spontaneous nature of adsorption. The collected outcomes showed that Fe 3 O 4 @AMCA-MIL53(Al) was a good material for the exclusion of these metal ions from aqueous medium. The adsorbed metals were easily recovered by desorption in 0.01 M HCl. The excellent adsorption capacity and the response to the magnetic field made this novel material an auspicious candidate for environmental remediation technologies.
Mesoscale Modeling of Kinetic Phase Behaviors in Mg-B-H (Subcontract Report)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, H.; Thornton, K.; Wood, B. C.

Storage of hydrogen on board vehicles is one of the critical enabling technologies for creating hydrogenfueled transportation systems that can reduce oil dependency and mitigate the long-term effects of fossil fuels on climate change. Stakeholders in developing hydrogen infrastructure are currently focused on highpressure storage at 350 bar and 700 bar, in part because no viable solid-phase storage material has emerged. Nevertheless, solid-state materials, including high-density hydrides, remain of interest because of their unique potential to meet all DOE targets and deliver hydrogen at lower pressures and higher on-board densities. A successful solution would significantly reduce costs and ensure themore » economic viability of a U.S. hydrogen infrastructure. The Mg(BH 4) 2-MgB 2 system represents a highly promising solution because of its reasonable reaction enthalpy, high intrinsic capacity, and demonstrated reversibility, yet suffers from poor reaction kinetics. This subcontract aims to deliver a phase-field model for the kinetics of the evolution of the relevant phases within the Mg-B-H system during hydrogenation and dehydrogenation. This model will be used within a broader theory, synthesis, and characterization framework to study the properties of geometry-selected nanoparticles of pristine and doped MgB 2/Mg(BH 4) 2 with two aims: (1) understand the intrinsic limitations in (de)hydrogenation; (2) devise strategies for improving thermodynamics and kinetics through nanostructuring.« less
Refined elasticity sampling for Monte Carlo-based identification of stabilizing network patterns.

PubMed

Childs, Dorothee; Grimbs, Sergio; Selbig, Joachim

2015-06-15

Structural kinetic modelling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a representation of the system's Jacobian matrix that depends solely on the network structure, steady state measurements, and the elasticities at the steady state. For a measured steady state, stability criteria can be derived by generating a large number of SKMs with randomly sampled elasticities and evaluating the resulting Jacobian matrices. The elasticity space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Here, we extend this approach by examining the kinetic feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, we show that the majority of sampled SKMs would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion is formulated that mitigates such infeasible models. After evaluating the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle and the intrinsic mechanisms responsible for their stability or instability. The findings of the statistical elasticity analysis confirm that several elasticities are jointly coordinated to control stability and that the main source for potential instabilities are mutations in the enzyme alpha-ketoglutarate dehydrogenase. © The Author 2015. Published by Oxford University Press.
Asymptotic-Preserving methods and multiscale models for plasma physics

NASA Astrophysics Data System (ADS)

Degond, Pierre; Deluzet, Fabrice

2017-05-01

The purpose of the present paper is to provide an overview of Asymptotic-Preserving methods for multiscale plasma simulations by addressing three singular perturbation problems. First, the quasi-neutral limit of fluid and kinetic models is investigated in the framework of non-magnetized as well as magnetized plasmas. Second, the drift limit for fluid descriptions of thermal plasmas under large magnetic fields is addressed. Finally efficient numerical resolutions of anisotropic elliptic or diffusion equations arising in magnetized plasma simulation are reviewed.
Electronic coupling in long-range electron transfer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newton, M.D.

1996-12-31

One of the quantities crucial in controlling electron transfer (et) kinetics is the donor/acceptor electronic coupling integral (HDA). Recent theoretical models for HDA will be presented, and the results of ab initio computational implementation will be reported and analyzed for several metal-to-metal ligand charge transfer processes in complex molecular aggregates. New procedures for defining diabatic states, including a generalization of the Mulliken-Hush model, allow applications to optical and excited state as well as ground state et in a many-state framework.

Kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB): the influence of interfacial transport and bulk diffusion on the oxidation of oleic acid by ozone

NASA Astrophysics Data System (ADS)

Shiraiwa, Manabu; Pfrang, Christian; Pöschl, Ulrich

2010-05-01

Aerosols are ubiquitous in the atmosphere and have strong effects on climate and public health. Gas-particle interactions can significantly change the physical and chemical properties of aerosols such as toxicity, reactivity, hygroscopicity and radiative properties. Chemical reactions and mass transport lead to continuous transformation and changes in the composition of atmospheric aerosols ("chemical aging"). Resistor model formulations are widely used to describe and investigate heterogeneous reactions and multiphase processes in laboratory, field and model studies of atmospheric chemistry. The traditional resistor models, however, are usually based on simplifying assumptions such as steady state conditions, homogeneous mixing, and limited numbers of non-interacting species and processes. In order to overcome these limitations, Pöschl, Rudich and Ammann have developed a kinetic model framework (PRA framework) with a double-layer surface concept and universally applicable rate equations and parameters for mass transport and chemical reactions at the gas-particle interface of aerosols and clouds [1]. Based on the PRA framework, we present a novel kinetic multi-layer model that explicitly resolves mass transport and chemical reaction at the surface and in the bulk of aerosol particles (KM-SUB) [2]. The model includes reversible adsorption, surface reactions and surface-bulk exchange as well as bulk diffusion and reaction. Unlike earlier models, KM-SUB does not require simplifying assumptions about steady-state conditions and radial mixing. The temporal evolution and concentration profiles of volatile and non-volatile species at the gas-particle interface and in the particle bulk can be modeled along with surface concentrations and gas uptake coefficients. In this study we explore and exemplify the effects of bulk diffusion on the rate of reactive gas uptake for a simple reference system, the ozonolysis of oleic acid particles, in comparison to experimental data and earlier model studies. We demonstrate how KM-SUB can be used to interpret and analyze experimental data from laboratory studies, and how the results can be extrapolated to atmospheric conditions. In particular, we show how interfacial transport and bulk transport, i.e., surface accommodation, bulk accommodation and bulk diffusion, influence the kinetics of the chemical reaction. Sensitivity studies suggest that in fine air particulate matter oleic acid and compounds with similar reactivity against ozone (C=C double bonds) can reach chemical life-times of multiple hours only if they are embedded in a (semi-)solid matrix with very low diffusion coefficients (~10-10 cm2 s-1). Depending on the complexity of the investigated system, unlimited numbers of volatile and non-volatile species and chemical reactions can be flexibly added and treated with KM-SUB. We propose and intend to pursue the application of KM-SUB as a basis for the development of a detailed master mechanism of aerosol chemistry as well as for the derivation of simplified but realistic parameterizations for large-scale atmospheric and climate models. References [1] Pöschl et al., Atmos. Chem. and Phys., 7, 5989-6023 (2007). [2] Shiraiwa et al., Atmos. Chem. Phys. Discuss., 10, 281-326 (2010).
Demonstration of Anisotropic Fluid Closure Capturing the Kinetic Structure of Magnetic Reconnection

NASA Astrophysics Data System (ADS)

Ohia, Obioma

2012-10-01

Magnetic reconnection in collisionless plasmas plays an important role in space and laboratory plasmas. Allowing magnetic stress to be reduced by a rearrangement of magnetic line topology, this process is often accompanied by a large release of magnetic field energy, which can heat the plasma, drive large scale flows, or accelerate particles. Reconnection has been widely studied through fluid models and kinetic simulations. While two-fluid models often reproduce the fast reconnection that is observed in nature and seen in kinetic simulations, it is found that the structure surrounding the electron diffusion region and the electron current layer differ vastly between fluid models and kinetic simulations [1]. Recently, using an adiabatic solution of the Vlasov equation, a new fluid closure has been obtained for electrons that relate parallel and perpendicular pressures to the density and magnetic field [2]. Here we present the results of fluid simulation, developed using the HiFi framework [3], that implements new equations of state for guide-field reconnection. The new fluid closure accurately accounts for the anisotropic electron pressure that builds in the reconnection region due to electric and magnetic trapping of electrons. In contrast to previous fluid models, our fluid simulation reproduces the detailed reconnection region as observed in fully kinetic simulations [4]. We hereby demonstrate that the new fluid closure self-consistently captures all the physics relevant to the structure of the reconnection region, providing a gateway to a renewed and deeper theoretical understanding for reconnection in weakly collisional regimes.[4pt] [1] Daughton W et al., Phys. Plasmas 13, 072101 (2006).[0pt] [2] Le A et al., Phys. Rev. Lett. 102, 085001 (2009). [0pt] [3] Lukin VS, Linton MG, Nonlinear Proc. Geoph. 18, 871 (2011). [0pt] [4] Ohia O, et al., Phys. Rev. Lett. In Press (2012).
Computational Thermodynamics and Kinetics-Based ICME Framework for High-Temperature Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Arróyave, Raymundo; Talapatra, Anjana; Johnson, Luke; Singh, Navdeep; Ma, Ji; Karaman, Ibrahim

2015-11-01

Over the last decade, considerable interest in the development of High-Temperature Shape Memory Alloys (HTSMAs) for solid-state actuation has increased dramatically as key applications in the aerospace and automotive industry demand actuation temperatures well above those of conventional SMAs. Most of the research to date has focused on establishing the (forward) connections between chemistry, processing, (micro)structure, properties, and performance. Much less work has been dedicated to the development of frameworks capable of addressing the inverse problem of establishing necessary chemistry and processing schedules to achieve specific performance goals. Integrated Computational Materials Engineering (ICME) has emerged as a powerful framework to address this problem, although it has yet to be applied to the development of HTSMAs. In this paper, the contributions of computational thermodynamics and kinetics to ICME of HTSMAs are described. Some representative examples of the use of computational thermodynamics and kinetics to understand the phase stability and microstructural evolution in HTSMAs are discussed. Some very recent efforts at combining both to assist in the design of HTSMAs and limitations to the full implementation of ICME frameworks for HTSMA development are presented.
Effect of nonlocal electron kinetics on the characteristics of a dielectric barrier discharge in xenon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avtaeva, S. V.; Skornyakov, A. V.

2009-07-15

The established dynamics of a dielectric barrier discharge in xenon at a pressure of 400 Torr is simulated in the framework of a one-dimensional fluid model in the local and nonlocal field approximations. It is shown that taking into account the nonlocal character of the electric field does not qualitatively change physical processes in a dielectric barrier discharge, but significantly affects its quantitative characteristics. In particular, the sheath thickness decreases, plasma ionization intensifies, the spatiotemporal distribution of the mean electron energy changes, and the discharge radiation efficiency increases. Electron kinetics in a dielectric barrier discharge in xenon is analyzed usingmore » the nonlocal field approximation.« less
Kinetic energy spectra in thermionic emission from small tungsten cluster anions: evidence for nonclassical electron capture.

PubMed

Concina, Bruno; Baguenard, Bruno; Calvo, Florent; Bordas, Christian

2010-03-14

The delayed electron emission from small mass-selected anionic tungsten clusters W(n)(-) has been studied for sizes in the range 9 < or = n < or = 21. Kinetic energy spectra have been measured for delays of about 100 ns after laser excitation by a velocity-map imaging spectrometer. They are analyzed in the framework of microreversible statistical theories. The low-energy behavior shows some significant deviations with respect to the classical Langevin capture model, which we interpret as possibly due to the influence of quantum dynamical effects such as tunneling through the centrifugal barrier, rather than shape effects. The cluster temperature has been extracted from both the experimental kinetic energy spectrum and the absolute decay rate. Discrepancies between the two approaches suggest that the sticking probability can be as low as a few percent for the smallest clusters.
Fission fragment mass and total kinetic energy distributions of spontaneously fissioning plutonium isotopes

NASA Astrophysics Data System (ADS)

Pomorski, K.; Nerlo-Pomorska, B.; Bartel, J.; Schmitt, C.

2018-03-01

The fission-fragment mass and total kinetic energy (TKE) distributions are evaluated in a quantum mechanical framework using elongation, mass asymmetry, neck degree of freedom as the relevant collective parameters in the Fourier shape parametrization recently developed by us. The potential energy surfaces (PES) are calculated within the macroscopic-microscopic model based on the Lublin-Strasbourg Drop (LSD), the Yukawa-folded (YF) single-particle potential and a monopole pairing force. The PES are presented and analysed in detail for even-even Plutonium isotopes with A = 236-246. They reveal deep asymmetric valleys. The fission-fragment mass and TKE distributions are obtained from the ground state of a collective Hamiltonian computed within the Born-Oppenheimer approximation, in the WKB approach by introducing a neck-dependent fission probability. The calculated mass and total kinetic energy distributions are found in good agreement with the data.
Influence of ionic complexation on release rate profiles from multiple water-in-oil-in-water (W/O/W) emulsions.

PubMed

Bonnet, Marie; Cansell, Maud; Placin, Frédéric; David-Briand, Elisabeth; Anton, Marc; Leal-Calderon, Fernando

2010-07-14

Water-in-oil-in-water (W/O/W) double emulsions were prepared, and the kinetics of release of magnesium ions from the internal to the external water phase was followed. Different chelating agents (phosvitin and gluconate) were used to bind magnesium within the prospect of improving the ion retention in the internal aqueous droplets. Magnesium release was monitored for 1 month of storage, for each formulation, with and without chelation, at two storage temperatures (4 and 25 degrees C). Leakage occurred without film rupturing (coalescence) and was mainly due to entropically driven diffusion/permeation phenomena. The experimental results revealed a clear correlation between the effectiveness of chelating agents to delay the delivery and their binding capacity characterized by the equilibrium affinity constant. The kinetic data (percent released versus time curves) were interpreted within the framework of a kinetic model based on diffusion and taking into account magnesium chelation.
Local CFD kinetic model of cadmium vaporization during fluid bed incineration of municipal solid waste.

PubMed

Soria, J; Gauthier, D; Falcoz, Q; Flamant, G; Mazza, G

2013-03-15

The emissions of heavy metals during incineration of Municipal Solid Waste (MSW) are a major issue to health and the environment. It is then necessary to well quantify these emissions in order to accomplish an adequate control and prevent the heavy metals from leaving the stacks. In this study the kinetic behavior of Cadmium during Fluidized Bed Incineration (FBI) of artificial MSW pellets, for bed temperatures ranging from 923 to 1073 K, was modeled. FLUENT 12.1.4 was used as the modeling framework for the simulations and implemented together with a complete set of user-defined functions (UDFs). The CFD model combines the combustion of a single solid waste particle with heavy metal (HM) vaporization from the burning particle, and it takes also into account both pyrolysis and volatiles' combustion. A kinetic rate law for the Cd release, derived from the CFD thermal analysis of the combusting particle, is proposed. The simulation results are compared with experimental data obtained in a lab-scale fluidized bed incinerator reported in literature, and with the predicted values from a particulate non-isothermal model, formerly developed by the authors. The comparison shows that the proposed CFD model represents very well the evolution of the HM release for the considered range of bed temperature. Copyright © 2013 Elsevier B.V. All rights reserved.
Effects of Transition-Metal Mixing on Na Ordering and Kinetics in Layered P 2 Oxides

NASA Astrophysics Data System (ADS)

Zheng, Chen; Radhakrishnan, Balachandran; Chu, Iek-Heng; Wang, Zhenbin; Ong, Shyue Ping

2017-06-01

Layered P 2 oxides are promising cathode materials for rechargeable sodium-ion batteries. In this work, we systematically investigate the effects of transition-metal (TM) mixing on Na ordering and kinetics in the NaxCo1 -yMnyO2 model system using density-functional-theory (DFT) calculations. The DFT-predicted 0-K stability diagrams indicate that Co-Mn mixing reduces the energetic differences between Na orderings, which may account for the reduction of the number of phase transformations observed during the cycling of mixed-TM P 2 layered oxides compared to a single TM. Using ab initio molecular-dynamics simulations and nudged elastic-band calculations, we show that the TM composition at the Na(1) (face-sharing) site has a strong influence on the Na site energies, which in turn impacts the kinetics of Na diffusion towards the end of the charge. By employing a site-percolation model, we establish theoretical upper and lower bounds for TM concentrations based on their effect on Na(1) site energies, providing a framework to rationally tune mixed-TM compositions for optimal Na diffusion.
Empirical kinetics and their role in elucidating the utility of transition-state theory to mineral–water reactions. A comment upon, ''Evidence and Potential Implications of Exponential Tails to Concentration Versus Time Plots for the Batch Dissolution of Calcite'' by V. W. Truesdale

DOE PAGES

Icenhower, Jonathan P.

2015-06-23

Transition-state theory (TST) is a successful theory for understanding many different types of reactions, but its application to mineral-water systems has not been successful, especially as the system approaches saturation with respect to a rate-limiting phase. A number of investigators have proposed alternate frameworks for using the kinetic rate data to construct models of dissolution, including Truesdale (Aquat Geochem, 2015; this issue). This alternate approach has been resisted, in spite of self-evident discrepancies between TST expectations and the data. The failure of TST under certain circumstances is a result of the presence of metastable intermediaries or reaction layers that formmore » on the surface of reacting solids, and these phenomena are not anticipated by the current theory. Furthermore, alternate approaches, such as the shrinking object model advocated by Truesdale, represent a potentially important avenue for advancing the science of dissolution kinetics.« less
Generalized first-order kinetic model for biosolids decomposition and oxidation during hydrothermal treatment.

PubMed

Shanableh, A

2005-01-01

The main objective of this study was to develop generalized first-order kinetic models to represent hydrothermal decomposition and oxidation of biosolids within a wide range of temperatures (200-450 degrees C). A lumping approach was used in which oxidation of the various organic ingredients was characterized by the chemical oxygen demand (COD), and decomposition was characterized by the particulate (i.e., nonfilterable) chemical oxygen demand (PCOD). Using the Arrhenius equation (k = k(o)e(-Ea/RT)), activation energy (Ea) levels were derived from 42 continuous-flow hydrothermal treatment experiments conducted at temperatures in the range of 200-450 degrees C. Using predetermined values for k(o) in the Arrhenius equation, the activation energies of the various organic ingredients were separated into 42 values for oxidation and a similar number for decomposition. The activation energy values were then classified into levels representing the relative ease at which the organic ingredients of the biosolids were oxidized or decomposed. The resulting simple first-order kinetic models adequately represented, within the experimental data range, hydrothermal decomposition of the organic particles as measured by PCOD and oxidation of the organic content as measured by COD. The modeling approach presented in the paper provide a simple and general framework suitable for assessing the relative reaction rates of the various organic ingredients of biosolids.
Nondeterministic computational fluid dynamics modeling of Escherichia coli inactivation by peracetic acid in municipal wastewater contact tanks.

PubMed

Santoro, Domenico; Crapulli, Ferdinando; Raisee, Mehrdad; Raspa, Giuseppe; Haas, Charles N

2015-06-16

Wastewater disinfection processes are typically designed according to heuristics derived from batch experiments in which the interaction among wastewater quality, reactor hydraulics, and inactivation kinetics is often neglected. In this paper, a computational fluid dynamics (CFD) study was conducted in a nondeterministic (ND) modeling framework to predict the Escherichia coli inactivation by peracetic acid (PAA) in municipal contact tanks fed by secondary settled wastewater effluent. The extent and variability associated with the observed inactivation kinetics were both satisfactorily predicted by the stochastic inactivation model at a 95% confidence level. Moreover, it was found that (a) the process variability induced by reactor hydraulics is negligible when compared to the one caused by inactivation kinetics, (b) the PAA dose required for meeting regulations is dictated equally by the fixed limit of the microbial concentration as well as its probability of occurrence, and (c) neglecting the probability of occurrence during process sizing could lead to an underestimation of the PAA dose required by as much as 100%. Finally, the ND-CFD model was used to generate sizing information in the form of probabilistic disinfection curves relating E. coli inactivation and probability of occurrence with the average PAA dose and PAA residual concentration at the outlet of the contact tank.
A framework for expanding aqueous chemistry in the ...

EPA Pesticide Factsheets

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM − KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from bio
Does the stepwave model predict mica dissolution kinetics?

NASA Astrophysics Data System (ADS)

Kurganskaya, Inna; Arvidson, Rolf S.; Fischer, Cornelius; Luttge, Andreas

2012-11-01

The micas are a unique class of minerals because of their layered structure. A frequent question arising in mica dissolution studies is whether this layered structure radically changes the dissolution mechanism. We address this question here, using data from VSI and AFM experiments involving muscovite to evaluate crystallographic controls on mica dissolution. These data provide insight into the dissolution process, and reveal important links to patterns of dissolution observed in framework minerals. Under our experimental conditions (pH 9.4, 155 °C), the minimal global rate of normal surface retreat observed in VSI data was 1.42 × 10-10 mol/m2/s (σ = 27%) while the local rate observed at deep etch pits reached 416 × 10-10 mol/m2/s (σ = 49%). Complementary AFM data clearly show crystallographic control of mica dissolution, both in terms of step advance and the geometric influence of interlayer rotation (stacking periodicity). These observations indicate that basal/edge surface area ratios are highly variable and change continuously over the course of reaction, thus obviating their utility as characteristic parameters defining mica reactivity. Instead, these observations of overall dissolution rate and the influence of screw dislocations illustrate the link between atomic step movement and overall dissolution rate defined by surface retreat normal to the mica surface. Considered in light of similar observations available elsewhere in the literature, these relationships provide support for application of the stepwave model to mica dissolution kinetics. This approach provides a basic mechanistic link between the dissolution kinetics of phyllosilicates, framework silicates, and related minerals, and suggests a resolution to the general problem of mica reactivity.
Molecular mechanisms of protein aggregation from global fitting of kinetic models.

PubMed

Meisl, Georg; Kirkegaard, Julius B; Arosio, Paolo; Michaels, Thomas C T; Vendruscolo, Michele; Dobson, Christopher M; Linse, Sara; Knowles, Tuomas P J

2016-02-01

The elucidation of the molecular mechanisms by which soluble proteins convert into their amyloid forms is a fundamental prerequisite for understanding and controlling disorders that are linked to protein aggregation, such as Alzheimer's and Parkinson's diseases. However, because of the complexity associated with aggregation reaction networks, the analysis of kinetic data of protein aggregation to obtain the underlying mechanisms represents a complex task. Here we describe a framework, using quantitative kinetic assays and global fitting, to determine and to verify a molecular mechanism for aggregation reactions that is compatible with experimental kinetic data. We implement this approach in a web-based software, AmyloFit. Our procedure starts from the results of kinetic experiments that measure the concentration of aggregate mass as a function of time. We illustrate the approach with results from the aggregation of the β-amyloid (Aβ) peptides measured using thioflavin T, but the method is suitable for data from any similar kinetic experiment measuring the accumulation of aggregate mass as a function of time; the input data are in the form of a tab-separated text file. We also outline general experimental strategies and practical considerations for obtaining kinetic data of sufficient quality to draw detailed mechanistic conclusions, and the procedure starts with instructions for extensive data quality control. For the core part of the analysis, we provide an online platform (http://www.amylofit.ch.cam.ac.uk) that enables robust global analysis of kinetic data without the need for extensive programming or detailed mathematical knowledge. The software automates repetitive tasks and guides users through the key steps of kinetic analysis: determination of constraints to be placed on the aggregation mechanism based on the concentration dependence of the aggregation reaction, choosing from several fundamental models describing assembly into linear aggregates and fitting the chosen models using an advanced minimization algorithm to yield the reaction orders and rate constants. Finally, we outline how to use this approach to investigate which targets potential inhibitors of amyloid formation bind to and where in the reaction mechanism they act. The protocol, from processing data to determining mechanisms, can be completed in <1 d.
Multiscale modelling for tokamak pedestals

NASA Astrophysics Data System (ADS)

Abel, I. G.

2018-04-01

Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a first-principles multiscale approach to the pedestal. We will present three separate sets of equations, covering the dynamics of edge localised modes (ELMs), the inter-ELM pedestal and pedestal turbulence, respectively. Precisely how these equations should be coupled to each other is covered in detail. This framework is completely self-consistent; it is derived from first principles by means of an asymptotic expansion of the fundamental Vlasov-Landau-Maxwell system in appropriate small parameters. The derivation exploits the narrowness of the pedestal region, the smallness of the thermal gyroradius and the low plasma (the ratio of thermal to magnetic pressures) typical of current pedestal operation to achieve its simplifications. The relationship between this framework and gyrokinetics is analysed, and possibilities to directly match our systems of equations onto multiscale gyrokinetics are explored. A detailed comparison between our model and other models in the literature is performed. Finally, the potential for matching this framework onto an open-field-line region is briefly discussed.
Quantitative pharmacological analysis of antagonist binding kinetics at CRF1 receptors in vitro and in vivo

PubMed Central

Ramsey, Simeon J; Attkins, Neil J; Fish, Rebecca; van der Graaf, Piet H

2011-01-01

BACKGROUND AND PURPOSE A series of novel non-peptide corticotropin releasing factor type-1 receptor (CRF1) antagonists were found to display varying degrees of insurmountable and non-competitive behaviour in functional in vitro assays. We describe how we attempted to relate this behaviour to ligand receptor-binding kinetics in a quantitative manner and how this resulted in the development and implementation of an efficient pharmacological screening method based on principles described by Motulsky and Mahan. EXPERIMENTAL APPROACH A non-equilibrium binding kinetic assay was developed to determine the receptor binding kinetics of non-peptide CRF1 antagonists. Nonlinear, mixed-effects modelling was used to obtain estimates of the compounds association and dissociation rates. We present an integrated pharmacokinetic–pharmacodynamic (PKPD) approach, whereby the time course of in vivo CRF1 receptor binding of novel compounds can be predicted on the basis of in vitro assays. KEY RESULTS The non-competitive antagonist behaviour appeared to be correlated to the CRF1 receptor off-rate kinetics. The integrated PKPD model suggested that, at least in a qualitative manner, the in vitro assay can be used to triage and select compounds for further in vivo investigations. CONCLUSIONS AND IMPLICATIONS This study provides evidence for a link between ligand offset kinetics and insurmountable/non-competitive antagonism at the CRF1 receptor. The exact molecular pharmacological nature of this association remains to be determined. In addition, we have developed a quantitative framework to study and integrate in vitro and in vivo receptor binding kinetic behaviour of CRF1 receptor antagonists in an efficient manner in a drug discovery setting. PMID:21449919
Kfits: a software framework for fitting and cleaning outliers in kinetic measurements.

PubMed

Rimon, Oded; Reichmann, Dana

2018-01-01

Kinetic measurements have played an important role in elucidating biochemical and biophysical phenomena for over a century. While many tools for analysing kinetic measurements exist, most require low noise levels in the data, leaving outlier measurements to be cleaned manually. This is particularly true for protein misfolding and aggregation processes, which are extremely noisy and hence difficult to model. Understanding these processes is paramount, as they are associated with diverse physiological processes and disorders, most notably neurodegenerative diseases. Therefore, a better tool for analysing and cleaning protein aggregation traces is required. Here we introduce Kfits, an intuitive graphical tool for detecting and removing noise caused by outliers in protein aggregation kinetics data. Following its workflow allows the user to quickly and easily clean large quantities of data and receive kinetic parameters for assessment of the results. With minor adjustments, the software can be applied to any type of kinetic measurements, not restricted to protein aggregation. Kfits is implemented in Python and available online at http://kfits.reichmannlab.com, in source at https://github.com/odedrim/kfits/, or by direct installation from PyPI (`pip install kfits`). danare@mail.huji.ac.il. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Localized Models of Charged Particle Motion in Martian Crustal Magnetic Cusps

NASA Astrophysics Data System (ADS)

Brain, D. A.; Poppe, A. R.; Jarvinen, R.; Dong, Y.; Egan, H. L.; Fang, X.

2017-12-01

The induced magnetosphere of Mars is punctuated by localized but strong crustal magnetic fields that are observed to play host to a variety of phenomena typically associated with global magnetic fields, such as auroral processes and particle precipitation, field-aligned current systems, and ion outflow. Each of these phenomena occur on the night side, in small-scale magnetic `cusp' regions of vertically aligned field. Cusp regions are not yet capable of being spatially resolved in global scale models that include the ion kinetics necessary for simulating charged particle transport along cusps. Local models are therefore necessary if we are to understand how cusp processes operate at Mars. Here we present the first results of an effort to model the kinetic particle motion and electric fields in Martian cusps. We are adapting both a 1.5D Particle-in-Cell (PIC) model for lunar magnetic cusps regions to the Martian case and a hybrid model framework (used previously for the global Martian plasma interaction and for lunar magnetic anomaly regions) to cusps in 2D. By comparing the models we can asses the importance of electron kinetics in particle transport along cusp field lines. In this first stage of our study we model a moderately strong nightside cusp, with incident hot hydrogen plasma from above, and cold planetary (oxygen) plasma entering the simulation from below. We report on the spatial and temporal distribution of plasma along cusp field lines for this initial case.
Storm time plasma transport in a unified and inter-coupled global magnetosphere model

NASA Astrophysics Data System (ADS)

Ilie, R.; Liemohn, M. W.; Toth, G.

2014-12-01

We present results from the two-way self-consistent coupling between the kinetic Hot Electron and Ion Drift Integrator (HEIDI) model and the Space Weather Modeling Framework (SWMF). HEIDI solves the time dependent, gyration and bounced averaged kinetic equation for the phase space density of different ring current species and computes full pitch angle distributions for all local times and radial distances. During geomagnetic times the dipole approximation becomes unsuitable even in the inner magnetosphere. Therefore the HEIDI model was generalized to accommodate an arbitrary magnetic field and through the coupling with SWMF it obtains a magnetic field description throughout the HEIDI domain along with a plasma distribution at the model outer boundary from the Block Adaptive Tree Solar Wind Roe Upwind Scheme (BATS-R-US) magnetohydrodynamics (MHD) model within SWMF. Electric field self-consistency is assured by the passing of convection potentials from the Ridley Ionosphere Model (RIM) within SWMF. In this study we test the various levels of coupling between the 3 physics based models, highlighting the role that the magnetic field, plasma sheet conditions and the cross polar cap potential play in the formation and evolution of the ring current. We show that the dynamically changing geospace environment itself plays a key role in determining the geoeffectiveness of the driver. The results of the self-consistent coupling between HEIDI, BATS-R-US and RIM during disturbed conditions emphasize the importance of a kinetic self-consistent approach to the description of geospace.

Modeling of dielectric properties of aqueous salt solutions with an equation of state.

PubMed

Maribo-Mogensen, Bjørn; Kontogeorgis, Georgios M; Thomsen, Kaj

2013-09-12

The static permittivity is the most important physical property for thermodynamic models that account for the electrostatic interactions between ions. The measured static permittivity in mixtures containing electrolytes is reduced due to kinetic depolarization and reorientation of the dipoles in the electrical field surrounding ions. Kinetic depolarization may explain 25-75% of the observed decrease in the permittivity of solutions containing salts, but since this is a dynamic property, this effect should not be included in the thermodynamic modeling of electrolytes. Kinetic depolarization has, however, been ignored in relation to thermodynamic modeling, and authors have either neglected the effect of salts on permittivity or used empirical correlations fitted to the measured static permittivity, leading to an overestimation of the reduction in the thermodynamic static permittivity. We present a new methodology for obtaining the static permittivity over wide ranges of temperatures, pressures, and compositions for use within an equation of state for mixed solvents containing salts. The static permittivity is calculated from a new extension of the framework developed by Onsager, Kirkwood, and Fröhlich to associating mixtures. Wertheim's association model as formulated in the statistical associating fluid theory is used to account for hydrogen-bonding molecules and ion-solvent association. Finally, we compare the Debye-Hückel Helmholtz energy obtained using an empirical model with the new physical model and show that the empirical models may introduce unphysical behavior in the equation of state.
A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms.

PubMed

Balbi, Pietro; Massobrio, Paolo; Hellgren Kotaleski, Jeanette

2017-09-01

Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.
Non-equilibrium dynamics of artificial quantum matter

NASA Astrophysics Data System (ADS)

Babadi, Mehrtash

The rapid progress of the field of ultracold atoms during the past two decades has set new milestones in our control over matter. By cooling dilute atomic gases and molecules to nano-Kelvin temperatures, novel quantum mechanical states of matter can be realized and studied on a table-top experimental setup while bulk matter can be tailored to faithfully simulate abstract theoretical models. Two of such models which have witnessed significant experimental and theoretical attention are (1) the two-component Fermi gas with resonant s-wave interactions, and (2) the single-component Fermi gas with dipole-dipole interactions. This thesis is devoted to studying the non-equilibrium collective dynamics of these systems using the general framework of quantum kinetic theory. We present a concise review of the utilized mathematical methods in the first two chapters, including the Schwinger-Keldysh formalism of non-equilibrium quantum fields, two-particle irreducible (2PI) effective actions and the framework of quantum kinetic theory. We study the collective dynamics of the dipolar Fermi gas in a quasi-two-dimensional optical trap in chapter 3 and provide a detailed account of its dynamical crossover from the collisionless to the hydrodynamical regime. Chapter 4 is devoted to studying the dynamics of the attractive Fermi gas in the normal phase. Starting from the self-consistent T-matrix (pairing fluctuation) approximation, we systematically derive a set of quantum kinetic equations and show that they provide a globally valid description of the dynamics of the attractive Fermi gas, ranging from the weak-coupling Fermi liquid phase to the intermediate non-Fermi liquid pairing pseudogap regime and finally the strong-coupling Bose liquid phase. The shortcomings of the self-consistent T-matrix approximation in two spatial dimensions are discussed along with a proposal to overcome its unphysical behaviors. The developed kinetic formalism is finally utilized to reproduce and interpret the findings of a recent experiment done on the collective dynamics of trapped two-dimensional ultracold gases.
Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950
Direct Measurements of Quantum Kinetic Energy Tensor in Stable and Metastable Water near the Triple Point: An Experimental Benchmark.

PubMed

Andreani, Carla; Romanelli, Giovanni; Senesi, Roberto

2016-06-16

This study presents the first direct and quantitative measurement of the nuclear momentum distribution anisotropy and the quantum kinetic energy tensor in stable and metastable (supercooled) water near its triple point, using deep inelastic neutron scattering (DINS). From the experimental spectra, accurate line shapes of the hydrogen momentum distributions are derived using an anisotropic Gaussian and a model-independent framework. The experimental results, benchmarked with those obtained for the solid phase, provide the state of the art directional values of the hydrogen mean kinetic energy in metastable water. The determinations of the direction kinetic energies in the supercooled phase, provide accurate and quantitative measurements of these dynamical observables in metastable and stable phases, that is, key insight in the physical mechanisms of the hydrogen quantum state in both disordered and polycrystalline systems. The remarkable findings of this study establish novel insight into further expand the capacity and accuracy of DINS investigations of the nuclear quantum effects in water and represent reference experimental values for theoretical investigations.
Stochastic foundations of undulatory transport phenomena: generalized Poisson-Kac processes—part III extensions and applications to kinetic theory and transport

NASA Astrophysics Data System (ADS)

Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro

2017-08-01

This third part extends the theory of Generalized Poisson-Kac (GPK) processes to nonlinear stochastic models and to a continuum of states. Nonlinearity is treated in two ways: (i) as a dependence of the parameters (intensity of the stochastic velocity, transition rates) of the stochastic perturbation on the state variable, similarly to the case of nonlinear Langevin equations, and (ii) as the dependence of the stochastic microdynamic equations of motion on the statistical description of the process itself (nonlinear Fokker-Planck-Kac models). Several numerical and physical examples illustrate the theory. Gathering nonlinearity and a continuum of states, GPK theory provides a stochastic derivation of the nonlinear Boltzmann equation, furnishing a positive answer to the Kac’s program in kinetic theory. The transition from stochastic microdynamics to transport theory within the framework of the GPK paradigm is also addressed.
Aerobic biodegradation kinetics for 1,4-dioxane under metabolic and cometabolic conditions.

PubMed

Barajas-Rodriguez, Francisco J; Freedman, David L

2018-05-15

Biodegradation of 1,4-dioxane has been studied extensively, however, there is insufficient information on the kinetic characteristics of cometabolism by propanotrophs and a lack of systematic comparisons to metabolic biodegradation. To fill in these gaps, experiments were performed with suspended growth cultures to determine 16 Monod kinetic coefficients that describe metabolic consumption of 1,4-dioxane by Pseudonocardia dioxanivorans CB1190 and cometabolism by the propanotrophic mixed culture ENV487 and the propanotroph Rhodococcus ruber ENV425. Maximum specific growth rates were highest for ENV425, followed by ENV487 and CB1190. Half saturation constants for 1,4-dioxane for the propanotrophs were one-half to one-quarter those for CB1190. Propane was preferentially degraded over 1,4-dioxane, but the reverse did not occur. A kinetic model was used to simulate batch biodegradation of 1,4-dioxane. Propanotrophs decreased 1,4-dioxane from 1000 to 1 μg/L in less time than CB1190 when the initial biomass concentration was 0.74 mg COD/L; metabolic biodegradation was favored at higher initial biomass concentrations and higher initial 1,4-dioxane concentrations. 1,4-Dioxane biodegradation was inhibited when oxygen was below 1.5 mg/L. The kinetic model provides a framework for comparing in situ biodegradation of 1,4-dioxane via bioaugmentation with cultures that use the contaminant as a growth substrate to those that achieve biodegradation via cometabolism. Copyright © 2018 Elsevier B.V. All rights reserved.
Modelling studies for photocatalytic degradation of organic dyes using TiO2 nanofibers.

PubMed

Singh, Narendra; Rana, Mohit Singh; Gupta, Raju Kumar

2017-09-05

In this work, modelling of the photocatalytic degradation of para-nitrophenol (PNP) using synthesized electrospun TiO 2 nanofibers under UV light illumination is reported. A dynamic model was developed in order to understand the behaviour of operating parameters, i.e. light intensity and catalyst loading on the photocatalytic activity. This model was simulated and analysed for both TiO 2 solid nanofibers and TiO 2 hollow nanofibers, applied as photocatalysts in the Langmuir-Hinshelwood kinetic framework. The entire photocatalytic degradation rate follows pseudo-first-order kinetics. The simulated results obtained from the developed model are in good agreement with the experimental results. At a catalyst loading of 1.0 mg mL -1 , better respective degradation rates were achieved at UV light irradiance of 4 mW cm -2 , for both the TiO 2 solid and hollow nanofibers. However, it was also observed that TiO 2 hollow nanofibers have a higher adsorption rate than that of TiO 2 solid nanofibers resulting in a higher photocatalytic degradation rate of PNP.
Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data.

PubMed

Hill, Deborah K; Orton, Matthew R; Mariotti, Erika; Boult, Jessica K R; Panek, Rafal; Jafar, Maysam; Parkes, Harold G; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M S; Beloueche-Babari, Mounia; Robinson, Simon P; Leach, Martin O; Chung, Yuen-Li; Eykyn, Thomas R

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13)C metabolic imaging in humans, where measurement of the input function can be problematic.
Model Free Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data

PubMed Central

Mariotti, Erika; Boult, Jessica K. R.; Panek, Rafal; Jafar, Maysam; Parkes, Harold G.; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M. S.; Beloueche-Babari, Mounia; Robinson, Simon P.; Leach, Martin O.; Chung, Yuen-Li; Eykyn, Thomas R.

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized 13C metabolic imaging in humans, where measurement of the input function can be problematic. PMID:24023724
Preparation and performance study of MgFe2O4/metal-organic framework composite for rapid removal of organic dyes from water

NASA Astrophysics Data System (ADS)

Tian, Huairu; Peng, Jun; Lv, Tingting; Sun, Chen; He, Hua

2018-01-01

In present study, a stable and magnetic metal-organic framework (MOF) material was synthesized by simple solvothermal method as adsorbent to rapid removal of two organic dyes, the Rhodamine B (RB) and Rhodamine 6G (Rh6G), in water samples. The prepared material showed great characteristics of large surface area (519.86 m2 g-1), excellent magnetic responsivity (35.00 emu g-1) and rapid removal (within 5 min). Maximum adsorption capacities of the magnetic material toward RB and Rh6G were up to 219.78 and 306.75 mg g-1, respectively. Adsorption kinetics suggested the adsorption process met the pseudo-second-order kinetic model. The prepared material could be reused at least 10 times by washing with acetonitrile solution, the relative standard deviation (RSD) of these ten cycles removal efficiency was 4.8%. In conclusion, good chemical inertness, a mechanical/water stability and super-hydrophilicity feature made this MOF a promising adsorbent for targets removal from environmental water sample.
Activated desorption at heterogeneous interfaces and long-time kinetics of hydrocarbon recovery from nanoporous media

PubMed Central

Lee, Thomas; Bocquet, Lydéric; Coasne, Benoit

2016-01-01

Hydrocarbon recovery from unconventional reservoirs (shale gas) is debated due to its environmental impact and uncertainties on its predictability. But a lack of scientific knowledge impedes the proposal of reliable alternatives. The requirement of hydrofracking, fast recovery decay and ultra-low permeability—inherent to their nanoporosity—are specificities of these reservoirs, which challenge existing frameworks. Here we use molecular simulation and statistical models to show that recovery is hampered by interfacial effects at the wet kerogen surface. Recovery is shown to be thermally activated with an energy barrier modelled from the interface wetting properties. We build a statistical model of the recovery kinetics with a two-regime decline that is consistent with published data: a short time decay, consistent with Darcy description, followed by a fast algebraic decay resulting from increasingly unreachable energy barriers. Replacing water by CO2 or propane eliminates the barriers, therefore raising hopes for clean/efficient recovery. PMID:27327254
Mixing-controlled reactive transport on travel times in heterogeneous media

NASA Astrophysics Data System (ADS)

Luo, J.; Cirpka, O.

2008-05-01

Modeling mixing-controlled reactive transport using traditional spatial discretization of the domain requires identifying the spatial distributions of hydraulic and reactive parameters including mixing-related quantities such as dispersivities and kinetic mass-transfer coefficients. In most applications, breakthrough curves of conservative and reactive compounds are measured at only a few locations and models are calibrated by matching these breakthrough curves, which is an ill posed inverse problem. By contrast, travel-time based transport models avoid costly aquifer characterization. By considering breakthrough curves measured on different scales, one can distinguish between mixing, which is a prerequisite for reactions, and spreading, which per se does not foster reactions. In the travel-time based framework, the breakthrough curve of a solute crossing an observation plane, or ending in a well, is interpreted as the weighted average of concentrations in an ensemble of non-interacting streamtubes, each of which is characterized by a distinct travel-time value. Mixing is described by longitudinal dispersion and/or kinetic mass transfer along individual streamtubes, whereas spreading is characterized by the distribution of travel times which also determines the weights associated to each stream tube. Key issues in using the travel-time based framework include the description of mixing mechanisms and the estimation of the travel-time distribution. In this work, we account for both apparent longitudinal dispersion and kinetic mass transfer as mixing mechanisms, thus generalizing the stochastic-convective model with or without inter-phase mass transfer and the advective-dispersive streamtube model. We present a nonparametric approach of determining the travel-time distribution, given a breakthrough curve integrated over an observation plane and estimated mixing parameters. The latter approach is superior to fitting parametric models in cases where the true travel-time distribution exhibits multiple peaks or long tails. It is demonstrated that there is freedom for the combinations of mixing parameters and travel-time distributions to fit conservative breakthrough curves and describe the tailing. Reactive transport cases with a bimolecular instantaneous irreversible reaction and a dual Michaelis-Menten problem demonstrate that the mixing introduced by local dispersion and mass transfer may be described by apparent mean mass transfer with coefficients evaluated by local breakthrough curves.
Quantitative Connection Between Ensemble Thermodynamics and Single-Molecule Kinetics: A Case Study Using Cryo-EM and smFRET Investigations of the Ribosome

PubMed Central

Frank, Joachim; Gonzalez, Ruben L.

2015-01-01

At equilibrium, thermodynamic and kinetic information can be extracted from biomolecular energy landscapes by many techniques. However, while static, ensemble techniques yield thermodynamic data, often only dynamic, single-molecule techniques can yield the kinetic data that describes transition-state energy barriers. Here we present a generalized framework based upon dwell-time distributions that can be used to connect such static, ensemble techniques with dynamic, single-molecule techniques, and thus characterize energy landscapes to greater resolutions. We demonstrate the utility of this framework by applying it to cryogenic electron microscopy and single-molecule fluorescence resonance energy transfer studies of the bacterial ribosomal pretranslocation complex. Among other benefits, application of this framework to these data explains why two transient, intermediate conformations of the pretranslocation complex, which are observed in a cryogenic electron microscopy study, may not be observed in several single-molecule fluorescence resonance energy transfer studies. PMID:25785884
Quantitative Connection between Ensemble Thermodynamics and Single-Molecule Kinetics: A Case Study Using Cryogenic Electron Microscopy and Single-Molecule Fluorescence Resonance Energy Transfer Investigations of the Ribosome.

PubMed

Thompson, Colin D Kinz; Sharma, Ajeet K; Frank, Joachim; Gonzalez, Ruben L; Chowdhury, Debashish

2015-08-27

At equilibrium, thermodynamic and kinetic information can be extracted from biomolecular energy landscapes by many techniques. However, while static, ensemble techniques yield thermodynamic data, often only dynamic, single-molecule techniques can yield the kinetic data that describe transition-state energy barriers. Here we present a generalized framework based upon dwell-time distributions that can be used to connect such static, ensemble techniques with dynamic, single-molecule techniques, and thus characterize energy landscapes to greater resolutions. We demonstrate the utility of this framework by applying it to cryogenic electron microscopy (cryo-EM) and single-molecule fluorescence resonance energy transfer (smFRET) studies of the bacterial ribosomal pre-translocation complex. Among other benefits, application of this framework to these data explains why two transient, intermediate conformations of the pre-translocation complex, which are observed in a cryo-EM study, may not be observed in several smFRET studies.
Generalized hydrodynamic reductions of the kinetic equation for a soliton gas

NASA Astrophysics Data System (ADS)

Pavlov, M. V.; Taranov, V. B.; El, G. A.

2012-05-01

We derive generalized multiflow hydrodynamic reductions of the nonlocal kinetic equation for a soliton gas and investigate their structure. These reductions not only provide further insight into the properties of the new kinetic equation but also could prove to be representatives of a novel class of integrable systems of hydrodynamic type beyond the conventional semi-Hamiltonian framework.
Continuous Time Random Walk and Migration-Proliferation Dichotomy of Brain Cancer

NASA Astrophysics Data System (ADS)

Iomin, A.

A theory of fractional kinetics of glial cancer cells is presented. A role of the migration-proliferation dichotomy in the fractional cancer cell dynamics in the outer-invasive zone is discussed and explained in the framework of a continuous time random walk. The main suggested model is based on a construction of a 3D comb model, where the migration-proliferation dichotomy becomes naturally apparent and the outer-invasive zone of glioma cancer is considered as a fractal composite with a fractal dimension Dfr < 3.
An integrated computational tool for precipitation simulation

NASA Astrophysics Data System (ADS)

Cao, W.; Zhang, F.; Chen, S.-L.; Zhang, C.; Chang, Y. A.

2011-07-01

Computer aided materials design is of increasing interest because the conventional approach solely relying on experimentation is no longer viable within the constraint of available resources. Modeling of microstructure and mechanical properties during precipitation plays a critical role in understanding the behavior of materials and thus accelerating the development of materials. Nevertheless, an integrated computational tool coupling reliable thermodynamic calculation, kinetic simulation, and property prediction of multi-component systems for industrial applications is rarely available. In this regard, we are developing a software package, PanPrecipitation, under the framework of integrated computational materials engineering to simulate precipitation kinetics. It is seamlessly integrated with the thermodynamic calculation engine, PanEngine, to obtain accurate thermodynamic properties and atomic mobility data necessary for precipitation simulation.
Acid Gas Stability of Zeolitic Imidazolate Frameworks: Generalized Kinetic and Thermodynamic Characteristics

DOE PAGES

Bhattacharyya, Souryadeep; Han, Rebecca; Kim, Wun -Gwi; ...

2018-05-29

Here, acid gases such as SO 2 and CO 2 are present in many environments in which the use of nanoporous metal-organic frameworks (MOFs) is envisaged. Among metal-organic frameworks, zeolitic imidazolate frameworks (ZIFs) have been extensively explored as membranes or adsorbents. However, there is little systematic knowledge of the effects of acid gas exposure on the structure of ZIFs, in particular the mechanistic aspects of ZIF degradation by acid gases as well as the effects of ZIF crystal topology and linker composition on their stability. Here we present a generalized and quantitative investigation of the kinetic and thermodynamic acid gasmore » stability of a diverse range of ZIF materials. The stability of 16 ZIFs (of SOD, RHO, ANA, and GME topologies) under different environments – humid air, liquid water, and acid gases CO 2 and SO 2 (dry, humid, and aqueous) – are investigated by a suite of experimental and computational methods. The kinetics of ZIF degradation under exposure to humid SO 2 is studied in detail, and effective rate constants for acid gas degradation of ZIFs are reported for the first time. Remarkably, the kinetics of degradation of the diverse ZIFs correlate strongly with the linker pKa and ZIF water adsorption in a manner contrary to that expected from previous predictions in the literature. Furthermore, we find that the material ZIF-71 (RHO topology) shows much higher stability relative to the other ZIFs in humid SO 2 and CO 2 environments.« less
Acid Gas Stability of Zeolitic Imidazolate Frameworks: Generalized Kinetic and Thermodynamic Characteristics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattacharyya, Souryadeep; Han, Rebecca; Kim, Wun -Gwi

Here, acid gases such as SO 2 and CO 2 are present in many environments in which the use of nanoporous metal-organic frameworks (MOFs) is envisaged. Among metal-organic frameworks, zeolitic imidazolate frameworks (ZIFs) have been extensively explored as membranes or adsorbents. However, there is little systematic knowledge of the effects of acid gas exposure on the structure of ZIFs, in particular the mechanistic aspects of ZIF degradation by acid gases as well as the effects of ZIF crystal topology and linker composition on their stability. Here we present a generalized and quantitative investigation of the kinetic and thermodynamic acid gasmore » stability of a diverse range of ZIF materials. The stability of 16 ZIFs (of SOD, RHO, ANA, and GME topologies) under different environments – humid air, liquid water, and acid gases CO 2 and SO 2 (dry, humid, and aqueous) – are investigated by a suite of experimental and computational methods. The kinetics of ZIF degradation under exposure to humid SO 2 is studied in detail, and effective rate constants for acid gas degradation of ZIFs are reported for the first time. Remarkably, the kinetics of degradation of the diverse ZIFs correlate strongly with the linker pKa and ZIF water adsorption in a manner contrary to that expected from previous predictions in the literature. Furthermore, we find that the material ZIF-71 (RHO topology) shows much higher stability relative to the other ZIFs in humid SO 2 and CO 2 environments.« less

Particle size studies to reveal crystallization mechanisms of the metal organic framework HKUST-1 during sonochemical synthesis.

PubMed

Armstrong, Mitchell R; Senthilnathan, Sethuraman; Balzer, Christopher J; Shan, Bohan; Chen, Liang; Mu, Bin

2017-01-01

Systematic studies of key operating parameters for the sonochemical synthesis of the metal organic framework (MOF) HKUST-1(also called CuBTC) were performed including reaction time, reactor volume, sonication amplitude, sonication tip size, solvent composition, and reactant concentrations analyzed through SEM particle size analysis. Trends in the particle size and size distributions show reproducible control of average particle sizes between 1 and 4μm. These results along with complementary studies in sonofragmentation and temperature control were conducted to compare these results to kinetic crystal growth models found in literature to develop a plausible hypothetical mechanism for ultrasound-assisted growth of metal-organic-frameworks composed of a competitive mechanism including constructive solid-on-solid (SOS) crystal growth and a deconstructive sonofragmentation. Copyright © 2016 Elsevier B.V. All rights reserved.
Quantifying fat, oil, and grease deposit formation kinetics.

PubMed

Iasmin, Mahbuba; Dean, Lisa O; Ducoste, Joel J

2016-01-01

Fat, oil, and grease (FOG) deposits formed in sanitary sewers are calcium-based saponified solids that are responsible for a significant number of nationwide sanitary sewer overflows (SSOs) across United States. In the current study, the kinetics of lab-based saponified solids were determined to understand the kinetics of FOG deposit formation in sewers for two types of fat (Canola and Beef Tallow) and two types of calcium sources (calcium chloride and calcium sulfate) under three pH (7 ± 0.5, 10 ± 0.5, and ≈14) and two temperature conditions (22 ± 0.5 and 45 ± 0.5 °C). The results of this study displayed quick reactions of a fraction of fats with calcium ions to form calcium based saponified solids. Results further showed that increased palmitic fatty acid content in source fats, the magnitude of the pH, and temperature significantly affect the FOG deposit formation and saponification rates. The experimental data of the kinetics were compared with two empirical models: a) Cotte saponification model and b) Foubert crystallization model and a mass-action based mechanistic model that included alkali driven hydrolysis of triglycerides. Results showed that the mass action based mechanistic model was able to predict changes in the rate of formation of saponified solids under the different experimental conditions compared to both empirical models. The mass-action based saponification model also revealed that the hydrolysis of Beef Tallow was slower compared to liquid Canola fat resulting in smaller quantities of saponified solids. This mechanistic saponification model, with its ability to track the saponified solids chemical precursors, may provide an initial framework to predict the spatial formation of FOG deposits in municipal sewers using system wide sewer collection modeling software. Copyright © 2015 Elsevier Ltd. All rights reserved.
Continuum mesoscopic framework for multiple interacting species and processes on multiple site types and/or crystallographic planes.

PubMed

Chatterjee, Abhijit; Vlachos, Dionisios G

2007-07-21

While recently derived continuum mesoscopic equations successfully bridge the gap between microscopic and macroscopic physics, so far they have been derived only for simple lattice models. In this paper, general deterministic continuum mesoscopic equations are derived rigorously via nonequilibrium statistical mechanics to account for multiple interacting surface species and multiple processes on multiple site types and/or different crystallographic planes. Adsorption, desorption, reaction, and surface diffusion are modeled. It is demonstrated that contrary to conventional phenomenological continuum models, microscopic physics, such as the interaction potential, determines the final form of the mesoscopic equation. Models of single component diffusion and binary diffusion of interacting particles on single-type site lattice and of single component diffusion on complex microporous materials' lattices consisting of two types of sites are derived, as illustrations of the mesoscopic framework. Simplification of the diffusion mesoscopic model illustrates the relation to phenomenological models, such as the Fickian and Maxwell-Stefan transport models. It is demonstrated that the mesoscopic equations are in good agreement with lattice kinetic Monte Carlo simulations for several prototype examples studied.
The What and Where of Adding Channel Noise to the Hodgkin-Huxley Equations

PubMed Central

Goldwyn, Joshua H.; Shea-Brown, Eric

2011-01-01

Conductance-based equations for electrically active cells form one of the most widely studied mathematical frameworks in computational biology. This framework, as expressed through a set of differential equations by Hodgkin and Huxley, synthesizes the impact of ionic currents on a cell's voltage—and the highly nonlinear impact of that voltage back on the currents themselves—into the rapid push and pull of the action potential. Later studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations or their counterparts. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the equations of Hodgkin-Huxley type. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic equations of Hodgkin-Huxley type as well as to more modern models of ion channel dynamics. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly MATLAB simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html. PMID:22125479
Kinetic modeling of cellulosic biomass to ethanol via simultaneous saccharification and fermentation: Part I. Accommodation of intermittent feeding and analysis of staged reactors.

PubMed

Shao, Xiongjun; Lynd, Lee; Wyman, Charles; Bakker, André

2009-01-01

The model of South et al. [South et al. (1995) Enzyme Microb Technol 17(9): 797-803] for simultaneous saccharification of fermentation of cellulosic biomass is extended and modified to accommodate intermittent feeding of substrate and enzyme, cascade reactor configurations, and to be more computationally efficient. A dynamic enzyme adsorption model is found to be much more computationally efficient than the equilibrium model used previously, thus increasing the feasibility of incorporating the kinetic model in a computational fluid dynamic framework in the future. For continuous or discretely fed reactors, it is necessary to use particle conversion in conversion-dependent hydrolysis rate laws rather than reactor conversion. Whereas reactor conversion decreases due to both reaction and exit of particles from the reactor, particle conversion decreases due to reaction only. Using the modified models, it is predicted that cellulose conversion increases with decreasing feeding frequency (feedings per residence time, f). A computationally efficient strategy for modeling cascade reactors involving a modified rate constant is shown to give equivalent results relative to an exhaustive approach considering the distribution of particles in each successive fermenter.
Modeling of electrical and mesoscopic circuits at quantum nanoscale from heat momentum operator

NASA Astrophysics Data System (ADS)

El-Nabulsi, Rami Ahmad

2018-04-01

We develop a new method to study electrical circuits at quantum nanoscale by introducing a heat momentum operator which reproduces quantum effects similar to those obtained in Suykens's nonlocal-in-time kinetic energy approach for the case of reversible motion. The series expansion of the heat momentum operator is similar to the momentum operator obtained in the framework of minimal length phenomenologies characterized by the deformation of Heisenberg algebra. The quantization of both LC and mesoscopic circuits revealed a number of motivating features like the emergence of a generalized uncertainty relation and a minimal charge similar to those obtained in the framework of minimal length theories. Additional features were obtained and discussed accordingly.
A thermostatted kinetic theory model for event-driven pedestrian dynamics

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-06-01

This paper is devoted to the modeling of the pedestrian dynamics by means of the thermostatted kinetic theory. Specifically the microscopic interactions among pedestrians and an external force field are modeled for simulating the evacuation of pedestrians from a metro station. The fundamentals of the stochastic game theory and the thermostatted kinetic theory are coupled for the derivation of a specific mathematical model which depicts the time evolution of the distribution of pedestrians at different exits of a metro station. The perturbation theory is employed in order to establish the stability analysis of the nonequilibrium stationary states in the case of a metro station consisting of two exits. A general sensitivity analysis on the initial conditions, the magnitude of the external force field and the number of exits is presented by means of numerical simulations which, in particular, show how the asymptotic distribution and the convergence time are affected by the presence of an external force field. The results show how, in evacuation conditions, the interaction dynamics among pedestrians can be negligible with respect to the external force. The important role of the thermostat term in allowing the reaching of the nonequilibrium stationary state is stressed out. Research perspectives are underlined at the end of paper, in particular for what concerns the derivation of frameworks that take into account the definition of local external actions and the introduction of the space and velocity dynamics.
Frontal Conversion and Uniformity in 3D Printing by Photopolymerisation

PubMed Central

Vitale, Alessandra; Cabral, João T.

2016-01-01

We investigate the impact of the non-uniform spatio-temporal conversion, intrinsic to photopolymerisation, in the context of light-driven 3D printing of polymers. The polymerisation kinetics of a series of model acrylate and thiol-ene systems, both neat and doped with a light-absorbing dye, is investigated experimentally and analysed according to a descriptive coarse-grained model for photopolymerisation. In particular, we focus on the relative kinetics of polymerisation with those of 3D printing, by comparing the evolution of the position of the conversion profile (zf) to the sequential displacement of the object stage (∆z). After quantifying the characteristic sigmoidal monomer-to-polymer conversion of the various systems, with a combination of patterning experiments, FT-IR mapping, and modelling, we compute representative regimes for which zf is smaller, commensurate with, or larger than ∆z. While non-monotonic conversion can be detrimental to 3D printing, for instance in causing differential shrinkage of inhomogeneity in material properties, we identify opportunities for facile fabrication of modulated materials in the z-direction (i.e., along the illuminated axis). Our simple framework and model, based on directly measured parameters, can thus be employed in photopolymerisation-based 3D printing, both in process optimisation and in the precise design of complex, internally stratified materials by coupling the z-stage displacement and frontal polymerisation kinetics. PMID:28773881
DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

PubMed Central

Baroukh, Caroline; Muñoz-Tamayo, Rafael; Steyer, Jean-Philippe; Bernard, Olivier

2014-01-01

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates. PMID:25105494
Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

PubMed

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.
Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

PubMed Central

Sing-Long, Carlos A.

2017-01-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618
Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

DOE PAGES

Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

2017-06-19

Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less
An energy landscape approach to protein aggregation

NASA Astrophysics Data System (ADS)

Buell, Alexander; Knowles, Tuomas

2012-02-01

Protein aggregation into ordered fibrillar structures is the hallmark of a class of diseases, the most prominent examples of which are Alzheimer's and Parkinson's disease. Recent results (e.g. Baldwin et al. J. Am. Chem. Soc. 2011) suggest that the aggregated state of a protein is in many cases thermodynamically more stable than the soluble state. Therefore the solubility of proteins in a cellular context appears to be to a large extent under kinetic control. Here, we first present a conceptual framework for the description of protein aggregation ( see AK Buell et al., Phys. Rev. Lett. 2010) that is an extension to the generally accepted energy landscape model for protein folding. Then we apply this model to analyse and interpret a large set of experimental data on the kinetics of protein aggregation, acquired mainly with a novel biosensing approach (see TPJK Knowles et al, Proc. Nat. Acad. Sc. 2007). We show how for example the effect of sequence modifications on the kinetics and thermodynamics of human lysozyme aggregation can be understood and quantified (see AK Buell et al., J. Am. Chem. Soc. 2011). These results have important implications for therapeutic strategies against protein aggregation disorders, in this case lysozyme systemic amyloidosis.
Estimating reaction rate coefficients within a travel-time modeling framework.

PubMed

Gong, R; Lu, C; Wu, W-M; Cheng, H; Gu, B; Watson, D; Jardine, P M; Brooks, S C; Criddle, C S; Kitanidis, P K; Luo, J

2011-01-01

A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transport over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.
Estimating Reaction Rate Coefficients Within a Travel-Time Modeling Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gong, R; Lu, C; Luo, Jian

A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transportmore » over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics.« less
An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Allison, E-mail: lewis.allison10@gmail.com; Smith, Ralph; Williams, Brian

For many simulation models, it can be prohibitively expensive or physically infeasible to obtain a complete set of experimental data to calibrate model parameters. In such cases, one can alternatively employ validated higher-fidelity codes to generate simulated data, which can be used to calibrate the lower-fidelity code. In this paper, we employ an information-theoretic framework to determine the reduction in parameter uncertainty that is obtained by evaluating the high-fidelity code at a specific set of design conditions. These conditions are chosen sequentially, based on the amount of information that they contribute to the low-fidelity model parameters. The goal is tomore » employ Bayesian experimental design techniques to minimize the number of high-fidelity code evaluations required to accurately calibrate the low-fidelity model. We illustrate the performance of this framework using heat and diffusion examples, a 1-D kinetic neutron diffusion equation, and a particle transport model, and include initial results from the integration of the high-fidelity thermal-hydraulics code Hydra-TH with a low-fidelity exponential model for the friction correlation factor.« less
Multiple Ion Binding Equilibria, Reaction Kinetics, and Thermodynamics in Dynamic Models of Biochemical Pathways

PubMed Central

Vinnakota, Kalyan C.; Wu, Fan; Kushmerick, Martin J.; Beard, Daniel A.

2009-01-01

The operation of biochemical systems in vivo and in vitro is strongly influenced by complex interactions between biochemical reactants and ions such as H+, Mg2+, K+, and Ca2+. These are important second messengers in metabolic and signaling pathways that directly influence the kinetics and thermodynamics of biochemical systems. Herein we describe the biophysical theory and computational methods to account for multiple ion binding to biochemical reactants and demonstrate the crucial effects of ion binding on biochemical reaction kinetics and thermodynamics. In simulations of realistic systems, the concentrations of these ions change with time due to dynamic buffering and competitive binding. In turn, the effective thermodynamic properties vary as functions of cation concentrations and important environmental variables such as temperature and overall ionic strength. Physically realistic simulations of biochemical systems require incorporating all of these phenomena into a coherent mathematical description. Several applications to physiological systems are demonstrated based on this coherent simulation framework. PMID:19216922
Advances in continuum kinetic and gyrokinetic simulations of turbulence on open-field line geometries

NASA Astrophysics Data System (ADS)

Hakim, Ammar; Shi, Eric; Juno, James; Bernard, Tess; Hammett, Greg

2017-10-01

For weakly collisional (or collisionless) plasmas, kinetic effects are required to capture the physics of micro-turbulence. We have implemented solvers for kinetic and gyrokinetic equations in the computational plasma physics framework, Gkeyll. We use a version of discontinuous Galerkin scheme that conserves energy exactly. Plasma sheaths are modeled with novel boundary conditions. Positivity of distribution functions is maintained via a reconstruction method, allowing robust simulations that continue to conserve energy even with positivity limiters. We have performed a large number of benchmarks, verifying the accuracy and robustness of our code. We demonstrate the application of our algorithm to two classes of problems (a) Vlasov-Maxwell simulations of turbulence in a magnetized plasma, applicable to space plasmas; (b) Gyrokinetic simulations of turbulence in open-field-line geometries, applicable to laboratory plasmas. Supported by the Max-Planck/Princeton Center for Plasma Physics, the SciDAC Center for the Study of Plasma Microturbulence, and DOE Contract DE-AC02-09CH11466.
Revisiting kinetic boundary conditions at the surface of fuel droplet hydrocarbons: An atomistic computational fluid dynamics simulation

PubMed Central

Nasiri, Rasoul

2016-01-01

The role of boundary conditions at the interface for both Boltzmann equation and the set of Navier-Stokes equations have been suggested to be important for studying of multiphase flows such as evaporation/condensation process which doesn’t always obey the equilibrium conditions. Here we present aspects of transition-state theory (TST) alongside with kinetic gas theory (KGT) relevant to the study of quasi-equilibrium interfacial phenomena and the equilibrium gas phase processes, respectively. A two-state mathematical model for long-chain hydrocarbons which have multi-structural specifications is introduced to clarify how kinetics and thermodynamics affect evaporation/condensation process at the surface of fuel droplet, liquid and gas phases and then show how experimental observations for a number of n-alkane may be reproduced using a hybrid framework TST and KGT with physically reasonable parameters controlling the interface, gas and liquid phases. The importance of internal activation dynamics at the surface of n-alkane droplets is established during the evaporation/condensation process. PMID:27215897
Model and system learners, optimal process constructors and kinetic theory-based goal-oriented design: A new paradigm in materials and processes informatics

NASA Astrophysics Data System (ADS)

Abisset-Chavanne, Emmanuelle; Duval, Jean Louis; Cueto, Elias; Chinesta, Francisco

2018-05-01

Traditionally, Simulation-Based Engineering Sciences (SBES) has relied on the use of static data inputs (model parameters, initial or boundary conditions, … obtained from adequate experiments) to perform simulations. A new paradigm in the field of Applied Sciences and Engineering has emerged in the last decade. Dynamic Data-Driven Application Systems [9, 10, 11, 12, 22] allow the linkage of simulation tools with measurement devices for real-time control of simulations and applications, entailing the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. It is in that context that traditional "digital-twins" are giving raise to a new generation of goal-oriented data-driven application systems, also known as "hybrid-twins", embracing models based on physics and models exclusively based on data adequately collected and assimilated for filling the gap between usual model predictions and measurements. Within this framework new methodologies based on model learners, machine learning and kinetic goal-oriented design are defining a new paradigm in materials, processes and systems engineering.

Revisiting gamma-ray burst afterglows with time-dependent parameters

NASA Astrophysics Data System (ADS)

Yang, Chao; Zou, Yuan-Chuan; Chen, Wei; Liao, Bin; Lei, Wei-Hua; Liu, Yu

2018-02-01

The relativistic external shock model of gamma-ray burst (GRB) afterglows has been established with five free parameters, i.e., the total kinetic energy E, the equipartition parameters for electrons {{ε }}{{e}} and for the magnetic field {{ε }}{{B}}, the number density of the environment n and the index of the power-law distribution of shocked electrons p. A lot of modified models have been constructed to consider the variety of GRB afterglows, such as: the wind medium environment by letting n change with radius, the energy injection model by letting kinetic energy change with time and so on. In this paper, by assuming all four parameters (except p) change with time, we obtain a set of formulas for the dynamics and radiation, which can be used as a reference for modeling GRB afterglows. Some interesting results are obtained. For example, in some spectral segments, the radiated flux density does not depend on the number density or the profile of the environment. As an application, through modeling the afterglow of GRB 060607A, we find that it can be interpreted in the framework of the time dependent parameter model within a reasonable range.
A statistical mechanical theory of proton transport kinetics in hydrogen-bonded networks based on population correlation functions with applications to acids and bases.

PubMed

Tuckerman, Mark E; Chandra, Amalendu; Marx, Dominik

2010-09-28

Extraction of relaxation times, lifetimes, and rates associated with the transport of topological charge defects in hydrogen-bonded networks from molecular dynamics simulations is a challenge because proton transfer reactions continually change the identity of the defect core. In this paper, we present a statistical mechanical theory that allows these quantities to be computed in an unbiased manner. The theory employs a set of suitably defined indicator or population functions for locating a defect structure and their associated correlation functions. These functions are then used to develop a chemical master equation framework from which the rates and lifetimes can be determined. Furthermore, we develop an integral equation formalism for connecting various types of population correlation functions and derive an iterative solution to the equation, which is given a graphical interpretation. The chemical master equation framework is applied to the problems of both hydronium and hydroxide transport in bulk water. For each case it is shown that the theory establishes direct links between the defect's dominant solvation structures, the kinetics of charge transfer, and the mechanism of structural diffusion. A detailed analysis is presented for aqueous hydroxide, examining both reorientational time scales and relaxation of the rotational anisotropy, which is correlated with recent experimental results for these quantities. Finally, for OH(-)(aq) it is demonstrated that the "dynamical hypercoordination mechanism" is consistent with available experimental data while other mechanistic proposals are shown to fail. As a means of going beyond the linear rate theory valid from short up to intermediate time scales, a fractional kinetic model is introduced in the Appendix in order to describe the nonexponential long-time behavior of time-correlation functions. Within the mathematical framework of fractional calculus the power law decay ∼t(-σ), where σ is a parameter of the model and depends on the dimensionality of the system, is obtained from Mittag-Leffler functions due to their long-time asymptotics, whereas (stretched) exponential behavior is found for short times.
Predicting trace organic compound attenuation by ozone oxidation: Development of indicator and surrogate models.

PubMed

Park, Minkyu; Anumol, Tarun; Daniels, Kevin D; Wu, Shimin; Ziska, Austin D; Snyder, Shane A

2017-08-01

Ozone oxidation has been demonstrated to be an effective treatment process for the attenuation of trace organic compounds (TOrCs); however, predicting TOrC attenuation by ozone processes is challenging in wastewaters. Since ozone is rapidly consumed, determining the exposure times of ozone and hydroxyl radical proves to be difficult. As direct potable reuse schemes continue to gain traction, there is an increasing need for the development of real-time monitoring strategies for TOrC abatement in ozone oxidation processes. Hence, this study is primarily aimed at developing indicator and surrogate models for the prediction of TOrC attenuation by ozone oxidation. To this end, the second-order kinetic equations with a second-phase R ct value (ratio of hydroxyl radical exposure to molecular ozone exposure) were used to calculate comparative kinetics of TOrC attenuation and the reduction of indicator and spectroscopic surrogate parameters, including UV absorbance at 254 nm (UVA 254 ) and total fluorescence (TF). The developed indicator model using meprobamate as an indicator compound and the surrogate models with UVA 254 and TF exhibited good predictive power for the attenuation of 13 kinetically distinct TOrCs in five filtered and unfiltered wastewater effluents (R 2 values > 0.8). This study is intended to help provide a guideline for the implementation of indicator/surrogate models for real-time monitoring of TOrC abatement with ozone processes and integrate them into a regulatory framework in water reuse. Copyright © 2017 Elsevier Ltd. All rights reserved.
Numerical investigation of non-perturbative kinetic effects of energetic particles on toroidicity-induced Alfvén eigenmodes in tokamaks and stellarators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slaby, Christoph; Könies, Axel; Kleiber, Ralf

2016-09-15

The resonant interaction of shear Alfvén waves with energetic particles is investigated numerically in tokamak and stellarator geometry using a non-perturbative MHD-kinetic hybrid approach. The focus lies on toroidicity-induced Alfvén eigenmodes (TAEs), which are most easily destabilized by a fast-particle population in fusion plasmas. While the background plasma is treated within the framework of an ideal-MHD theory, the drive of the fast particles, as well as Landau damping of the background plasma, is modelled using the drift-kinetic Vlasov equation without collisions. Building on analytical theory, a fast numerical tool, STAE-K, has been developed to solve the resulting eigenvalue problem usingmore » a Riccati shooting method. The code, which can be used for parameter scans, is applied to tokamaks and the stellarator Wendelstein 7-X. High energetic-ion pressure leads to large growth rates of the TAEs and to their conversion into kinetically modified TAEs and kinetic Alfvén waves via continuum interaction. To better understand the physics of this conversion mechanism, the connections between TAEs and the shear Alfvén wave continuum are examined. It is shown that, when energetic particles are present, the continuum deforms substantially and the TAE frequency can leave the continuum gap. The interaction of the TAE with the continuum leads to singularities in the eigenfunctions. To further advance the physical model and also to eliminate the MHD continuum together with the singularities in the eigenfunctions, a fourth-order term connected to radiative damping has been included. The radiative damping term is connected to non-ideal effects of the bulk plasma and introduces higher-order derivatives to the model. Thus, it has the potential to substantially change the nature of the solution. For the first time, the fast-particle drive, Landau damping, continuum damping, and radiative damping have been modelled together in tokamak- as well as in stellarator geometry.« less
Continuum theory of fibrous tissue damage mechanics using bond kinetics: application to cartilage tissue engineering.

PubMed

Nims, Robert J; Durney, Krista M; Cigan, Alexander D; Dusséaux, Antoine; Hung, Clark T; Ateshian, Gerard A

2016-02-06

This study presents a damage mechanics framework that employs observable state variables to describe damage in isotropic or anisotropic fibrous tissues. In this mixture theory framework, damage is tracked by the mass fraction of bonds that have broken. Anisotropic damage is subsumed in the assumption that multiple bond species may coexist in a material, each having its own damage behaviour. This approach recovers the classical damage mechanics formulation for isotropic materials, but does not appeal to a tensorial damage measure for anisotropic materials. In contrast with the classical approach, the use of observable state variables for damage allows direct comparison of model predictions to experimental damage measures, such as biochemical assays or Raman spectroscopy. Investigations of damage in discrete fibre distributions demonstrate that the resilience to damage increases with the number of fibre bundles; idealizing fibrous tissues using continuous fibre distribution models precludes the modelling of damage. This damage framework was used to test and validate the hypothesis that growth of cartilage constructs can lead to damage of the synthesized collagen matrix due to excessive swelling caused by synthesized glycosaminoglycans. Therefore, alternative strategies must be implemented in tissue engineering studies to prevent collagen damage during the growth process.
Continuum theory of fibrous tissue damage mechanics using bond kinetics: application to cartilage tissue engineering

PubMed Central

Nims, Robert J.; Durney, Krista M.; Cigan, Alexander D.; Hung, Clark T.; Ateshian, Gerard A.

2016-01-01

This study presents a damage mechanics framework that employs observable state variables to describe damage in isotropic or anisotropic fibrous tissues. In this mixture theory framework, damage is tracked by the mass fraction of bonds that have broken. Anisotropic damage is subsumed in the assumption that multiple bond species may coexist in a material, each having its own damage behaviour. This approach recovers the classical damage mechanics formulation for isotropic materials, but does not appeal to a tensorial damage measure for anisotropic materials. In contrast with the classical approach, the use of observable state variables for damage allows direct comparison of model predictions to experimental damage measures, such as biochemical assays or Raman spectroscopy. Investigations of damage in discrete fibre distributions demonstrate that the resilience to damage increases with the number of fibre bundles; idealizing fibrous tissues using continuous fibre distribution models precludes the modelling of damage. This damage framework was used to test and validate the hypothesis that growth of cartilage constructs can lead to damage of the synthesized collagen matrix due to excessive swelling caused by synthesized glycosaminoglycans. Therefore, alternative strategies must be implemented in tissue engineering studies to prevent collagen damage during the growth process. PMID:26855751
Power-law spatial dispersion from fractional Liouville equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tarasov, Vasily E.

2013-10-15

A microscopic model in the framework of fractional kinetics to describe spatial dispersion of power-law type is suggested. The Liouville equation with the Caputo fractional derivatives is used to obtain the power-law dependence of the absolute permittivity on the wave vector. The fractional differential equations for electrostatic potential in the media with power-law spatial dispersion are derived. The particular solutions of these equations for the electric potential of point charge in this media are considered.
Interface collisions

NASA Astrophysics Data System (ADS)

Aarão Reis, F. D. A.; Pierre-Louis, O.

2018-04-01

We provide a theoretical framework to analyze the properties of frontal collisions of two growing interfaces considering different short-range interactions between them. Due to their roughness, the collision events spread in time and form rough domain boundaries, which defines collision interfaces in time and space. We show that statistical properties of such interfaces depend on the kinetics of the growing interfaces before collision, but are independent of the details of their interaction and of their fluctuations during the collision. Those properties exhibit dynamic scaling with exponents related to the growth kinetics, but their distributions may be nonuniversal. Our results are supported by simulations of lattice models with irreversible dynamics and local interactions. Relations to first passage processes are discussed and a possible application to grain-boundary formation in two-dimensional materials is suggested.
Hydrodynamic effects of kinetic power extraction by in-stream tidal turbines

NASA Astrophysics Data System (ADS)

Polagye, Brian L.

The hydrodynamic effects of extracting kinetic power from tidal streams presents unique challenges to the development of in-stream tidal power. In-stream tidal turbines superficially resemble wind turbines and extract kinetic power from the ebb and flood of strong tidal currents. Extraction increases the resistance to flow, leading to changes in tidal range, transport, mixing, and the kinetic resource itself. These far-field changes have environmental, social, and economic implications that must be understood to develop the in-stream resource. This dissertation describes the development of a one-dimensional numerical channel model and its application to the study of these effects. The model is applied to determine the roles played by site geometry, network topology, tidal regime, and device dynamics. A comparison is also made between theoretical and modeled predictions for the maximum amount of power which could be extracted from a tidal energy site. The model is extended to a simulation of kinetic power extraction from Puget Sound, Washington. In general, extracting tidal energy will have a number of far-field effects, in proportion to the level of power extraction. At the theoretical limit, these effects can be very significant (e.g., 50% reduction in transport), but are predicted to be immeasurably small for pilot-scale projects. Depending on the specifics of the site, far-field effects may either augment or reduce the existing tidal regime. Changes to the tide, in particular, have significant spatial variability. Since tidal streams are generally subcritical, effects are felt throughout the estuary, not just at the site of extraction. The one dimensional numerical modeling is supported by a robust theory for predicting the performance characteristics of in-stream devices. The far-field effects of tidal power depend on the total power dissipated by turbines, rather than the power extracted. When the low-speed wake downstream of a turbine mixes with the free-stream, power is lost, such that the total power dissipated by the turbine is significantly greater than the power extracted. This dissertation concludes with a framework for three-dimensional numerical modeling of near-field extraction effects.
Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.
Neutrino-electron scattering: general constraints on Z ' and dark photon models

NASA Astrophysics Data System (ADS)

Lindner, Manfred; Queiroz, Farinaldo S.; Rodejohann, Werner; Xu, Xun-Jie

2018-05-01

We study the framework of U(1) X models with kinetic mixing and/or mass mixing terms. We give general and exact analytic formulas of fermion gauge interactions and the cross sections of neutrino-electron scattering in such models. Then we derive limits on a variety of U(1) X models that induce new physics contributions to neutrino-electron scattering, taking into account interference between the new physics and Standard Model contributions. Data from TEXONO, CHARM-II and GEMMA are analyzed and shown to be complementary to each other to provide the most restrictive bounds on masses of the new vector bosons. In particular, we demonstrate the validity of our results to dark photon-like as well as light Z ' models.
Traveltime-based descriptions of transport and mixing in heterogeneous domains

NASA Astrophysics Data System (ADS)

Luo, Jian; Cirpka, Olaf A.

2008-09-01

Modeling mixing-controlled reactive transport using traditional spatial discretization of the domain requires identifying the spatial distributions of hydraulic and reactive parameters including mixing-related quantities such as dispersivities and kinetic mass transfer coefficients. In most applications, breakthrough curves (BTCs) of conservative and reactive compounds are measured at only a few locations and spatially explicit models are calibrated by matching these BTCs. A common difficulty in such applications is that the individual BTCs differ too strongly to justify the assumption of spatial homogeneity, whereas the number of observation points is too small to identify the spatial distribution of the decisive parameters. The key objective of the current study is to characterize physical transport by the analysis of conservative tracer BTCs and predict the macroscopic BTCs of compounds that react upon mixing from the interpretation of conservative tracer BTCs and reactive parameters determined in the laboratory. We do this in the framework of traveltime-based transport models which do not require spatially explicit, costly aquifer characterization. By considering BTCs of a conservative tracer measured on different scales, one can distinguish between mixing, which is a prerequisite for reactions, and spreading, which per se does not foster reactions. In the traveltime-based framework, the BTC of a solute crossing an observation plane, or ending in a well, is interpreted as the weighted average of concentrations in an ensemble of non-interacting streamtubes, each of which is characterized by a distinct traveltime value. Mixing is described by longitudinal dispersion and/or kinetic mass transfer along individual streamtubes, whereas spreading is characterized by the distribution of traveltimes, which also determines the weights associated with each stream tube. Key issues in using the traveltime-based framework include the description of mixing mechanisms and the estimation of the traveltime distribution. In this work, we account for both apparent longitudinal dispersion and kinetic mass transfer as mixing mechanisms, thus generalizing the stochastic-convective model with or without inter-phase mass transfer and the advective-dispersive streamtube model. We present a nonparametric approach of determining the traveltime distribution, given a BTC integrated over an observation plane and estimated mixing parameters. The latter approach is superior to fitting parametric models in cases wherein the true traveltime distribution exhibits multiple peaks or long tails. It is demonstrated that there is freedom for the combinations of mixing parameters and traveltime distributions to fit conservative BTCs and describe the tailing. A reactive transport case of a dual Michaelis-Menten problem demonstrates that the reactive mixing introduced by local dispersion and mass transfer may be described by apparent mean mass transfer with coefficients evaluated by local BTCs.
Overview of the ArbiTER edge plasma eigenvalue code

NASA Astrophysics Data System (ADS)

Baver, Derek; Myra, James; Umansky, Maxim

2011-10-01

The Arbitrary Topology Equation Reader, or ArbiTER, is a flexible eigenvalue solver that is currently under development for plasma physics applications. The ArbiTER code builds on the equation parser framework of the existing 2DX code, extending it to include a topology parser. This will give the code the capability to model problems with complicated geometries (such as multiple X-points and scrape-off layers) or model equations with arbitrary numbers of dimensions (e.g. for kinetic analysis). In the equation parser framework, model equations are not included in the program's source code. Instead, an input file contains instructions for building a matrix from profile functions and elementary differential operators. The program then executes these instructions in a sequential manner. These instructions may also be translated into analytic form, thus giving the code transparency as well as flexibility. We will present an overview of how the ArbiTER code is to work, as well as preliminary results from early versions of this code. Work supported by the U.S. DOE.
Nonextensive kinetic theory and H-theorem in general relativity

NASA Astrophysics Data System (ADS)

Santos, A. P.; Silva, R.; Alcaniz, J. S.; Lima, J. A. S.

2017-11-01

The nonextensive kinetic theory for degenerate quantum gases is discussed in the general relativistic framework. By incorporating nonadditive modifications in the collisional term of the relativistic Boltzmann equation and entropy current, it is shown that Tsallis entropic framework satisfies a H-theorem in the presence of gravitational fields. Consistency with the 2nd law of thermodynamics is obtained only whether the entropic q-parameter lies in the interval q ∈ [ 0 , 2 ] . As occurs in the absence of gravitational fields, it is also proved that the local collisional equilibrium is described by the extended Bose-Einstein (Fermi-Dirac) q-distributions.
Reaction rates for mesoscopic reaction-diffusion kinetics

DOE PAGES

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2015-02-23

The mesoscopic reaction-diffusion master equation (RDME) is a popular modeling framework frequently applied to stochastic reaction-diffusion kinetics in systems biology. The RDME is derived from assumptions about the underlying physical properties of the system, and it may produce unphysical results for models where those assumptions fail. In that case, other more comprehensive models are better suited, such as hard-sphere Brownian dynamics (BD). Although the RDME is a model in its own right, and not inferred from any specific microscale model, it proves useful to attempt to approximate a microscale model by a specific choice of mesoscopic reaction rates. In thismore » paper we derive mesoscopic scale-dependent reaction rates by matching certain statistics of the RDME solution to statistics of the solution of a widely used microscopic BD model: the Smoluchowski model with a Robin boundary condition at the reaction radius of two molecules. We also establish fundamental limits on the range of mesh resolutions for which this approach yields accurate results and show both theoretically and in numerical examples that as we approach the lower fundamental limit, the mesoscopic dynamics approach the microscopic dynamics. Finally, we show that for mesh sizes below the fundamental lower limit, results are less accurate. Thus, the lower limit determines the mesh size for which we obtain the most accurate results.« less
Reaction rates for mesoscopic reaction-diffusion kinetics

PubMed Central

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2016-01-01

The mesoscopic reaction-diffusion master equation (RDME) is a popular modeling framework frequently applied to stochastic reaction-diffusion kinetics in systems biology. The RDME is derived from assumptions about the underlying physical properties of the system, and it may produce unphysical results for models where those assumptions fail. In that case, other more comprehensive models are better suited, such as hard-sphere Brownian dynamics (BD). Although the RDME is a model in its own right, and not inferred from any specific microscale model, it proves useful to attempt to approximate a microscale model by a specific choice of mesoscopic reaction rates. In this paper we derive mesoscopic scale-dependent reaction rates by matching certain statistics of the RDME solution to statistics of the solution of a widely used microscopic BD model: the Smoluchowski model with a Robin boundary condition at the reaction radius of two molecules. We also establish fundamental limits on the range of mesh resolutions for which this approach yields accurate results and show both theoretically and in numerical examples that as we approach the lower fundamental limit, the mesoscopic dynamics approach the microscopic dynamics. We show that for mesh sizes below the fundamental lower limit, results are less accurate. Thus, the lower limit determines the mesh size for which we obtain the most accurate results. PMID:25768640
Linking Thermodynamics to Pollutant Reduction Kinetics by Fe2+ Bound to Iron Oxides.

PubMed

Stewart, Sydney M; Hofstetter, Thomas B; Joshi, Prachi; Gorski, Christopher A

2018-05-15

Numerous studies have reported that pollutant reduction rates by ferrous iron (Fe 2+ ) are substantially enhanced in the presence of an iron (oxyhydr)oxide mineral. Developing a thermodynamic framework to explain this phenomenon has been historically difficult due to challenges in quantifying reduction potential ( E H ) values for oxide-bound Fe 2+ species. Recently, our group demonstrated that E H values for hematite- and goethite-bound Fe 2+ can be accurately calculated using Gibbs free energy of formation values. Here, we tested if calculated E H values for oxide-bound Fe 2+ could be used to develop a free energy relationship capable of describing variations in reduction rate constants of substituted nitrobenzenes, a class of model pollutants that contain reducible aromatic nitro groups, using data collected here and compiled from the literature. All the data could be described by a single linear relationship between the logarithms of the surface-area-normalized rate constant ( k SA ) values and E H and pH values [log( k SA ) = - E H /0.059 V - pH + 3.42]. This framework provides mechanistic insights into how the thermodynamic favorability of electron transfer from oxide-bound Fe 2+ relates to redox reaction kinetics.
Transition path theory analysis of c-Src kinase activation

PubMed Central

Meng, Yilin; Shukla, Diwakar; Pande, Vijay S.; Roux, Benoît

2016-01-01

Nonreceptor tyrosine kinases of the Src family are large multidomain allosteric proteins that are crucial to cellular signaling pathways. In a previous study, we generated a Markov state model (MSM) to simulate the activation of c-Src catalytic domain, used as a prototypical tyrosine kinase. The long-time kinetics of transition predicted by the MSM was in agreement with experimental observations. In the present study, we apply the framework of transition path theory (TPT) to the previously constructed MSM to characterize the main features of the activation pathway. The analysis indicates that the activating transition, in which the activation loop first opens up followed by an inward rotation of the αC-helix, takes place via a dense set of intermediate microstates distributed within a fairly broad “transition tube” in a multidimensional conformational subspace connecting the two end-point conformations. Multiple microstates with negligible equilibrium probabilities carry a large transition flux associated with the activating transition, which explains why extensive conformational sampling is necessary to accurately determine the kinetics of activation. Our results suggest that the combination of MSM with TPT provides an effective framework to represent conformational transitions in complex biomolecular systems. PMID:27482115
A stochastic differential equation model of diurnal cortisol patterns

NASA Technical Reports Server (NTRS)

Brown, E. N.; Meehan, P. M.; Dempster, A. P.

2001-01-01

Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.
Uncertainty Propagation in OMFIT

NASA Astrophysics Data System (ADS)

Smith, Sterling; Meneghini, Orso; Sung, Choongki

2017-10-01

A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.

Progress in Studying Scintillator Proportionality: Phenomenological Model

NASA Astrophysics Data System (ADS)

Bizarri, G.; Cherepy, N. J.; Choong, W. S.; Hull, G.; Moses, W. W.; Payne, S. A.; Singh, J.; Valentine, J. D.; Vasilev, A. N.; Williams, R. T.

2009-08-01

We present a model to describe the origin of non-proportional dependence of scintillator light yield on the energy of an ionizing particle. The non-proportionality is discussed in terms of energy relaxation channels and their linear and non-linear dependences on the deposited energy. In this approach, the scintillation response is described as a function of the deposited energy deposition and the kinetic rates of each relaxation channel. This mathematical framework allows both a qualitative interpretation and a quantitative fitting representation of scintillation non-proportionality response as function of kinetic rates. This method was successfully applied to thallium doped sodium iodide measured with SLYNCI, a new facility using the Compton coincidence technique. Finally, attention is given to the physical meaning of the dominant relaxation channels, and to the potential causes responsible for the scintillation non-proportionality. We find that thallium doped sodium iodide behaves as if non-proportionality is due to competition between radiative recombinations and non-radiative Auger processes.
Freed by interaction kinetic states in the Harper model

NASA Astrophysics Data System (ADS)

Frahm, Klaus M.; Shepelyansky, Dima L.

2015-12-01

We study the problem of two interacting particles in a one-dimensional quasiperiodic lattice of the Harper model. We show that a short or long range interaction between particles leads to emergence of delocalized pairs in the non-interacting localized phase. The properties of these freed by interaction kinetic states (FIKS) are analyzed numerically including the advanced Arnoldi method. We find that the number of sites populated by FIKS pairs grows algebraically with the system size with the maximal exponent b = 1, up to a largest lattice size N = 10 946 reached in our numerical simulations, thus corresponding to a complete delocalization of pairs. For delocalized FIKS pairs the spectral properties of such quasiperiodic operators represent a deep mathematical problem. We argue that FIKS pairs can be detected in the framework of recent cold atom experiments [M. Schreiber et al., Science 349, 842 (2015)] by a simple setup modification. We also discuss possible implications of FIKS pairs for electron transport in the regime of charge-density wave and high T c superconductivity.
Fibre Break Failure Processes in Unidirectional Composites. Part 2: Failure and Critical Damage State Induced by Sustained Tensile Loading

NASA Astrophysics Data System (ADS)

Thionnet, A.; Chou, H. Y.; Bunsell, A.

2015-04-01

The purpose of these three papers is not to just revisit the modelling of unidirectional composites. It is to provide a robust framework based on physical processes that can be used to optimise the design and long term reliability of internally pressurised filament wound structures. The model presented in Part 1 for the case of monotonically loaded unidirectional composites is further developed to consider the effects of the viscoelastic nature of the matrix in determining the kinetics of fibre breaks under slow or sustained loading. It is shown that the relaxation of the matrix around fibre breaks leads to locally increasing loads on neighbouring fibres and in some cases their delayed failure. Although ultimate failure is similar to the elastic case in that clusters of fibre breaks ultimately control composite failure the kinetics of their development varies significantly from the elastic case. Failure loads have been shown to reduce when loading rates are lowered.
Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems

NASA Astrophysics Data System (ADS)

Flenner, Elijah; Janosi, Lorant; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan

2012-03-01

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Here we formulate two computer simulation methods: (1) a kinetic Monte Carlo (KMC) and (2) a cellular particle dynamics (CPD) method, which are capable of describing and predicting the shape evolution in time of three-dimensional multicellular systems during their biomechanical relaxation. Our work is motivated by the need of developing quantitative methods for optimizing postprinting structure formation in bioprinting-assisted tissue engineering. The KMC and CPD model parameters are determined and calibrated by using an original computational-theoretical-experimental framework applied to the fusion of two spherical cell aggregates. The two methods are used to predict the (1) formation of a toroidal structure through fusion of spherical aggregates and (2) cell sorting within an aggregate formed by two types of cells with different adhesivities.
Emergence of ion channel modal gating from independent subunit kinetics.

PubMed

Bicknell, Brendan A; Goodhill, Geoffrey J

2016-09-06

Many ion channels exhibit a slow stochastic switching between distinct modes of gating activity. This feature of channel behavior has pronounced implications for the dynamics of ionic currents and the signaling pathways that they regulate. A canonical example is the inositol 1,4,5-trisphosphate receptor (IP3R) channel, whose regulation of intracellular Ca(2+) concentration is essential for numerous cellular processes. However, the underlying biophysical mechanisms that give rise to modal gating in this and most other channels remain unknown. Although ion channels are composed of protein subunits, previous mathematical models of modal gating are coarse grained at the level of whole-channel states, limiting further dialogue between theory and experiment. Here we propose an origin for modal gating, by modeling the kinetics of ligand binding and conformational change in the IP3R at the subunit level. We find good agreement with experimental data over a wide range of ligand concentrations, accounting for equilibrium channel properties, transient responses to changing ligand conditions, and modal gating statistics. We show how this can be understood within a simple analytical framework and confirm our results with stochastic simulations. The model assumes that channel subunits are independent, demonstrating that cooperative binding or concerted conformational changes are not required for modal gating. Moreover, the model embodies a generally applicable principle: If a timescale separation exists in the kinetics of individual subunits, then modal gating can arise as an emergent property of channel behavior.
Epidermal Homeostasis and Radiation Responses in a Multiscale Tissue Modeling Framework

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2013-01-01

The surface of skin is lined with several thin layers of epithelial cells that are maintained throughout life time by a small population of stem cells. High dose radiation exposures could injure and deplete the underlying proliferative cells and induce cutaneous radiation syndrome. In this work we propose a multiscale computational model for skin epidermal dynamics that links phenomena occurring at the subcellular, cellular, and tissue levels of organization, to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis. Incorporating experimentally measured histological and cell kinetic parameters, we obtain results of population kinetics and proliferation indexes comparable to observations in unirradiated and acutely irradiated swine experiments. At the sub-cellular level, several recently published Wnt signaling controlled cell-cycle models are applied and the roles of key components and parameters are analyzed. Based on our simulation results, we demonstrate that a moderate increase of proliferation rate for the survival proliferative cells is sufficient to fully repopulate the area denuded by high dose radiation, as long as the integrity of underlying basement membrane is maintained. Our work highlights the importance of considering proliferation kinetics as well as the spatial organization of tissues when conducting in vivo investigations of radiation responses. This integrated model allow us to test the validity of several basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and enhance our understanding of the pathophysiological effects of ionizing radiation on skin.
Rise time of voltage pulses in NbN superconducting single photon detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smirnov, K. V.; CJSC “Superconducting Nanotechnology”; National Research University Higher School of Economics, Moscow Institute of Electronics and Mathematics, 34 Tallinskaya St., 109028 Moscow

2016-08-01

We have found experimentally that the rise time of voltage pulse in NbN superconducting single photon detectors increases nonlinearly with increasing the length of the detector L. The effect is connected with dependence of resistance of the detector R{sub n}, which appears after photon absorption, on its kinetic inductance L{sub k} and, hence, on the length of the detector. This conclusion is confirmed by our calculations in the framework of two temperature model.
Hyperon polarization in heavy-ion collisions and holographic gravitational anomaly

NASA Astrophysics Data System (ADS)

Baznat, Mircea; Gudima, Konstantin; Sorin, Alexander; Teryaev, Oleg

2018-04-01

We study the energy dependence of global polarization of Λ hyperons in peripheral Au-Au collisions. We combine the calculation of vorticity and strange chemical potential in the framework of the kinetic quark-gluon-string model with the anomalous mechanism related to the axial vortical effect. We pay special attention to the temperature-dependent contribution related to the holographic gravitational anomaly and find that the preliminary data from the BNL Relativistic Heavy Ion Collider are compatible with its suppression discovered earlier in lattice calculations.
Drying process optimization for an API solvate using heat transfer model of an agitated filter dryer.

PubMed

Nere, Nandkishor K; Allen, Kimberley C; Marek, James C; Bordawekar, Shailendra V

2012-10-01

Drying an early stage active pharmaceutical ingredient candidate required excessively long cycle times in a pilot plant agitated filter dryer. The key to faster drying is to ensure sufficient heat transfer and minimize mass transfer limitations. Designing the right mixing protocol is of utmost importance to achieve efficient heat transfer. To this order, a composite model was developed for the removal of bound solvent that incorporates models for heat transfer and desolvation kinetics. The proposed heat transfer model differs from previously reported models in two respects: it accounts for the effects of a gas gap between the vessel wall and solids on the overall heat transfer coefficient, and headspace pressure on the mean free path length of the inert gas and thereby on the heat transfer between the vessel wall and the first layer of solids. A computational methodology was developed incorporating the effects of mixing and headspace pressure to simulate the drying profile using a modified model framework within the Dynochem software. A dryer operational protocol was designed based on the desolvation kinetics, thermal stability studies of wet and dry cake, and the understanding gained through model simulations, resulting in a multifold reduction in drying time. Copyright © 2012 Wiley-Liss, Inc.
A new predictive multi-zone model for HCCI engine combustion

DOE PAGES

Bissoli, Mattia; Frassoldati, Alessio; Cuoci, Alberto; ...

2016-06-30

Here, this work introduces a new predictive multi-zone model for the description of combustion in Homogeneous Charge Compression Ignition (HCCI) engines. The model exploits the existing OpenSMOKE++ computational suite to handle detailed kinetic mechanisms, providing reliable predictions of the in-cylinder auto-ignition processes. All the elements with a significant impact on the combustion performances and emissions, like turbulence, heat and mass exchanges, crevices, residual burned gases, thermal and feed stratification are taken into account. Compared to other computational approaches, this model improves the description of mixture stratification phenomena by coupling a wall heat transfer model derived from CFD application with amore » proper turbulence model. Furthermore, the calibration of this multi-zone model requires only three parameters, which can be derived from a non-reactive CFD simulation: these adaptive variables depend only on the engine geometry and remain fixed across a wide range of operating conditions, allowing the prediction of auto-ignition, pressure traces and pollutants. This computational framework enables the use of detail kinetic mechanisms, as well as Rate of Production Analysis (RoPA) and Sensitivity Analysis (SA) to investigate the complex chemistry involved in the auto-ignition and the pollutants formation processes. In the final sections of the paper, these capabilities are demonstrated through the comparison with experimental data.« less
Multi-scale genetic dynamic modelling I : an algorithm to compute generators.

PubMed

Kirkilionis, Markus; Janus, Ulrich; Sbano, Luca

2011-09-01

We present a new approach or framework to model dynamic regulatory genetic activity. The framework is using a multi-scale analysis based upon generic assumptions on the relative time scales attached to the different transitions of molecular states defining the genetic system. At micro-level such systems are regulated by the interaction of two kinds of molecular players: macro-molecules like DNA or polymerases, and smaller molecules acting as transcription factors. The proposed genetic model then represents the larger less abundant molecules with a finite discrete state space, for example describing different conformations of these molecules. This is in contrast to the representations of the transcription factors which are-like in classical reaction kinetics-represented by their particle number only. We illustrate the method by considering the genetic activity associated to certain configurations of interacting genes that are fundamental to modelling (synthetic) genetic clocks. A largely unknown question is how different molecular details incorporated via this more realistic modelling approach lead to different macroscopic regulatory genetic models which dynamical behaviour might-in general-be different for different model choices. The theory will be applied to a real synthetic clock in a second accompanying article (Kirkilioniset al., Theory Biosci, 2011).
Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions

PubMed Central

Meyer, Andrew J.; Eskinazi, Ilan; Jackson, Jennifer N.; Rao, Anil V.; Patten, Carolynn; Fregly, Benjamin J.

2016-01-01

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject’s self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot–ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject’s walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject’s walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject’s walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations. PMID:27790612
Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE PAGES

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting; ...

2018-03-28

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less
Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less
SPH simulations of WBC adhesion to the endothelium: the role of haemodynamics and endothelial binding kinetics.

PubMed

Gholami, Babak; Comerford, Andrew; Ellero, Marco

2015-11-01

A multiscale Lagrangian particle solver introduced in our previous work is extended to model physiologically realistic near-wall cell dynamics. Three-dimensional simulation of particle trajectories is combined with realistic receptor-ligand adhesion behaviour to cover full cell interactions in the vicinity of the endothelium. The selected stochastic adhesion model, which is based on a Monte Carlo acceptance-rejection method, fits in our Lagrangian framework and does not compromise performance. Additionally, appropriate inflow/outflow boundary conditions are implemented for our SPH solver to enable realistic pulsatile flow simulation. The model is tested against in-vitro data from a 3D geometry with a stenosis and sudden expansion. In both steady and pulsatile flow conditions, results show close agreement with the experimental ones. Furthermore we demonstrate, in agreement with experimental observations, that haemodynamics alone does not account for adhesion of white blood cells, in this case U937 monocytic human cells. Our findings suggest that the current framework is fully capable of modelling cell dynamics in large arteries in a realistic and efficient manner.
Open quantum system approach to the modeling of spin recombination reactions.

PubMed

Tiersch, M; Steiner, U E; Popescu, S; Briegel, H J

2012-04-26

In theories of spin-dependent radical pair reactions, the time evolution of the radical pair, including the effect of the chemical kinetics, is described by a master equation in the Liouville formalism. For the description of the chemical kinetics, a number of possible reaction operators have been formulated in the literature. In this work, we present a framework that allows for a unified description of the various proposed mechanisms and the forms of reaction operators for the spin-selective recombination processes. On the basis of the concept that master equations can be derived from a microscopic description of the spin system interacting with external degrees of freedom, it is possible to gain insight into the underlying microscopic processes and develop a systematic approach toward determining the specific form of the reaction operator in concrete scenarios.
A quasilinear kinetic model for solar wind electrons and protons instabilities

NASA Astrophysics Data System (ADS)

Sarfraz, M.; Yoon, P. H.

2017-12-01

In situ measurements confirm the anisotropic behavior in temperatures of solar wind species. These anisotropies associated with charge particles are observed to be relaxed. In collionless limit, kinetic instabilities play a significant role to reshape particles distribution. The linear analysis results are encapsulated in inverse relationship between anisotropy and plasma beta based observations fittings techniques, simulations methods, or solution of linearized Vlasov equation. Here amacroscopic quasilinear technique is adopted to confirm inverse relationship through solutions of set of self-consistent kinetic equations. Firstly, for a homogeneous and non-collisional medium, quasilinear kinetic model is employed to display asymptotic variations of core and halo electrons temperatures and saturations of wave energy densities for electromagnetic electron cyclotron (EMEC) instability sourced by, T⊥}>T{∥ . It is shown that, in (β ∥ , T⊥}/T{∥ ) phase space, the saturations stages of anisotropies associated with core and halo electrons lined up on their respective marginal stability curves. Secondly, for case of electrons firehose instability ignited by excessive parallel temperature i.e T⊥}>T{∥ , both electrons and protons are allowed to dynamically evolve in time. It is also observed that, the trajectories of protons and electrons at saturation stages in phase space of anisotropy and plasma beta correspond to proton cyclotron and firehose marginal stability curves, respectively. Next, the outstanding issue that most of observed proton data resides in nearly isotropic state in phase space is interpreted. Here, in quasilinear frame-work of inhomogeneous solar wind system, a set of self-consistent quasilinear equations is formulated to show a dynamical variations of temperatures with spatial distributions. On choice of different initial parameters, it is shown that, interplay of electron and proton instabilities provides an counter-balancing force to slow down the protons away from marginal stability states. As we are dealing both, protons and electrons for radially expanding solar wind plasma, our present approach may eventually be incorporated in global-kinetic models of the solar wind species.
Quantification of in vivo metabolic kinetics of hyperpolarized pyruvate in rat kidneys using dynamic 13C MRSI.

PubMed

Xu, Tao; Mayer, Dirk; Gu, Meng; Yen, Yi-Fen; Josan, Sonal; Tropp, James; Pfefferbaum, Adolf; Hurd, Ralph; Spielman, Daniel

2011-10-01

With signal-to-noise ratio enhancements on the order of 10,000-fold, hyperpolarized MRSI of metabolically active substrates allows the study of both the injected substrate and downstream metabolic products in vivo. Although hyperpolarized [1-(13)C]pyruvate, in particular, has been used to demonstrate metabolic activities in various animal models, robust quantification and metabolic modeling remain important areas of investigation. Enzyme saturation effects are routinely seen with commonly used doses of hyperpolarized [1-(13)C]pyruvate; however, most metrics proposed to date, including metabolite ratios, time-to-peak of metabolic products and single exchange rate constants, fail to capture these saturation effects. In addition, the widely used small-flip-angle excitation approach does not correctly model the inflow of fresh downstream metabolites generated proximal to the target slice, which is often a significant factor in vivo. In this work, we developed an efficient quantification framework employing a spiral-based dynamic spectroscopic imaging approach. The approach overcomes the aforementioned limitations and demonstrates that the in vivo (13)C labeling of lactate and alanine after a bolus injection of [1-(13)C]pyruvate is well approximated by saturatable kinetics, which can be mathematically modeled using a Michaelis-Menten-like formulation, with the resulting estimated apparent maximal reaction velocity V(max) and apparent Michaelis constant K(M) being unbiased with respect to critical experimental parameters, including the substrate dose, bolus shape and duration. Although the proposed saturatable model has a similar mathematical formulation to the original Michaelis-Menten kinetics, it is conceptually different. In this study, we focus on the (13)C labeling of lactate and alanine and do not differentiate the labeling mechanism (net flux or isotopic exchange) or the respective contribution of various factors (organ perfusion rate, substrate transport kinetics, enzyme activities and the size of the unlabeled lactate and alanine pools) to the labeling process. Copyright © 2011 John Wiley & Sons, Ltd.
Feedback, Mass Conservation and Reaction Kinetics Impact the Robustness of Cellular Oscillations

PubMed Central

Baum, Katharina; Kofahl, Bente; Steuer, Ralf; Wolf, Jana

2016-01-01

Oscillations occur in a wide variety of cellular processes, for example in calcium and p53 signaling responses, in metabolic pathways or within gene-regulatory networks, e.g. the circadian system. Since it is of central importance to understand the influence of perturbations on the dynamics of these systems a number of experimental and theoretical studies have examined their robustness. The period of circadian oscillations has been found to be very robust and to provide reliable timing. For intracellular calcium oscillations the period has been shown to be very sensitive and to allow for frequency-encoded signaling. We here apply a comprehensive computational approach to study the robustness of period and amplitude of oscillatory systems. We employ different prototype oscillator models and a large number of parameter sets obtained by random sampling. This framework is used to examine the effect of three design principles on the sensitivities towards perturbations of the kinetic parameters. We find that a prototype oscillator with negative feedback has lower period sensitivities than a prototype oscillator relying on positive feedback, but on average higher amplitude sensitivities. For both oscillator types, the use of Michaelis-Menten instead of mass action kinetics in all degradation and conversion reactions leads to an increase in period as well as amplitude sensitivities. We observe moderate changes in sensitivities if replacing mass conversion reactions by purely regulatory reactions. These insights are validated for a set of established models of various cellular rhythms. Overall, our work highlights the importance of reaction kinetics and feedback type for the variability of period and amplitude and therefore for the establishment of predictive models. PMID:28027301
Anomalous hydrodynamics of Weyl materials

NASA Astrophysics Data System (ADS)

Monteiro, Gustavo; Abanov, Alexander

Kinetic theory is a useful tool to study transport in Weyl materials when the band-touching points are hidden inside a Fermi surface. It accounts, for example, for the negative magnetoresistance caused by the chiral magnetic effect and quantum oscillations (SdH effect) in the magnetoresistance together within the same framework. As an alternative approach to kinetic theory we also consider the regime of strong interactions where hydrodynamics can be applicable. A variational principle of these hydrodynamic equations can be found in and provide a natural framework to study hydrodynamic surface modes which correspond to the strongly-interacting physics signature of Fermi arcs. G.M. acknowledges the financial support from FAPESP.

Results from the OH-PT model: a Kinetic-MHD Model of the Outer Heliosphere within SWMF

NASA Astrophysics Data System (ADS)

Michael, A.; Opher, M.; Tenishev, V.; Borovikov, D.; Toth, G.

2017-12-01

We present an update of the OH-PT model, a kinetic-MHD model of the outer heliosphere. The OH-PT model couples the Outer Heliosphere (OH) and Particle Tracker (PT) components within the Space Weather Modeling Framework (SWMF). The OH component utilizes the Block-Adaptive Tree Solarwind Roe-type Upwind Scheme (BATS-R-US) MHD code, a highly parallel, 3D, and block-adaptive solver. As a stand-alone model, the OH component solves the ideal MHD equations for the plasma and a separate set of Euler's equations for the different populations of neutral atoms. The neutrals and plasma in the outer heliosphere are coupled through charge-exchange. While this provides an accurate solution for the plasma, it is an inaccurate description of the neutrals. The charge-exchange mean free path is on the order of the size of the heliosphere; therefore the neutrals cannot be described as a fluid. The PT component is based on the Adaptive Mesh Particle Simulator (AMPS) model, a 3D, direct simulation Monte Carlo model that solves the Boltzmann equation for the motion and interaction of multi-species plasma and is used to model the neutral distribution functions throughout the domain. The charge-exchange process occurs within AMPS, which handles each event on a particle-by-particle basis and calculates the resulting source terms to the MHD equations. The OH-PT model combines the MHD solution for the plasma with the kinetic solution for the neutrals to form a self-consistent model of the heliosphere. In this work, we present verification and validation of the model as well as demonstrate the codes capabilities. Furthermore we provide a comparison of the OH-PT model to our multi-fluid approximation and detail the differences between the models in both the plasma solution and neutral distribution functions.
Multifluid MHD Simulations of the Plasma Environment of Comet Churyumov-Gerasimenko at Different Heliocentric Distances

NASA Astrophysics Data System (ADS)

Huang, Z.; Jia, X.; Rubin, M.; Fougere, N.; Gombosi, T. I.; Tenishev, V.; Combi, M. R.; Bieler, A. M.; Toth, G.; Hansen, K. C.; Shou, Y.

2014-12-01

We study the plasma environment of the comet Churyumov-Gerasimenko, which is the target of the Rosetta mission, by performing large scale numerical simulations. Our model is based on BATS-R-US within the Space Weather Modeling Framework that solves the governing multifluid MHD equations, which describe the behavior of the cometary heavy ions, the solar wind protons, and electrons. The model includes various mass loading processes, including ionization, charge exchange, dissociative ion-electron recombination, as well as collisional interactions between different fluids. The neutral background used in our MHD simulations is provided by a kinetic Direct Simulation Monte Carlo (DSMC) model. We will simulate how the cometary plasma environment changes at different heliocentric distances.
Coupled Kinetic-MHD Simulations of Divertor Heat Load with ELM Perturbations

NASA Astrophysics Data System (ADS)

Cummings, Julian; Chang, C. S.; Park, Gunyoung; Sugiyama, Linda; Pankin, Alexei; Klasky, Scott; Podhorszki, Norbert; Docan, Ciprian; Parashar, Manish

2010-11-01

The effect of Type-I ELM activity on divertor plate heat load is a key component of the DOE OFES Joint Research Target milestones for this year. In this talk, we present simulations of kinetic edge physics, ELM activity, and the associated divertor heat loads in which we couple the discrete guiding-center neoclassical transport code XGC0 with the nonlinear extended MHD code M3D using the End-to-end Framework for Fusion Integrated Simulations, or EFFIS. In these coupled simulations, the kinetic code and the MHD code run concurrently on the same massively parallel platform and periodic data exchanges are performed using a memory-to-memory coupling technology provided by EFFIS. The M3D code models the fast ELM event and sends frequent updates of the magnetic field perturbations and electrostatic potential to XGC0, which in turn tracks particle dynamics under the influence of these perturbations and collects divertor particle and energy flux statistics. We describe here how EFFIS technologies facilitate these coupled simulations and discuss results for DIII-D, NSTX and Alcator C-Mod tokamak discharges.
Negative Cooperativity in the Interaction of Prostaglandin H Synthase-1 with the Competitive Inhibitor Naproxen Can Be Described as the Interaction of a Non-competitive Inhibitor with Heterogeneous Enzyme Preparation.

PubMed

Filimonov, I S; Berzova, A P; Barkhatov, V I; Krivoshey, A V; Trushkin, N A; Vrzheshch, P V

2018-02-01

The kinetic mechanism of the interaction of nonsteroidal anti-inflammatory drugs (NSAIDs) with their main pharmacological target, prostaglandin H synthase (PGHS), has not yet been established. We showed that inhibition of PGHS-1 from sheep vesicular glands by naproxen (a representative of NSAIDs) demonstrates a non-competitive character with respect to arachidonic acid and cannot be described within a framework of the commonly used kinetic schemes. However, it can be described by taking into account the negative cooperativity of naproxen binding to the cyclooxygenase active sites of the PGHS-1 homodimer (the first naproxen molecule forms a more stable complex (K 1 = 0.1 µM) with the enzyme than the second naproxen molecule (K 2 = 9.2 µM)). An apparent non-competitive interaction of PGHS-1 with naproxen is due to slow dissociation of the enzyme-inhibitor complexes. The same experimental data could also be described using commonly accepted kinetic schemes, assuming that naproxen interacts was a mixture of two enzyme species with the inhibition constants K α = 0.05 µM and K β = 18.3 µM. Theoretical analysis and numerical calculations show that the phenomenon of kinetic convergence of these two models has a general nature: when K 2 > K 1 , the kinetic patterns (for transient kinetics and equilibrium state) generated by the cooperative model could be described by a scheme assuming the presence of two enzyme forms with the inhibition constants K α = K 1 /2, K β = 2·K 2 . When K 2 < K 1 , the cooperative model can be presented as a scheme with two inhibitor molecules simultaneously binding to the enzyme with the observed inhibition constant K (K = K 1 ·K 2 ). The assumption on the heterogeneity of the enzyme preparation in relation to its affinity to the inhibitor can be used instead of the assumption on the negative cooperativity of the enzyme-inhibitor interactions for convenient and easy practical description of such phenomena in enzymology, biotechnology, pharmacology, and other fields of science.
Modeling neutralization kinetics of HIV by broadly neutralizing monoclonal antibodies in genital secretions coating the cervicovaginal mucosa.

PubMed

McKinley, Scott A; Chen, Alex; Shi, Feng; Wang, Simi; Mucha, Peter J; Forest, M Gregory; Lai, Samuel K

2014-01-01

Eliciting broadly neutralizing antibodies (bnAb) in cervicovaginal mucus (CVM) represents a promising "first line of defense" strategy to reduce vaginal HIV transmission. However, it remains unclear what levels of bnAb must be present in CVM to effectively reduce infection. We approached this complex question by modeling the dynamic tally of bnAb coverage on HIV. This analysis introduces a critical, timescale-dependent competition: to protect, bnAb must accumulate at sufficient stoichiometry to neutralize HIV faster than virions penetrate CVM and reach target cells. We developed a model that incorporates concentrations and diffusivities of HIV and bnAb in semen and CVM, kinetic rates for binding (kon) and unbinding (koff) of select bnAb, and physiologically relevant thicknesses of CVM and semen layers. Comprehensive model simulations lead to robust conclusions about neutralization kinetics in CVM. First, due to the limited time virions in semen need to penetrate CVM, substantially greater bnAb concentrations than in vitro estimates must be present in CVM to neutralize HIV. Second, the model predicts that bnAb with more rapid kon, almost independent of koff, should offer greater neutralization potency in vivo. These findings suggest the fastest arriving virions at target cells present the greatest likelihood of infection. It also implies the marked improvements in in vitro neutralization potency of many recently discovered bnAb may not translate to comparable reduction in the bnAb dose needed to confer protection against initial vaginal infections. Our modeling framework offers a valuable tool to gaining quantitative insights into the dynamics of mucosal immunity against HIV and other infectious diseases.
Development of a point-kinetic verification scheme for nuclear reactor applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demazière, C., E-mail: demaz@chalmers.se; Dykin, V.; Jareteg, K.

In this paper, a new method that can be used for checking the proper implementation of time- or frequency-dependent neutron transport models and for verifying their ability to recover some basic reactor physics properties is proposed. This method makes use of the application of a stationary perturbation to the system at a given frequency and extraction of the point-kinetic component of the system response. Even for strongly heterogeneous systems for which an analytical solution does not exist, the point-kinetic component follows, as a function of frequency, a simple analytical form. The comparison between the extracted point-kinetic component and its expectedmore » analytical form provides an opportunity to verify and validate neutron transport solvers. The proposed method is tested on two diffusion-based codes, one working in the time domain and the other working in the frequency domain. As long as the applied perturbation has a non-zero reactivity effect, it is demonstrated that the method can be successfully applied to verify and validate time- or frequency-dependent neutron transport solvers. Although the method is demonstrated in the present paper in a diffusion theory framework, higher order neutron transport methods could be verified based on the same principles.« less
Structural and Kinetic Basis for Substrate Selectivity in Populus tremuloides Sinapyl Alcohol Dehydrogenase

PubMed Central

Bomati, Erin K.; Noel, Joseph P.

2005-01-01

We describe the three-dimensional structure of sinapyl alcohol dehydrogenase (SAD) from Populus tremuloides (aspen), a member of the NADP(H)-dependent dehydrogenase family that catalyzes the last reductive step in the formation of monolignols. The active site topology revealed by the crystal structure substantiates kinetic results indicating that SAD maintains highest specificity for the substrate sinapaldehyde. We also report substantial substrate inhibition kinetics for the SAD-catalyzed reduction of hydroxycinnamaldehydes. Although SAD and classical cinnamyl alcohol dehydrogenases (CADs) catalyze the same reaction and share some sequence identity, the active site topology of SAD is strikingly different from that predicted for classical CADs. Kinetic analyses of wild-type SAD and several active site mutants demonstrate the complexity of defining determinants of substrate specificity in these enzymes. These results, along with a phylogenetic analysis, support the inclusion of SAD in a plant alcohol dehydrogenase subfamily that includes cinnamaldehyde and benzaldehyde dehydrogenases. We used the SAD three-dimensional structure to model several of these SAD-like enzymes, and although their active site topologies largely mirror that of SAD, we describe a correlation between substrate specificity and amino acid substitution patterns in their active sites. The SAD structure thus provides a framework for understanding substrate specificity in this family of enzymes and for engineering new enzyme specificities. PMID:15829607
Structural and kinetic basis for substrate selectivity in Populus tremuloides sinapyl alcohol dehydrogenase.

PubMed

Bomati, Erin K; Noel, Joseph P

2005-05-01

We describe the three-dimensional structure of sinapyl alcohol dehydrogenase (SAD) from Populus tremuloides (aspen), a member of the NADP(H)-dependent dehydrogenase family that catalyzes the last reductive step in the formation of monolignols. The active site topology revealed by the crystal structure substantiates kinetic results indicating that SAD maintains highest specificity for the substrate sinapaldehyde. We also report substantial substrate inhibition kinetics for the SAD-catalyzed reduction of hydroxycinnamaldehydes. Although SAD and classical cinnamyl alcohol dehydrogenases (CADs) catalyze the same reaction and share some sequence identity, the active site topology of SAD is strikingly different from that predicted for classical CADs. Kinetic analyses of wild-type SAD and several active site mutants demonstrate the complexity of defining determinants of substrate specificity in these enzymes. These results, along with a phylogenetic analysis, support the inclusion of SAD in a plant alcohol dehydrogenase subfamily that includes cinnamaldehyde and benzaldehyde dehydrogenases. We used the SAD three-dimensional structure to model several of these SAD-like enzymes, and although their active site topologies largely mirror that of SAD, we describe a correlation between substrate specificity and amino acid substitution patterns in their active sites. The SAD structure thus provides a framework for understanding substrate specificity in this family of enzymes and for engineering new enzyme specificities.
Exploration of the Transition from the Hydrodynamic-like to the Strongly Kinetic Regime in Shock-Driven Implosions

DOE PAGES

Rosenberg, M. J.; Rinderknecht, H. G.; Hoffman, N. M.; ...

2014-05-05

Clear evidence of the transition from hydrodynamiclike to strongly kinetic shock-driven implosions is, for the first time, revealed and quantitatively assessed. Implosions with a range of initial equimolar D 3He gas densities show that as the density is decreased, hydrodynamic simulations strongly diverge from and increasingly over-predict the observed nuclear yields, from a factor of ~2 at 3.1 mg/cm 3 to a factor of 100 at 0.14 mg/cm 3. (The corresponding Knudsen number, the ratio of ion mean-free path to minimum shell radius, varied from 0.3 to 9; similarly, the ratio of fusion burn duration to ion diffusion time, anothermore » figure of merit of kinetic effects, varied from 0.3 to 14.) This result is shown to be unrelated to the effects of hydrodynamic mix. As a first step to garner insight into this transition, a reduced ion kinetic (RIK) model that includes gradient-diffusion and loss-term approximations to several transport processes was implemented within the framework of a one-dimensional radiation-transport code. After empirical calibration, the RIK simulations reproduce the observed yield trends, largely as a result of ion diffusion and the depletion of the reacting tail ions.« less
Mass, Momentum and Kinetic Energy of a Relativistic Particle

ERIC Educational Resources Information Center

Zanchini, Enzo

2010-01-01

A rigorous definition of mass in special relativity, proposed in a recent paper, is recalled and employed to obtain simple and rigorous deductions of the expressions of momentum and kinetic energy for a relativistic particle. The whole logical framework appears as the natural extension of the classical one. Only the first, second and third laws of…
Differential equation methods for simulation of GFP kinetics in non-steady state experiments.

PubMed

Phair, Robert D

2018-03-15

Genetically encoded fluorescent proteins, combined with fluorescence microscopy, are widely used in cell biology to collect kinetic data on intracellular trafficking. Methods for extraction of quantitative information from these data are based on the mathematics of diffusion and tracer kinetics. Current methods, although useful and powerful, depend on the assumption that the cellular system being studied is in a steady state, that is, the assumption that all the molecular concentrations and fluxes are constant for the duration of the experiment. Here, we derive new tracer kinetic analytical methods for non-steady state biological systems by constructing mechanistic nonlinear differential equation models of the underlying cell biological processes and linking them to a separate set of differential equations governing the kinetics of the fluorescent tracer. Linking the two sets of equations is based on a new application of the fundamental tracer principle of indistinguishability and, unlike current methods, supports correct dependence of tracer kinetics on cellular dynamics. This approach thus provides a general mathematical framework for applications of GFP fluorescence microscopy (including photobleaching [FRAP, FLIP] and photoactivation to frequently encountered experimental protocols involving physiological or pharmacological perturbations (e.g., growth factors, neurotransmitters, acute knockouts, inhibitors, hormones, cytokines, and metabolites) that initiate mechanistically informative intracellular transients. When a new steady state is achieved, these methods automatically reduce to classical steady state tracer kinetic analysis. © 2018 Phair. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Zeolitic imidazolate frameworks for kinetic separation of propane and propene

DOEpatents

Li, Jing; Li, Kunhao; Olson, David H.

2014-08-05

Zeolitic Imidazolate Frameworks (ZIFs) characterized by organic ligands consisting of imidazole ligands that are either essentially all 2-chloroimidazole ligands or essentially all 2-bromoimidazole ligands are disclosed. Methods for separating propane and propene with the ZIFs of the present invention, as well as other ZIFs, are also disclosed.
Modeling time-coincident ultrafast electron transfer and solvation processes at molecule-semiconductor interfaces

NASA Astrophysics Data System (ADS)

Li, Lesheng; Giokas, Paul G.; Kanai, Yosuke; Moran, Andrew M.

2014-06-01

Kinetic models based on Fermi's Golden Rule are commonly employed to understand photoinduced electron transfer dynamics at molecule-semiconductor interfaces. Implicit in such second-order perturbative descriptions is the assumption that nuclear relaxation of the photoexcited electron donor is fast compared to electron injection into the semiconductor. This approximation breaks down in systems where electron transfer transitions occur on 100-fs time scale. Here, we present a fourth-order perturbative model that captures the interplay between time-coincident electron transfer and nuclear relaxation processes initiated by light absorption. The model consists of a fairly small number of parameters, which can be derived from standard spectroscopic measurements (e.g., linear absorbance, fluorescence) and/or first-principles electronic structure calculations. Insights provided by the model are illustrated for a two-level donor molecule coupled to both (i) a single acceptor level and (ii) a density of states (DOS) calculated for TiO2 using a first-principles electronic structure theory. These numerical calculations show that second-order kinetic theories fail to capture basic physical effects when the DOS exhibits narrow maxima near the energy of the molecular excited state. Overall, we conclude that the present fourth-order rate formula constitutes a rigorous and intuitive framework for understanding photoinduced electron transfer dynamics that occur on the 100-fs time scale.
Hybrid RANS-LES using high order numerical methods

NASA Astrophysics Data System (ADS)

Henry de Frahan, Marc; Yellapantula, Shashank; Vijayakumar, Ganesh; Knaus, Robert; Sprague, Michael

2017-11-01

Understanding the impact of wind turbine wake dynamics on downstream turbines is particularly important for the design of efficient wind farms. Due to their tractable computational cost, hybrid RANS/LES models are an attractive framework for simulating separation flows such as the wake dynamics behind a wind turbine. High-order numerical methods can be computationally efficient and provide increased accuracy in simulating complex flows. In the context of LES, high-order numerical methods have shown some success in predictions of turbulent flows. However, the specifics of hybrid RANS-LES models, including the transition region between both modeling frameworks, pose unique challenges for high-order numerical methods. In this work, we study the effect of increasing the order of accuracy of the numerical scheme in simulations of canonical turbulent flows using RANS, LES, and hybrid RANS-LES models. We describe the interactions between filtering, model transition, and order of accuracy and their effect on turbulence quantities such as kinetic energy spectra, boundary layer evolution, and dissipation rate. This work was funded by the U.S. Department of Energy, Exascale Computing Project, under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.
Predicting kinetic nanocrystal shapes through multi-scale theory and simulation: Polyvinylpyrrolidone-mediated growth of Ag nanocrystals

NASA Astrophysics Data System (ADS)

Balankura, Tonnam; Qi, Xin; Zhou, Ya; Fichthorn, Kristen A.

2016-10-01

In the shape-controlled synthesis of colloidal Ag nanocrystals, structure-directing agents, particularly polyvinylpyrrolidone (PVP), are known to be a key additive in making nanostructures with well-defined shapes. Although many Ag nanocrystals have been successfully synthesized using PVP, the mechanism by which PVP actuates shape control remains elusive. Here, we present a multi-scale theoretical framework for kinetic Wulff shape predictions that accounts for the chemical environment, which we used to probe the kinetic influence of the adsorbed PVP film. Within this framework, we use umbrella-sampling molecular dynamics simulations to calculate the potential of mean force and diffusion coefficient profiles of Ag atom deposition onto Ag(100) and Ag(111) in ethylene glycol solution with surface-adsorbed PVP. We use these profiles to calculate the mean-first passage times and implement extensive Brownian dynamics simulations, which allows the kinetic effects to be quantitatively evaluated. Our results show that PVP films can regulate the flux of Ag atoms to be greater towards Ag(111) than Ag(100). PVP's preferential binding towards Ag(100) over Ag(111) gives PVP its flux-regulating capabilities through the lower free-energy barrier of Ag atoms to cross the lower-density PVP film on Ag(111) and enhanced Ag trapping by the extended PVP film on Ag(111). Under kinetic control, {100}-faceted nanocrystals will be formed when the Ag flux is greater towards Ag(111). The predicted kinetic Wulff shapes are in agreement with the analogous experimental system.
Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities

NASA Astrophysics Data System (ADS)

Esposito, Gaetano

Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and identifying sources of uncertainty affecting relevant reaction pathways are usually addressed by resorting to Global Sensitivity Analysis (GSA) techniques. In particular, the most sensitive reactions controlling combustion phenomena are first identified using the Morris Method and then analyzed under the Random Sampling -- High Dimensional Model Representation (RS-HDMR) framework. The HDMR decomposition shows that 10% of the variance seen in the extinction strain rate of non-premixed flames is due to second-order effects between parameters, whereas the maximum concentration of acetylene, a key soot precursor, is affected by mostly only first-order contributions. Moreover, the analysis of the global sensitivity indices demonstrates that improving the accuracy of the reaction rates including the vinyl radical, C2H3, can drastically reduce the uncertainty of predicting targeted flame properties. Finally, the back-propagation of the experimental uncertainty of the extinction strain rate to the parameter space is also performed. This exercise, achieved by recycling the numerical solutions of the RS-HDMR, shows that some regions of the parameter space have a high probability of reproducing the experimental value of the extinction strain rate between its own uncertainty bounds. Therefore this study demonstrates that the uncertainty analysis of bulk flame properties can effectively provide information on relevant chemical reactions.
How Four Scientists Integrate Thermodynamic and Kinetic Theory, Context, Analogies, and Methods in Protein-Folding and Dynamics Research: Implications for Biochemistry Instruction.

PubMed

Jeffery, Kathleen A; Pelaez, Nancy; Anderson, Trevor R

2018-01-01

To keep biochemistry instruction current and relevant, it is crucial to expose students to cutting-edge scientific research and how experts reason about processes governed by thermodynamics and kinetics such as protein folding and dynamics. This study focuses on how experts explain their research into this topic with the intention of informing instruction. Previous research has modeled how expert biologists incorporate research methods, social or biological context, and analogies when they talk about their research on mechanisms. We used this model as a guiding framework to collect and analyze interview data from four experts. The similarities and differences that emerged from analysis indicate that all experts integrated theoretical knowledge with their research context, methods, and analogies when they explained how phenomena operate, in particular by mapping phenomena to mathematical models; they explored different processes depending on their explanatory aims, but readily transitioned between different perspectives and explanatory models; and they explained thermodynamic and kinetic concepts of relevance to protein folding in different ways that aligned with their particular research methods. We discuss how these findings have important implications for teaching and future educational research. © 2018 K. A. Jeffery et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Adsorptive removal of 1-naphthol from water with Zeolitic imidazolate framework-67

NASA Astrophysics Data System (ADS)

Yan, Xinlong; Hu, Xiaoyan; Chen, Tao; Zhang, Shiyu; Zhou, Min

2017-08-01

1-Naphthol is widely used as an intermediate in the plastics, dyes, fibers and rubbers production areas, leading to the increasing detection of 1-naphthol in the soil and water environment, which is of particular concern due to its acute toxicity and negative environmental impacts. Considering the high surface area and good stability of ZIFs (zeolitic imidazole frameworks) material, ZIF-67 (a representative cobalt-based ZIFs material) was synthesized and applied as an adsorbent for removal of 1-naphthol from aqueous solution. The obtained ZIF-67 was characterized by XRD, TEM, XPS, N2 physisorption and TG, and the adsorption isotherm, kinetics, and regeneration of the adsorbent were studied in detail. The adsorption of 1-naphthol on ZIF-67 followed a pseudo-second-order equation kinetics and fitted Langmuir adsorption model with a maximum adsorption capacity of 339 mg/g at 313 K, which is much higher than that of the common adsorbents reported such as activated carbon and carbon nanotubes et al. The solution pH was found to be an important factor influencing the adsorption process, which could be explained by the predominant mechanism controlling the process, i.e. electrostatic attraction. In addition, the ZIF-67 showed desirable reusability toward 1-naphthol removal from alkaline aqueous solution.
A generalized disjunctive programming framework for the optimal synthesis and analysis of processes for ethanol production from corn stover.

PubMed

Scott, Felipe; Aroca, Germán; Caballero, José Antonio; Conejeros, Raúl

2017-07-01

The aim of this study is to analyze the techno-economic performance of process configurations for ethanol production involving solid-liquid separators and reactors in the saccharification and fermentation stage, a family of process configurations where few alternatives have been proposed. Since including these process alternatives creates a large number of possible process configurations, a framework for process synthesis and optimization is proposed. This approach is supported on kinetic models fed with experimental data and a plant-wide techno-economic model. Among 150 process configurations, 40 show an improved MESP compared to a well-documented base case (BC), almost all include solid separators and some show energy retrieved in products 32% higher compared to the BC. Moreover, 16 of them also show a lower capital investment per unit of ethanol produced per year. Several of the process configurations found in this work have not been reported in the literature. Copyright © 2017 Elsevier Ltd. All rights reserved.
A symbiotic approach to fluid equations and non-linear flux-driven simulations of plasma dynamics

NASA Astrophysics Data System (ADS)

Halpern, Federico

2017-10-01

The fluid framework is ubiquitous in studies of plasma transport and stability. Typical forms of the fluid equations are motivated by analytical work dating several decades ago, before computer simulations were indispensable, and can be, therefore, not optimal for numerical computation. We demonstrate a new first-principles approach to obtaining manifestly consistent, skew-symmetric fluid models, ensuring internal consistency and conservation properties even in discrete form. Mass, kinetic, and internal energy become quadratic (and always positive) invariants of the system. The model lends itself to a robust, straightforward discretization scheme with inherent non-linear stability. A simpler, drift-ordered form of the equations is obtained, and first results of their numerical implementation as a binary framework for bulk-fluid global plasma simulations are demonstrated. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Fusion Energy Sciences, Theory Program, under Award No. DE-FG02-95ER54309.

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development

PubMed Central

2014-01-01

Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on average 15% of the mean values over the succeeding parameter sets. Conclusions Our results indicate that the presented approach is effective for comparing model alternatives and reducing models to the minimum complexity replicating measured data. We therefore believe that this approach has significant potential for reparameterising existing frameworks, for identification of redundant model components of large biophysical models and to increase their predictive capacity. PMID:24886522
Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K

2018-01-03

Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.
Taking Ockham's razor to enzyme dynamics and catalysis.

PubMed

Glowacki, David R; Harvey, Jeremy N; Mulholland, Adrian J

2012-01-29

The role of protein dynamics in enzyme catalysis is a matter of intense current debate. Enzyme-catalysed reactions that involve significant quantum tunnelling can give rise to experimental kinetic isotope effects with complex temperature dependences, and it has been suggested that standard statistical rate theories, such as transition-state theory, are inadequate for their explanation. Here we introduce aspects of transition-state theory relevant to the study of enzyme reactivity, taking cues from chemical kinetics and dynamics studies of small molecules in the gas phase and in solution--where breakdowns of statistical theories have received significant attention and their origins are relatively better understood. We discuss recent theoretical approaches to understanding enzyme activity and then show how experimental observations for a number of enzymes may be reproduced using a transition-state-theory framework with physically reasonable parameters. Essential to this simple model is the inclusion of multiple conformations with different reactivity.
Energy Dissipation and Phase-Space Dynamics in Eulerian Vlasov-Maxwell Turbulence

NASA Astrophysics Data System (ADS)

Tenbarge, Jason; Juno, James; Hakim, Ammar

2017-10-01

Turbulence in a magnetized plasma is a primary mechanism responsible for transforming energy at large injection scales into small-scale motions, which are ultimately dissipated as heat in systems such as the solar corona, wind, and other astrophysical objects. At large scales, the turbulence is well described by fluid models of the plasma; however, understanding the processes responsible for heating a weakly collisional plasma such as the solar wind requires a kinetic description. We present a fully kinetic Eulerian Vlasov-Maxwell study of turbulence using the Gkeyll simulation framework, including studies of the cascade of energy in phase space and formation and dissipation of coherent structures. We also leverage the recently developed field-particle correlations to diagnose the dominant sources of dissipation and compare the results of the field-particle correlation to other dissipation measures. NSF SHINE AGS-1622306 and DOE DE-AC02-09CH11466.
Persistent spin helix manipulation by optical doping of a CdTe quantum well

NASA Astrophysics Data System (ADS)

Passmann, F.; Anghel, S.; Tischler, T.; Poshakinskiy, A. V.; Tarasenko, S. A.; Karczewski, G.; Wojtowicz, T.; Bristow, A. D.; Betz, M.

2018-05-01

Time-resolved Kerr-rotation microscopy explores the influence of optical doping on the persistent spin helix in a [001]-grown CdTe quantum well at cryogenic temperatures. Electron spin-diffusion dynamics reveal a momentum-dependent effective magnetic field providing SU(2) spin-rotation symmetry, consistent with kinetic theory. The Dresselhaus and Rashba spin-orbit coupling parameters are extracted independently from rotating the spin helix with external magnetic fields applied parallel and perpendicular to the effective magnetic field. Most importantly, a nonuniform spatiotemporal precession pattern is observed. The kinetic-theory framework of spin diffusion allows for modeling of this finding by incorporating the photocarrier density into the Rashba (α) and the Dresselhaus (β3) parameters. Corresponding calculations are further validated by an excitation-density-dependent measurement. This work shows universality of the persistent spin helix by its observation in a II-VI compound and the ability to fine-tune it by optical doping.
The kinetic origin of delayed yielding in metallic glasses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ye, Y. F.; Liu, X. D.; Wang, S.

2016-06-20

Recent experiments showed that irreversible structural change or plasticity could occur in metallic glasses (MGs) even within the apparent elastic limit after a sufficiently long waiting time. To explain this phenomenon, a stochastic shear transformation model is developed based on a unified rate theory to predict delayed yielding in MGs, which is validated afterwards through extensive atomistic simulations carried out on different MGs. On a fundamental level, an analytic framework is established in this work that links time, stress, and temperature altogether into a general yielding criterion for MGs.
Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

PubMed

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.
Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

PubMed Central

2010-01-01

Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. Results In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. Conclusions The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates. PMID:20500862
Effect of heating rate and kinetic model selection on activation energy of nonisothermal crystallization of amorphous felodipine.

PubMed

Chattoraj, Sayantan; Bhugra, Chandan; Li, Zheng Jane; Sun, Changquan Calvin

2014-12-01

The nonisothermal crystallization kinetics of amorphous materials is routinely analyzed by statistically fitting the crystallization data to kinetic models. In this work, we systematically evaluate how the model-dependent crystallization kinetics is impacted by variations in the heating rate and the selection of the kinetic model, two key factors that can lead to significant differences in the crystallization activation energy (Ea ) of an amorphous material. Using amorphous felodipine, we show that the Ea decreases with increase in the heating rate, irrespective of the kinetic model evaluated in this work. The model that best describes the crystallization phenomenon cannot be identified readily through the statistical fitting approach because several kinetic models yield comparable R(2) . Here, we propose an alternate paired model-fitting model-free (PMFMF) approach for identifying the most suitable kinetic model, where Ea obtained from model-dependent kinetics is compared with those obtained from model-free kinetics. The most suitable kinetic model is identified as the one that yields Ea values comparable with the model-free kinetics. Through this PMFMF approach, nucleation and growth is identified as the main mechanism that controls the crystallization kinetics of felodipine. Using this PMFMF approach, we further demonstrate that crystallization mechanism from amorphous phase varies with heating rate. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Mutation-induced protein interaction kinetics changes affect apoptotic network dynamic properties and facilitate oncogenesis

PubMed Central

Zhao, Linjie; Sun, Tanlin; Pei, Jianfeng; Ouyang, Qi

2015-01-01

It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation. PMID:26170328
Quantum-kinetic theory of photocurrent generation via direct and phonon-mediated optical transitions

NASA Astrophysics Data System (ADS)

Aeberhard, U.

2011-07-01

A quantum kinetic theory of direct and phonon-mediated indirect optical transitions is developed within the framework of the nonequilibrium Green’s function formalism. After validation against the standard Fermi golden rule approach in the bulk case, it is used in the simulation of photocurrent generation in ultrathin crystalline silicon p-i-n junction devices.
Characteristics in Restructuring High School Students' Frameworks of Gaseous Kinetics in Korea: A Psychological Point of View.

ERIC Educational Resources Information Center

Cho, In-Young; Park, Hyun-Ju; Choi, Byung-Soon

This study was conducted to describe in detail Korean students' conceptual change learning processes in the study of kinetic theory of gases. The study was interpretive, using multiple data sources to achieve a triangulation of data. Three students from a public high school for boys served as representative cases. How epistemological aspect and…
A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

NASA Astrophysics Data System (ADS)

Fahey, Kathleen M.; Carlton, Annmarie G.; Pye, Havala O. T.; Baek, Jaemeen; Hutzell, William T.; Stanier, Charles O.; Baker, Kirk R.; Wyat Appel, K.; Jaoui, Mohammed; Offenberg, John H.

2017-04-01

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM - KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM - KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM - KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in cloud SOA at the surface in the eastern United States for June 2013.
From minerals to hillslopes: Towards an integrated framework for interpreting chemical and physical erosion

NASA Astrophysics Data System (ADS)

Hahm, W.; Riebe, C. S.; Ferrier, K.; Kirchner, J. W.

2011-12-01

Traditional frameworks for conceptualizing hillslope denudation distinguish between the movement of mass in solution (chemical erosion) and mass moved via mechanical processes (physical erosion). At the hillslope scale, physical and chemical erosion rates can be quantified by combining measurements of regolith chemistry with cosmogenic nuclide concentrations in bedrock and sediment, while basin-scale rates are often inferred from riverine solute and sediment loads. These techniques integrate the effects of numerous weathering and erosion mechanisms and do not provide prima facie information about the precise nature and scale of those mechanisms. For insight into erosional process, physical erosion has been considered in terms of two limiting regimes. When physical erosion outpaces weathering front advance, regolith is mobilized downslope as soon as it is sufficiently loosened by weathering, and physical erosion rates are limited by rates of mobile regolith production. This is commonly termed weathering-limited erosion. Conversely, when weathering front advance outpaces erosion, the mobile regolith layer grows thicker over time, and physical erosion rates are limited by the efficiency of downslope transport processes. This is termed transport-limited erosion. This terminology brings the description of hillslope evolution closer to the realm of essential realism, to the extent that measurable quantities from the field can be cast in a process-based framework. An analogous process-limitation framework describes chemical erosion. In supply-limited chemical erosion, chemical weathering depletes regolith of its reactive phases during residence on a hillslope, and chemical erosion rates are limited by the supply of fresh minerals to the weathering zone. Alternatively, hillslopes may exhibit kinetic-limited chemical erosion, where physical erosion transports regolith downslope before weatherable phases are completely removed by chemical erosion. We show how supply- and kinetic-limited chemical erosion can be distinguished from one another using data from a global compilation of physical and chemical erosion rates. As a step towards understanding these rates at the level of essential realism, we explore how the hillslope-scale regimes of supply- and kinetic-limited chemical erosion relate to existing conceptual frameworks that interpret weathering rates in terms of transport- and kinetic-limitation at the mineral scale.
Emergence of running dark energy from polynomial f( R) theory in Palatini formalism

NASA Astrophysics Data System (ADS)

Szydłowski, Marek; Stachowski, Aleksander; Borowiec, Andrzej

2017-09-01

We consider FRW cosmology in f(R)= R+ γ R^2+δ R^3 modified framework. The Palatini approach reduces its dynamics to the simple generalization of Friedmann equation. Thus we study the dynamics in two-dimensional phase space with some details. After reformulation of the model in the Einstein frame, it reduces to the FRW cosmological model with a homogeneous scalar field and vanishing kinetic energy term. This potential determines the running cosmological constant term as a function of the Ricci scalar. As a result we obtain the emergent dark energy parametrization from the covariant theory. We study also singularities of the model and demonstrate that in the Einstein frame some undesirable singularities disappear.
GPU-powered model analysis with PySB/cupSODA.

PubMed

Harris, Leonard A; Nobile, Marco S; Pino, James C; Lubbock, Alexander L R; Besozzi, Daniela; Mauri, Giancarlo; Cazzaniga, Paolo; Lopez, Carlos F

2017-11-01

A major barrier to the practical utilization of large, complex models of biochemical systems is the lack of open-source computational tools to evaluate model behaviors over high-dimensional parameter spaces. This is due to the high computational expense of performing thousands to millions of model simulations required for statistical analysis. To address this need, we have implemented a user-friendly interface between cupSODA, a GPU-powered kinetic simulator, and PySB, a Python-based modeling and simulation framework. For three example models of varying size, we show that for large numbers of simulations PySB/cupSODA achieves order-of-magnitude speedups relative to a CPU-based ordinary differential equation integrator. The PySB/cupSODA interface has been integrated into the PySB modeling framework (version 1.4.0), which can be installed from the Python Package Index (PyPI) using a Python package manager such as pip. cupSODA source code and precompiled binaries (Linux, Mac OS/X, Windows) are available at github.com/aresio/cupSODA (requires an Nvidia GPU; developer.nvidia.com/cuda-gpus). Additional information about PySB is available at pysb.org. paolo.cazzaniga@unibg.it or c.lopez@vanderbilt.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
SPY: a new scission-point model based on microscopic inputs to predict fission fragment properties

NASA Astrophysics Data System (ADS)

Panebianco, Stefano; Dubray, Nöel; Goriely, Stéphane; Hilaire, Stéphane; Lemaître, Jean-François; Sida, Jean-Luc

2014-04-01

Despite the difficulty in describing the whole fission dynamics, the main fragment characteristics can be determined in a static approach based on a so-called scission-point model. Within this framework, a new Scission-Point model for the calculations of fission fragment Yields (SPY) has been developed. This model, initially based on the approach developed by Wilkins in the late seventies, consists in performing a static energy balance at scission, where the two fragments are supposed to be completely separated so that their macroscopic properties (mass and charge) can be considered as fixed. Given the knowledge of the system state density, averaged quantities such as mass and charge yields, mean kinetic and excitation energy can then be extracted in the framework of a microcanonical statistical description. The main advantage of the SPY model is the introduction of one of the most up-to-date microscopic descriptions of the nucleus for the individual energy of each fragment and, in the future, for their state density. These quantities are obtained in the framework of HFB calculations using the Gogny nucleon-nucleon interaction, ensuring an overall coherence of the model. Starting from a description of the SPY model and its main features, a comparison between the SPY predictions and experimental data will be discussed for some specific cases, from light nuclei around mercury to major actinides. Moreover, extensive predictions over the whole chart of nuclides will be discussed, with particular attention to their implication in stellar nucleosynthesis. Finally, future developments, mainly concerning the introduction of microscopic state densities, will be briefly discussed.
Mapping the function of neuronal ion channels in model and experiment

PubMed Central

Podlaski, William F; Seeholzer, Alexander; Groschner, Lukas N; Miesenböck, Gero; Ranjan, Rajnish; Vogels, Tim P

2017-01-01

Ion channel models are the building blocks of computational neuron models. Their biological fidelity is therefore crucial for the interpretation of simulations. However, the number of published models, and the lack of standardization, make the comparison of ion channel models with one another and with experimental data difficult. Here, we present a framework for the automated large-scale classification of ion channel models. Using annotated metadata and responses to a set of voltage-clamp protocols, we assigned 2378 models of voltage- and calcium-gated ion channels coded in NEURON to 211 clusters. The IonChannelGenealogy (ICGenealogy) web interface provides an interactive resource for the categorization of new and existing models and experimental recordings. It enables quantitative comparisons of simulated and/or measured ion channel kinetics, and facilitates field-wide standardization of experimentally-constrained modeling. DOI: http://dx.doi.org/10.7554/eLife.22152.001 PMID:28267430
A linear framework for time-scale separation in nonlinear biochemical systems.

PubMed

Gunawardena, Jeremy

2012-01-01

Cellular physiology is implemented by formidably complex biochemical systems with highly nonlinear dynamics, presenting a challenge for both experiment and theory. Time-scale separation has been one of the few theoretical methods for distilling general principles from such complexity. It has provided essential insights in areas such as enzyme kinetics, allosteric enzymes, G-protein coupled receptors, ion channels, gene regulation and post-translational modification. In each case, internal molecular complexity has been eliminated, leading to rational algebraic expressions among the remaining components. This has yielded familiar formulas such as those of Michaelis-Menten in enzyme kinetics, Monod-Wyman-Changeux in allostery and Ackers-Johnson-Shea in gene regulation. Here we show that these calculations are all instances of a single graph-theoretic framework. Despite the biochemical nonlinearity to which it is applied, this framework is entirely linear, yet requires no approximation. We show that elimination of internal complexity is feasible when the relevant graph is strongly connected. The framework provides a new methodology with the potential to subdue combinatorial explosion at the molecular level.
On the validity of cosmic no-hair conjecture in an anisotropic inationary model

NASA Astrophysics Data System (ADS)

Do, Tuan Q.

2018-05-01

We will present main results of our recent investigations on the validity of cosmic no-hair conjecture proposed by Hawking and his colleagues long time ago in the framework of an anisotropic inflationary model proposed by Kanno, Soda, and Watanabe. As a result, we will show that the cosmic no-hair conjecture seems to be generally violated in the Kanno-Soda- Watanabe model for both canonical and non-canonical scalar fields due to the existence of a non-trivial coupling term between scalar and electromagnetic fields. However, we will also show that the validity of the cosmic no-hair conjecture will be ensured once a unusual scalar field called the phantom field, whose kinetic energy term is negative definite, is introduced into the Kanno-Soda-Watanabe model.

A novel mechanistic modeling framework for analysis of electrode balancing and degradation modes in commercial lithium-ion cells

NASA Astrophysics Data System (ADS)

Schindler, Stefan; Danzer, Michael A.

2017-03-01

Aiming at a long-term stable and safe operation of rechargeable lithium-ion cells, elementary design aspects and degradation phenomena have to be considered depending on the specific application. Among the degrees of freedom in cell design, electrode balancing is of particular interest and has a distinct effect on useable capacity and voltage range. Concerning intrinsic degradation modes, understanding the underlying electrochemical processes and tracing the overall degradation history are the most crucial tasks. In this study, a model-based, minimal parameter framework for combined elucidation of electrode balancing and degradation pathways in commercial lithium-ion cells is introduced. The framework rests upon the simulation of full cell voltage profiles from the superposition of equivalent, artificially degraded half-cell profiles and allows to separate aging contributions from loss of available lithium and active materials in both electrodes. A physically meaningful coupling between thermodynamic and kinetic degradation modes based on the correlation between altered impedance features and loss of available lithium as well as loss of active material is proposed and validated by a low temperature degradation profile examined in one of our recent publications. The coupled framework is able to determine the electrode balancing within an error range of < 1% and the projected cell degradation is qualitatively and quantitatively in line with experimental observations.
A kinetic and thermodynamic framework for the Azoarcus group I ribozyme reaction

PubMed Central

Gleitsman, Kristin R.

2014-01-01

Determination of quantitative thermodynamic and kinetic frameworks for ribozymes derived from the Azoarcus group I intron and comparisons to their well-studied analogs from the Tetrahymena group I intron reveal similarities and differences between these RNAs. The guanosine (G) substrate binds to the Azoarcus and Tetrahymena ribozymes with similar equilibrium binding constants and similar very slow association rate constants. These and additional literature observations support a model in which the free ribozyme is not conformationally competent to bind G and in which the probability of assuming the binding-competent state is determined by tertiary interactions of peripheral elements. As proposed previously, the slow binding of guanosine may play a role in the specificity of group I intron self-splicing, and slow binding may be used analogously in other biological processes. The internal equilibrium between ribozyme-bound substrates and products is similar for these ribozymes, but the Azoarcus ribozyme does not display the coupling in the binding of substrates that is observed with the Tetrahymena ribozyme, suggesting that local preorganization of the active site and rearrangements within the active site upon substrate binding are different for these ribozymes. Our results also confirm the much greater tertiary binding energy of the 5′-splice site analog with the Azoarcus ribozyme, binding energy that presumably compensates for the fewer base-pairing interactions to allow the 5′-exon intermediate in self splicing to remain bound subsequent to 5′-exon cleavage and prior to exon ligation. Most generally, these frameworks provide a foundation for design and interpretation of experiments investigating fundamental properties of these and other structured RNAs. PMID:25246656
A Methodology for Evaluating the Hygroscopic Behavior of Wood in Adaptive Building Skins using Motion Grammar

NASA Astrophysics Data System (ADS)

El-Dabaa, Rana; Abdelmohsen, Sherif

2018-05-01

The challenge in designing kinetic architecture lies in the lack of applying computational design and human computer interaction to successfully design intelligent and interactive interfaces. The use of ‘programmable materials’ as specifically fabricated composite materials that afford motion upon stimulation is promising for low-cost low-tech systems for kinetic facades in buildings. Despite efforts to develop working prototypes, there has been no clear methodological framework for understanding and controlling the behavior of programmable materials or for using them for such purposes. This paper introduces a methodology for evaluating the motion acquired from programmed material – resulting from the hygroscopic behavior of wood – through ‘motion grammar’. Motion grammar typically allows for the explanation of desired motion control in a computationally tractable method. The paper analyzed and evaluated motion parameters related to the hygroscopic properties and behavior of wood, and introduce a framework for tracking and controlling wood as a programmable material for kinetic architecture.
A Theory for Self-consistent Acceleration of Energetic Charged Particles by Dynamic Small-scale Flux Ropes

NASA Astrophysics Data System (ADS)

le Roux, J. A.; Zank, G. P.; Khabarova, O.; Webb, G. M.

2016-12-01

Simulations of charged particle acceleration in turbulent plasma regions with numerous small-scale contracting and merging (reconnecting) magnetic islands/flux ropes emphasize the key role of temporary particle trapping in these structures for efficient acceleration that can result in power-law spectra. In response, a comprehensive kinetic transport theory framework was developed by Zank et al. and le Roux et al. to capture the essential physics of energetic particle acceleration in solar wind regions containing numerous dynamic small-scale flux ropes. Examples of test particle solutions exhibiting hard power-law spectra for energetic particles were presented in recent publications by both Zank et al. and le Roux et al.. However, the considerable pressure in the accelerated particles suggests the need for expanding the kinetic transport theory to enable a self-consistent description of energy exchange between energetic particles and small-scale flux ropes. We plan to present the equations of an expanded kinetic transport theory framework that will enable such a self-consistent description.
Modeling of dispersion near roadways based on the vehicle-induced turbulence concept

NASA Astrophysics Data System (ADS)

Sahlodin, Ali M.; Sotudeh-Gharebagh, Rahmat; Zhu, Yifang

A mathematical model is developed for dispersion near roadways by incorporating vehicle-induced turbulence (VIT) into Gaussian dispersion modeling using computational fluid dynamics (CFD). The model is based on the Gaussian plume equation in which roadway is regarded as a series of point sources. The Gaussian dispersion parameters are modified by simulation of the roadway using CFD in order to evaluate turbulent kinetic energy (TKE) as a measure of VIT. The model was evaluated against experimental carbon monoxide concentrations downwind of two major freeways reported in the literature. Good agreements were achieved between model results and the literature data. A significant difference was observed between the model results with and without considering VIT. The difference is rather high for data very close to the freeways. This model, after evaluation with additional data, may be used as a framework for predicting dispersion and deposition from any roadway for different traffic (vehicle type and speed) conditions.
Continuum-kinetic-microscopic model of lung clearance due to core-annular fluid entrainment

PubMed Central

Mitran, Sorin

2013-01-01

The human lung is protected against aspirated infectious and toxic agents by a thin liquid layer lining the interior of the airways. This airway surface liquid is a bilayer composed of a viscoelastic mucus layer supported by a fluid film known as the periciliary liquid. The viscoelastic behavior of the mucus layer is principally due to long-chain polymers known as mucins. The airway surface liquid is cleared from the lung by ciliary transport, surface tension gradients, and airflow shear forces. This work presents a multiscale model of the effect of airflow shear forces, as exerted by tidal breathing and cough, upon clearance. The composition of the mucus layer is complex and variable in time. To avoid the restrictions imposed by adopting a viscoelastic flow model of limited validity, a multiscale computational model is introduced in which the continuum-level properties of the airway surface liquid are determined by microscopic simulation of long-chain polymers. A bridge between microscopic and continuum levels is constructed through a kinetic-level probability density function describing polymer chain configurations. The overall multiscale framework is especially suited to biological problems due to the flexibility afforded in specifying microscopic constituents, and examining the effects of various constituents upon overall mucus transport at the continuum scale. PMID:23729842
Continuum-kinetic-microscopic model of lung clearance due to core-annular fluid entrainment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitran, Sorin, E-mail: mitran@unc.edu

2013-07-01

The human lung is protected against aspirated infectious and toxic agents by a thin liquid layer lining the interior of the airways. This airway surface liquid is a bilayer composed of a viscoelastic mucus layer supported by a fluid film known as the periciliary liquid. The viscoelastic behavior of the mucus layer is principally due to long-chain polymers known as mucins. The airway surface liquid is cleared from the lung by ciliary transport, surface tension gradients, and airflow shear forces. This work presents a multiscale model of the effect of airflow shear forces, as exerted by tidal breathing and cough,more » upon clearance. The composition of the mucus layer is complex and variable in time. To avoid the restrictions imposed by adopting a viscoelastic flow model of limited validity, a multiscale computational model is introduced in which the continuum-level properties of the airway surface liquid are determined by microscopic simulation of long-chain polymers. A bridge between microscopic and continuum levels is constructed through a kinetic-level probability density function describing polymer chain configurations. The overall multiscale framework is especially suited to biological problems due to the flexibility afforded in specifying microscopic constituents, and examining the effects of various constituents upon overall mucus transport at the continuum scale.« less
Continuum-kinetic-microscopic model of lung clearance due to core-annular fluid entrainment

NASA Astrophysics Data System (ADS)

Mitran, Sorin

2013-07-01

The human lung is protected against aspirated infectious and toxic agents by a thin liquid layer lining the interior of the airways. This airway surface liquid is a bilayer composed of a viscoelastic mucus layer supported by a fluid film known as the periciliary liquid. The viscoelastic behavior of the mucus layer is principally due to long-chain polymers known as mucins. The airway surface liquid is cleared from the lung by ciliary transport, surface tension gradients, and airflow shear forces. This work presents a multiscale model of the effect of airflow shear forces, as exerted by tidal breathing and cough, upon clearance. The composition of the mucus layer is complex and variable in time. To avoid the restrictions imposed by adopting a viscoelastic flow model of limited validity, a multiscale computational model is introduced in which the continuum-level properties of the airway surface liquid are determined by microscopic simulation of long-chain polymers. A bridge between microscopic and continuum levels is constructed through a kinetic-level probability density function describing polymer chain configurations. The overall multiscale framework is especially suited to biological problems due to the flexibility afforded in specifying microscopic constituents, and examining the effects of various constituents upon overall mucus transport at the continuum scale.
Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation.

PubMed

Getto, Philipp; Marciniak-Czochra, Anna

2015-01-01

Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.
Single-channel autocorrelation functions: the effects of time interval omission.

PubMed Central

Ball, F G; Sansom, M S

1988-01-01

We present a general mathematical framework for analyzing the dynamic aspects of single channel kinetics incorporating time interval omission. An algorithm for computing model autocorrelation functions, incorporating time interval omission, is described. We show, under quite general conditions, that the form of these autocorrelations is identical to that which would be obtained if time interval omission was absent. We also show, again under quite general conditions, that zero correlations are necessarily a consequence of the underlying gating mechanism and not an artefact of time interval omission. The theory is illustrated by a numerical study of an allosteric model for the gating mechanism of the locust muscle glutamate receptor-channel. PMID:2455553
PET image reconstruction: a robust state space approach.

PubMed

Liu, Huafeng; Tian, Yi; Shi, Pengcheng

2005-01-01

Statistical iterative reconstruction algorithms have shown improved image quality over conventional nonstatistical methods in PET by using accurate system response models and measurement noise models. Strictly speaking, however, PET measurements, pre-corrected for accidental coincidences, are neither Poisson nor Gaussian distributed and thus do not meet basic assumptions of these algorithms. In addition, the difficulty in determining the proper system response model also greatly affects the quality of the reconstructed images. In this paper, we explore the usage of state space principles for the estimation of activity map in tomographic PET imaging. The proposed strategy formulates the organ activity distribution through tracer kinetics models, and the photon-counting measurements through observation equations, thus makes it possible to unify the dynamic reconstruction problem and static reconstruction problem into a general framework. Further, it coherently treats the uncertainties of the statistical model of the imaging system and the noisy nature of measurement data. Since H(infinity) filter seeks minimummaximum-error estimates without any assumptions on the system and data noise statistics, it is particular suited for PET image reconstruction where the statistical properties of measurement data and the system model are very complicated. The performance of the proposed framework is evaluated using Shepp-Logan simulated phantom data and real phantom data with favorable results.
Building polyhedra by self-assembly: theory and experiment.

PubMed

Kaplan, Ryan; Klobušický, Joseph; Pandey, Shivendra; Gracias, David H; Menon, Govind

2014-01-01

We investigate the utility of a mathematical framework based on discrete geometry to model biological and synthetic self-assembly. Our primary biological example is the self-assembly of icosahedral viruses; our synthetic example is surface-tension-driven self-folding polyhedra. In both instances, the process of self-assembly is modeled by decomposing the polyhedron into a set of partially formed intermediate states. The set of all intermediates is called the configuration space, pathways of assembly are modeled as paths in the configuration space, and the kinetics and yield of assembly are modeled by rate equations, Markov chains, or cost functions on the configuration space. We review an interesting interplay between biological function and mathematical structure in viruses in light of this framework. We discuss in particular: (i) tiling theory as a coarse-grained description of all-atom models; (ii) the building game-a growth model for the formation of polyhedra; and (iii) the application of these models to the self-assembly of the bacteriophage MS2. We then use a similar framework to model self-folding polyhedra. We use a discrete folding algorithm to compute a configuration space that idealizes surface-tension-driven self-folding and analyze pathways of assembly and dominant intermediates. These computations are then compared with experimental observations of a self-folding dodecahedron with side 300 μm. In both models, despite a combinatorial explosion in the size of the configuration space, a few pathways and intermediates dominate self-assembly. For self-folding polyhedra, the dominant intermediates have fewer degrees of freedom than comparable intermediates, and are thus more rigid. The concentration of assembly pathways on a few intermediates with distinguished geometric properties is biologically and physically important, and suggests deeper mathematical structure.
Relativistic transport theory for a two-temperature magnetized plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Metens, T.; Balescu, R.

1990-09-01

The relativistic kinetic theory of linear transport is worked out within the framework of a new moment method. A complete analytical study of the transport in a two-temperature inhomogeneous magnetized fusion plasma is given. The transport relations and coefficients are derived from the kinetic equation with the full relativistic Beliaev--Budker collision operator and the impact of relativistic effects on the confinement are investigated.
Sorption Modeling and Verification for Off-Gas Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tavlarides, Lawrence; Yiacoumi, Sotira; Tsouris, Costas

2016-12-20

This project was successfully executed to provide valuable adsorption data and improve a comprehensive model developed in previous work by the authors. Data obtained were used in an integrated computer program to predict the behavior of adsorption columns. The model is supported by experimental data and has been shown to predict capture of off gas similar to that evolving during the reprocessing of nuclear waste. The computer program structure contains (a) equilibrium models of off-gases with the adsorbate; (b) mass-transfer models to describe off-gas mass transfer to a particle, diffusion through the pores of the particle, and adsorption on themore » active sites of the particle; and (c) incorporation of these models into fixed bed adsorption modeling, which includes advection through the bed. These models are being connected with the MOOSE (Multiphysics Object-Oriented Simulation Environment) software developed at the Idaho National Laboratory through DGOSPREY (Discontinuous Galerkin Off-gas SeParation and REcoverY) computer codes developed in this project. Experiments for iodine and water adsorption have been conducted on reduced silver mordenite (Ag0Z) for single layered particles. Adsorption apparatuses have been constructed to execute these experiments over a useful range of conditions for temperatures ranging from ambient to 250°C and water dew points ranging from -69 to 19°C. Experimental results were analyzed to determine mass transfer and diffusion of these gases into the particles and to determine which models best describe the single and binary component mass transfer and diffusion processes. The experimental results were also used to demonstrate the capabilities of the comprehensive models developed to predict single-particle adsorption and transients of the adsorption-desorption processes in fixed beds. Models for adsorption and mass transfer have been developed to mathematically describe adsorption kinetics and transport via diffusion and advection processes. These models were built on a numerical framework for solving conservation law problems in one-dimensional geometries such as spheres, cylinders, and lines. Coupled with the framework are specific models for adsorption in commercial adsorbents, such as zeolites and mordenites. Utilizing this modeling approach, the authors were able to accurately describe and predict adsorption kinetic data obtained from experiments at a variety of different temperatures and gas phase concentrations. A demonstration of how these models, and framework, can be used to simulate adsorption in fixed- bed columns is provided. The CO 2 absorption work involved modeling with supportive experimental information. A dynamic model was developed to simulate CO 2 absorption using high alkaline content water solutions. The model is based upon transient mass and energy balances for chemical species commonly present in CO 2 absorption. A computer code was developed to implement CO 2 absorption with a chemical reaction model. Experiments were conducted in a laboratory scale column to determine the model parameters. The influence of geometric parameters and operating variables on CO 2 absorption was studied over a wide range of conditions. Continuing work could employ the model to control column operation and predict the absorption behavior under various input conditions and other prescribed experimental perturbations. The value of the validated models and numerical frameworks developed in this project is that they can be used to predict the sorption behavior of off-gas evolved during the reprocessing of nuclear waste and thus reduce the cost of the experiments. They can also be used to design sorption processes based on concentration limits and flow-rates determined at the plant level.« less
Thermodynamic controls on the kinetics of microbial low-pH Fe(II) oxidation.

PubMed

Larson, Lance N; Sánchez-España, Javier; Kaley, Bradley; Sheng, Yizhi; Bibby, Kyle; Burgos, William D

2014-08-19

Acid mine drainage (AMD) is a major worldwide environmental threat to surface and groundwater quality. Microbial low-pH Fe(II) oxidation could be exploited for cost-effective AMD treatment; however, its use is limited because of uncertainties associated with its rate and ability to remove Fe from solution. We developed a thermodynamic-based framework to evaluate the kinetics of low-pH Fe(II) oxidation. We measured the kinetics of low-pH Fe(II) oxidation at five sites in the Appalachian Coal Basin in the US and three sites in the Iberian Pyrite Belt in Spain and found that the fastest rates of Fe(II) oxidation occurred at the sites with the lowest pH values. Thermodynamic calculations showed that the Gibbs free energy of Fe(II) oxidation (ΔG(oxidation)) was also most negative at the sites with the lowest pH values. We then conducted two series of microbial Fe(II) oxidation experiments in laboratory-scale chemostatic bioreactors operated through a series of pH values (2.1-4.2) and found the same relationships between Fe(II) oxidation kinetics, ΔG(oxidation), and pH. Conditions that favored the fastest rates of Fe(II) oxidation coincided with higher Fe(III) solubility. The solubility of Fe(III) minerals, thus plays an important role on Fe(II) oxidation kinetics. Methods to incorporate microbial low-pH Fe(II) oxidation into active and passive AMD treatment systems are discussed in the context of these findings. This study presents a simplified model that describes the relationship between free energy and microbial kinetics and should be broadly applicable to many biogeochemical systems.
KMCLib 1.1: Extended random number support and technical updates to the KMCLib general framework for kinetic Monte-Carlo simulations

NASA Astrophysics Data System (ADS)

Leetmaa, Mikael; Skorodumova, Natalia V.

2015-11-01

We here present a revised version, v1.1, of the KMCLib general framework for kinetic Monte-Carlo (KMC) simulations. The generation of random numbers in KMCLib now relies on the C++11 standard library implementation, and support has been added for the user to choose from a set of C++11 implemented random number generators. The Mersenne-twister, the 24 and 48 bit RANLUX and a 'minimal-standard' PRNG are supported. We have also included the possibility to use true random numbers via the C++11 std::random_device generator. This release also includes technical updates to support the use of an extended range of operating systems and compilers.
Genotype-specific relationships among phosphorus use, growth and abundance in Daphnia pulicaria

PubMed Central

Chowdhury, Priyanka Roy; Baker, Kristina D.; Weider, Lawrence J.; Jeyasingh, Punidan D.

2017-01-01

The framework ecological stoichiometry uses elemental composition of species to make predictions about growth and competitive ability in defined elemental supply conditions. Although intraspecific differences in stoichiometry have been observed, we have yet to understand the mechanisms generating and maintaining such variation. We used variation in phosphorus (P) content within a Daphnia species to test the extent to which %P can explain variation in growth and competition. Further, we measured 33P kinetics (acquisition, assimilation, incorporation and retention) to understand the extent to which such variables improved predictions. Genotypes showed significant variation in P content, 33P kinetics and growth rate. P content alone was a poor predictor of growth rate and competitive ability. While most genotypes exhibited the typical growth penalty under P limitation, a few varied little in growth between P diets. These observations indicate that some genotypes can maintain growth under P-limited conditions by altering P use, suggesting that decomposing P content of an individual into physiological components of P kinetics will improve stoichiometric models. More generally, attention to the interplay between nutrient content and nutrient-use is required to make inferences regarding the success of genotypes in defined conditions of nutrient supply. PMID:29308224
Hard versus soft dynamics for adsorption-desorption kinetics: Exact results in one-dimension.

PubMed

Manzi, S J; Huespe, V J; Belardinelli, R E; Pereyra, V D

2009-11-01

The adsorption-desorption kinetics is discussed in the framework of the kinetic lattice-gas model. The master equation formalism has been introduced to describe the evolution of the system, where the transition probabilities are written as an expansion of the occupation configurations of all neighboring sites. Since the detailed balance principle determines half of the coefficients that arise from the expansion, it is necessary to introduce ad hoc, a dynamic scheme to get the rest of them. Three schemes of the so-called hard dynamics, in which the probability of transition from single site cannot be factored into a part which depends only on the interaction energy and one that only depends on the field energy, and five schemes of the so-called soft dynamics, in which this factorization is possible, were introduced for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and nonequilibrium observables, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and nonequilibrium observables have several problems. Some of them can be regarded as abnormal behavior.
A kinetic approach to some quasi-linear laws of macroeconomics

NASA Astrophysics Data System (ADS)

Gligor, M.; Ignat, M.

2002-11-01

Some previous works have presented the data on wealth and income distributions in developed countries and have found that the great majority of population is described by an exponential distribution, which results in idea that the kinetic approach could be adequate to describe this empirical evidence. The aim of our paper is to extend this framework by developing a systematic kinetic approach of the socio-economic systems and to explain how linear laws, modelling correlations between macroeconomic variables, may arise in this context. Firstly we construct the Boltzmann kinetic equation for an idealised system composed by many individuals (workers, officers, business men, etc.), each of them getting a certain income and spending money for their needs. To each individual a certain time variable amount of money is associated this meaning him/her phase space coordinate. In this way the exponential distribution of money in a closed economy is explicitly found. The extension of this result, including states near the equilibrium, give us the possibility to take into account the regular increase of the total amount of money, according to the modern economic theories. The Kubo-Green-Onsager linear response theory leads us to a set of linear equations between some macroeconomic variables. Finally, the validity of such laws is discussed in relation with the time reversal symmetry and is tested empirically using some macroeconomic time series.
A thermodynamic framework for thermo-chemo-elastic interactions in chemically active materials

NASA Astrophysics Data System (ADS)

Zhang, XiaoLong; Zhong, Zheng

2017-08-01

In this paper, a general thermodynamic framework is developed to describe the thermo-chemo-mechanical interactions in elastic solids undergoing mechanical deformation, imbibition of diffusive chemical species, chemical reactions and heat exchanges. Fully coupled constitutive relations and evolving laws for irreversible fluxes are provided based on entropy imbalance and stoichiometry that governs reactions. The framework manifests itself with a special feature that the change of Helmholtz free energy is attributed to separate contributions of the diffusion-swelling process and chemical reaction-dilation process. Both the extent of reaction and the concentrations of diffusive species are taken as independent state variables, which describe the reaction-activated responses with underlying variation of microstructures and properties of a material in an explicit way. A specialized isothermal formulation for isotropic materials is proposed that can properly account for volumetric constraints from material incompressibility under chemo-mechanical loadings, in which inhomogeneous deformation is associated with reaction and diffusion under various kinetic time scales. This framework can be easily applied to model the transient volumetric swelling of a solid caused by imbibition of external chemical species and simultaneous chemical dilation arising from reactions between the diffusing species and the solid.

Computational membrane biophysics: From ion channel interactions with drugs to cellular function.

PubMed

Miranda, Williams E; Ngo, Van A; Perissinotti, Laura L; Noskov, Sergei Yu

2017-11-01

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.
Water bag modeling of a multispecies plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morel, P.; Gravier, E.; Besse, N.

2011-03-15

We report in the present paper a new modeling method to study multiple species dynamics in magnetized plasmas. Such a method is based on the gyrowater bag modeling, which consists in using a multistep-like distribution function along the velocity direction parallel to the magnetic field. The choice of a water bag representation allows an elegant link between kinetic and fluid descriptions of a plasma. The gyrowater bag model has been recently adapted to the context of strongly magnetized plasmas. We present its extension to the case of multi ion species magnetized plasmas: each ion species being modeled via a multiwatermore » bag distribution function. The water bag modelization will be discussed in details, under the simplification of a cylindrical geometry that is convenient for linear plasma devices. As an illustration, results obtained in the linear framework for ion temperature gradient instabilities are presented, that are shown to agree qualitatively with older works.« less
Numerical modelling in biosciences using delay differential equations

NASA Astrophysics Data System (ADS)

Bocharov, Gennadii A.; Rihan, Fathalla A.

2000-12-01

Our principal purposes here are (i) to consider, from the perspective of applied mathematics, models of phenomena in the biosciences that are based on delay differential equations and for which numerical approaches are a major tool in understanding their dynamics, (ii) to review the application of numerical techniques to investigate these models. We show that there are prima facie reasons for using such models: (i) they have a richer mathematical framework (compared with ordinary differential equations) for the analysis of biosystem dynamics, (ii) they display better consistency with the nature of certain biological processes and predictive results. We analyze both the qualitative and quantitative role that delays play in basic time-lag models proposed in population dynamics, epidemiology, physiology, immunology, neural networks and cell kinetics. We then indicate suitable computational techniques for the numerical treatment of mathematical problems emerging in the biosciences, comparing them with those implemented by the bio-modellers.
Predicting crystal growth via a unified kinetic three-dimensional partition model

NASA Astrophysics Data System (ADS)

Anderson, Michael W.; Gebbie-Rayet, James T.; Hill, Adam R.; Farida, Nani; Attfield, Martin P.; Cubillas, Pablo; Blatov, Vladislav A.; Proserpio, Davide M.; Akporiaye, Duncan; Arstad, Bjørnar; Gale, Julian D.

2017-04-01

Understanding and predicting crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for more than one hundred years, it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopy. To organize and understand this large amount of new information, new rules for crystal growth need to be developed and tested. However, because of the complexity and variety of different crystal systems, attempts to understand crystal growth in detail have so far relied on developing models that are usually applicable to only one system. Such models cannot be used to achieve the wide scope of understanding that is required to create a unified model across crystal types and crystal structures. Here we describe a general approach to understanding and, in theory, predicting the growth of a wide range of crystal types, including the incorporation of defect structures, by simultaneous molecular-scale simulation of crystal habit and surface topology using a unified kinetic three-dimensional partition model. This entails dividing the structure into ‘natural tiles’ or Voronoi polyhedra that are metastable and, consequently, temporally persistent. As such, these units are then suitable for re-construction of the crystal via a Monte Carlo algorithm. We demonstrate our approach by predicting the crystal growth of a diverse set of crystal types, including zeolites, metal-organic frameworks, calcite, urea and L-cystine.
Electrodiffusion: a continuum modeling framework for biomolecular systems with realistic spatiotemporal resolution.

PubMed

Lu, Benzhuo; Zhou, Y C; Huber, Gary A; Bond, Stephen D; Holst, Michael J; McCammon, J Andrew

2007-10-07

A computational framework is presented for the continuum modeling of cellular biomolecular diffusion influenced by electrostatic driving forces. This framework is developed from a combination of state-of-the-art numerical methods, geometric meshing, and computer visualization tools. In particular, a hybrid of (adaptive) finite element and boundary element methods is adopted to solve the Smoluchowski equation (SE), the Poisson equation (PE), and the Poisson-Nernst-Planck equation (PNPE) in order to describe electrodiffusion processes. The finite element method is used because of its flexibility in modeling irregular geometries and complex boundary conditions. The boundary element method is used due to the convenience of treating the singularities in the source charge distribution and its accurate solution to electrostatic problems on molecular boundaries. Nonsteady-state diffusion can be studied using this framework, with the electric field computed using the densities of charged small molecules and mobile ions in the solvent. A solution for mesh generation for biomolecular systems is supplied, which is an essential component for the finite element and boundary element computations. The uncoupled Smoluchowski equation and Poisson-Boltzmann equation are considered as special cases of the PNPE in the numerical algorithm, and therefore can be solved in this framework as well. Two types of computations are reported in the results: stationary PNPE and time-dependent SE or Nernst-Planck equations solutions. A biological application of the first type is the ionic density distribution around a fragment of DNA determined by the equilibrium PNPE. The stationary PNPE with nonzero flux is also studied for a simple model system, and leads to an observation that the interference on electrostatic field of the substrate charges strongly affects the reaction rate coefficient. The second is a time-dependent diffusion process: the consumption of the neurotransmitter acetylcholine by acetylcholinesterase, determined by the SE and a single uncoupled solution of the Poisson-Boltzmann equation. The electrostatic effects, counterion compensation, spatiotemporal distribution, and diffusion-controlled reaction kinetics are analyzed and different methods are compared.
Water age and stream solute dynamics at the Hubbard Brook Experimental Forest (US)

NASA Astrophysics Data System (ADS)

Botter, Gianluca; Benettin, Paolo; McGuire, Kevin; Rinaldo, Andrea

2016-04-01

The contribution discusses experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (New Hampshire, USA) to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is used to model both conservative and weathering-derived solutes. Based on the available information about the hydrology of the site, an integrated transport model was developed and used to estimate the relevant hydrochemical fluxes. The model was designed to reproduce the deuterium content of streamflow and allowed for the estimate of catchment water storage and dynamic travel time distributions (TTDs). Within this framework, dissolved silicon and sodium concentration in streamflow were simulated by implementing first-order chemical kinetics based explicitly on dynamic TTD, thus upscaling local geochemical processes to catchment scale. Our results highlight the key role of water stored within the subsoil glacial material in both the short-term and long-term solute circulation at Hubbard Brook. The analysis of the results provided by the calibrated model allowed a robust estimate of the emerging concentration-discharge relationship, streamflow age distributions (including the fraction of event water) and storage size, and their evolution in time due to hydrologic variability.
A Quantitative Theoretical Framework For Protein-Induced Fluorescence Enhancement-Förster-Type Resonance Energy Transfer (PIFE-FRET).

PubMed

Lerner, Eitan; Ploetz, Evelyn; Hohlbein, Johannes; Cordes, Thorben; Weiss, Shimon

2016-07-07

Single-molecule, protein-induced fluorescence enhancement (PIFE) serves as a molecular ruler at molecular distances inaccessible to other spectroscopic rulers such as Förster-type resonance energy transfer (FRET) or photoinduced electron transfer. In order to provide two simultaneous measurements of two distances on different molecular length scales for the analysis of macromolecular complexes, we and others recently combined measurements of PIFE and FRET (PIFE-FRET) on the single molecule level. PIFE relies on steric hindrance of the fluorophore Cy3, which is covalently attached to a biomolecule of interest, to rotate out of an excited-state trans isomer to the cis isomer through a 90° intermediate. In this work, we provide a theoretical framework that accounts for relevant photophysical and kinetic parameters of PIFE-FRET, show how this framework allows the extraction of the fold-decrease in isomerization mobility from experimental data, and show how these results provide information on changes in the accessible volume of Cy3. The utility of this model is then demonstrated for experimental results on PIFE-FRET measurement of different protein-DNA interactions. The proposed model and extracted parameters could serve as a benchmark to allow quantitative comparison of PIFE effects in different biological systems.
Consideration of HOMs in α- and β-pinene SOA model

NASA Astrophysics Data System (ADS)

Gatzsche, Kathrin; Iinuma, Yoshiteru; Mutzel, Anke; Berndt, Torsten; Wolke, Ralf

2016-04-01

Secondary organic aerosol (SOA) is the major burden of the atmospheric organic particulate matter with 140 - 910 TgC yr-1 (Hallquist et al., 2009). SOA particles are formed via the oxidation of volatile organic carbons (VOCs), where the volatility of the VOCs is lowered due to the increase in their functionalization as well as their binding ability. Therefore, gaseous compounds can either nucleate to form new particles or condense on existing particles. The framework of SOA formation under natural conditions is very complex, because there are a multitude of gas-phase precursors, atmospheric degradation processes and products after oxidation. A lacking understanding about chemical and physical processes associated with SOA formation makes modeling of SOA processes difficult, leading to discrepancy between measured and modeled global SOA burdens. The present study utilizes a parcel model SPACCIM (SPectral Aerosol Cloud Chemistry Interaction Model, Wolke et al., 2005) that couples a multiphase chemical model with a microphysical model. For SOA modeling a further development of SPACCIM was necessary. Therefore, two components are added (i) a gas-phase chemistry mechanism for the VOC oxidation and (ii) a partitioning approach for the gas-to-particle phase transfer. An aggregated gas-phase chemistry mechanism for α- and β-pinene was adapted from Chen and Griffin (2005). For the phase transfer an absorptive partitioning approach (Pankow, 1994) and a kinetic approach (Zaveri et al., 2014) are implemented. Whereby the kinetic approach serves some advantages. The organic aerosol can be resolved in different size sections, whereby the particle radius is involved in the partitioning equations. The phase state of the organic material and the reactivity of the organic compounds in the particle-phase directly influence the modeled SOA yields. Recently, highly oxidized multifunctional organic compounds (HOMs) were found in the gas phase from lab and field studies. They are also known as extremely low-volatile organic compounds (ELVOCs) (Ehn et al. 2014). The importance of HOMs for the early aerosol growth makes them indispensable in SOA modeling. Thus, we included HOMs in our model framework. The measurements from the institute's own smog chamber LEAK are used as a base for model evaluation and process analysis, especially since HOMs were lately identified from LEAK data (Mutzel et al., 2015). The presentation will provide a sensitivity study for the kinetic approach as well as a comparison of measured and modeled SOA yields. References: Ehn, M., Thornton, J. A., Kleist, E. et al. (2014) Nature, 506, 476 - 479 Hallquist, M., Wenger, J. C., Baltensperger, U., et al. (2009) Atmos. Chem. Phys., 9, 5155 - 5236 Mutzel, A., Poulain, L., Berndt, T. et al. (2015) Environ. Sci. Technol., 49, 7754 - 7761 Pankow, J. F. (1994) Atmos. Environ., 28, 2, 189 - 193 Wolke, R., Sehili, A. M., Simmel, M., Knoth, O., Tilgner, A. and Herrmann, H. (2005) Atmos. Environ., 39, 4375 - 4388 Zaveri, R. A., Easter, R. C., Shilling J. E. and Seinfeld, J. H. (2014) Atmos. Chem. Phys., 14, 5153 - 5181
Presenting a new kinetic model for methanol to light olefins reactions over a hierarchical SAPO-34 catalyst using the Langmuir-Hinshelwood-Hougen-Watson mechanism

NASA Astrophysics Data System (ADS)

Javad Azarhoosh, Mohammad; Halladj, Rouein; Askari, Sima

2017-10-01

In this study, a new kinetic model for methanol to light olefins (MTO) reactions over a hierarchical SAPO-34 catalyst using the Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism was presented and the kinetic parameters was obtained using a genetic algorithm (GA) and genetic programming (GP). Several kinetic models for the MTO reactions have been presented. However, due to the complexity of the reactions, most reactions are considered lumped and elementary, which cannot be deemed a completely accurate kinetic model of the process. Therefore, in this study, the LHHW mechanism is presented as kinetic models of MTO reactions. Because of the non-linearity of the kinetic models and existence of many local optimal points, evolutionary algorithms (GA and GP) are used in this study to estimate the kinetic parameters in the rate equations. Via the simultaneous connection of the code related to modelling the reactor and the GA and GP codes in the MATLAB R2013a software, optimization of the kinetic models parameters was performed such that the least difference between the results from the kinetic models and experiential results was obtained and the best kinetic parameters of MTO process reactions were achieved. A comparison of the results from the model with experiential results showed that the present model possesses good accuracy.
Study of reactive collisions between electrons and molecular cations using multichannel quantum defect theory: Application to HD{sup +} and BeH{sup +}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pop, N., E-mail: nicolina.pop@upt.ro; Ilie, S.; Motapon, O.

2014-11-24

The present work is aimed at performing the computation of cross sections and Maxwell rate coefficients in the framework of the stepwise version of the Multichannel Quantum Defect Theory (MQDT). Cross sections and rate coefficients suitable for the modelling of the kinetics of HD{sup +} and BeH{sup +} in fusion plasmas and in the stellar atmospheres are presented and discussed. A very good agreement is found between our results for rotational transitions for HD{sup +} and other computations, as well as with experiment.
Modeling aerosol surface chemistry and gas-particle interaction kinetics with K2-SURF: PAH oxidation

NASA Astrophysics Data System (ADS)

Shiraiwa, M.; Garland, R.; Pöschl, U.

2009-04-01

Atmospheric aerosols are ubiquitous in the atmosphere. They have the ability to impact cloud properties, radiative balance and provide surfaces for heterogeneous reactions. The uptake of gaseous species on aerosol surfaces impacts both the aerosol particles and the atmospheric budget of trace gases. These subsequent changes to the aerosol can in turn impact the aerosol chemical and physical properties. However, this uptake, as well as the impact on the aerosol, is not fully understood. This uncertainty is due not only to limited measurement data, but also a dearth of comprehensive and applicable modeling formalizations used for the analysis, interpretation and description of these heterogeneous processes. Without a common model framework, comparing and extrapolating experimental data is difficult. In this study, a novel kinetic surface model (K2-SURF) [Ammann & Pöschl, 2007; Pöschl et al., 2007] was used to describe the oxidation of a variety of polycyclic aromatic hydrocarbons (PAHs). Integrated into this consistent and universally applicable kinetic and thermodynamic process model are the concepts, terminologies and mathematical formalizations essential to the description of atmospherically relevant physicochemical processes involving organic and mixed organic-inorganic aerosols. Within this process model framework, a detailed master mechanism, simplified mechanism and parameterizations of atmospheric aerosol chemistry are being developed and integrated in analogy to existing mechanisms and parameterizations of atmospheric gas-phase chemistry. One of the key aspects to this model is the defining of a clear distinction between various layers of the particle and surrounding gas phase. The processes occurring at each layer can be fully described using known fluxes and kinetic parameters. Using this system there is a clear separation of gas phase, gas-surface and surface bulk transport and reactions. The partitioning of compounds can be calculated using the flux values between the layers. By describing these layers unambiguously, the interactions of all species in the system can be appropriately modeled. In describing the oxidation of PAHs, the focus was on the interactions between the sorption layer and quasi-static surface layer. The results from a variety of published experimental studies [Pöschl et al., 2001; Kahan et al., 2006; Kwamena et al., 2004, 2006, 2007; Mmereki and Donaldson, 2003; Mmereki et al., 2004; Dubowski et al., 2004; Donaldson et al., 2005; Segal-Rosenheimer and Dubowski, 2007] were analyzed and compared utilizing K2-SURF. The heterogeneous reaction of PAH and O3 are found to follow a Langmuir-Hinshelwood mechanism, in which ozone first absorbs to the surface and then reacts with PAH. The Langmuir equilibrium constants and second-order-rate coefficients of surface reaction were estimated. In PAH/O3/solid substrate system, they showed similar reaction rate (×10), but large difference (×1000) in adsorption. The mean residence time and adsorption enthalpy were estimated for O3 at the surface of substrates, suggesting the chemisorption of O3 molecules or O atoms, respectively. Initial uptake coefficients of O3 under different conditions were also investigated. The observed dependence on gas-phase O3 concentration was well explained with K2-SURF model in five-order range. In addition, competitive adsorption of other gas phase species (NO2, H2O) was well described by the model. Possible mechanism of PAH degradation system and atmospheric implications are discussed.
Development of an Uncertainty Quantification Predictive Chemical Reaction Model for Syngas Combustion

DOE PAGES

Slavinskaya, N. A.; Abbasi, M.; Starcke, J. H.; ...

2017-01-24

An automated data-centric infrastructure, Process Informatics Model (PrIMe), was applied to validation and optimization of a syngas combustion model. The Bound-to-Bound Data Collaboration (B2BDC) module of PrIMe was employed to discover the limits of parameter modifications based on uncertainty quantification (UQ) and consistency analysis of the model–data system and experimental data, including shock-tube ignition delay times and laminar flame speeds. Existing syngas reaction models are reviewed, and the selected kinetic data are described in detail. Empirical rules were developed and applied to evaluate the uncertainty bounds of the literature experimental data. Here, the initial H 2/CO reaction model, assembled frommore » 73 reactions and 17 species, was subjected to a B2BDC analysis. For this purpose, a dataset was constructed that included a total of 167 experimental targets and 55 active model parameters. Consistency analysis of the composed dataset revealed disagreement between models and data. Further analysis suggested that removing 45 experimental targets, 8 of which were self-inconsistent, would lead to a consistent dataset. This dataset was subjected to a correlation analysis, which highlights possible directions for parameter modification and model improvement. Additionally, several methods of parameter optimization were applied, some of them unique to the B2BDC framework. The optimized models demonstrated improved agreement with experiments compared to the initially assembled model, and their predictions for experiments not included in the initial dataset (i.e., a blind prediction) were investigated. The results demonstrate benefits of applying the B2BDC methodology for developing predictive kinetic models.« less
Development of an Uncertainty Quantification Predictive Chemical Reaction Model for Syngas Combustion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slavinskaya, N. A.; Abbasi, M.; Starcke, J. H.

An automated data-centric infrastructure, Process Informatics Model (PrIMe), was applied to validation and optimization of a syngas combustion model. The Bound-to-Bound Data Collaboration (B2BDC) module of PrIMe was employed to discover the limits of parameter modifications based on uncertainty quantification (UQ) and consistency analysis of the model–data system and experimental data, including shock-tube ignition delay times and laminar flame speeds. Existing syngas reaction models are reviewed, and the selected kinetic data are described in detail. Empirical rules were developed and applied to evaluate the uncertainty bounds of the literature experimental data. Here, the initial H 2/CO reaction model, assembled frommore » 73 reactions and 17 species, was subjected to a B2BDC analysis. For this purpose, a dataset was constructed that included a total of 167 experimental targets and 55 active model parameters. Consistency analysis of the composed dataset revealed disagreement between models and data. Further analysis suggested that removing 45 experimental targets, 8 of which were self-inconsistent, would lead to a consistent dataset. This dataset was subjected to a correlation analysis, which highlights possible directions for parameter modification and model improvement. Additionally, several methods of parameter optimization were applied, some of them unique to the B2BDC framework. The optimized models demonstrated improved agreement with experiments compared to the initially assembled model, and their predictions for experiments not included in the initial dataset (i.e., a blind prediction) were investigated. The results demonstrate benefits of applying the B2BDC methodology for developing predictive kinetic models.« less
Numerical methods for solving moment equations in kinetic theory of neuronal network dynamics

NASA Astrophysics Data System (ADS)

Rangan, Aaditya V.; Cai, David; Tao, Louis

2007-02-01

Recently developed kinetic theory and related closures for neuronal network dynamics have been demonstrated to be a powerful theoretical framework for investigating coarse-grained dynamical properties of neuronal networks. The moment equations arising from the kinetic theory are a system of (1 + 1)-dimensional nonlinear partial differential equations (PDE) on a bounded domain with nonlinear boundary conditions. The PDEs themselves are self-consistently specified by parameters which are functions of the boundary values of the solution. The moment equations can be stiff in space and time. Numerical methods are presented here for efficiently and accurately solving these moment equations. The essential ingredients in our numerical methods include: (i) the system is discretized in time with an implicit Euler method within a spectral deferred correction framework, therefore, the PDEs of the kinetic theory are reduced to a sequence, in time, of boundary value problems (BVPs) with nonlinear boundary conditions; (ii) a set of auxiliary parameters is introduced to recast the original BVP with nonlinear boundary conditions as BVPs with linear boundary conditions - with additional algebraic constraints on the auxiliary parameters; (iii) a careful combination of two Newton's iterates for the nonlinear BVP with linear boundary condition, interlaced with a Newton's iterate for solving the associated algebraic constraints is constructed to achieve quadratic convergence for obtaining the solutions with self-consistent parameters. It is shown that a simple fixed-point iteration can only achieve a linear convergence for the self-consistent parameters. The practicability and efficiency of our numerical methods for solving the moment equations of the kinetic theory are illustrated with numerical examples. It is further demonstrated that the moment equations derived from the kinetic theory of neuronal network dynamics can very well capture the coarse-grained dynamical properties of integrate-and-fire neuronal networks.
Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

PubMed

Cotten, Cameron; Reed, Jennifer L

2013-01-30

Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets.
Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

PubMed Central

2013-01-01

Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets. PMID:23360254
Flexible and porous cellulose aerogels/zeolitic imidazolate framework (ZIF-8) hybrids for adsorption removal of Cr(IV) from water

NASA Astrophysics Data System (ADS)

Bo, Shaoguo; Ren, Wenjing; Lei, Chao; Xie, Yuanbo; Cai, Yurong; Wang, Shunli; Gao, Junkuo; Ni, Qingqing; Yao, Juming

2018-06-01

The low cost of adsorption treatment of heavy metal ions in water has been extensively studied. In this paper, we have demonstrated a facile method of combining two emerging materials cellulose aerogels (CA) and metal-organic frameworks (MOFs) into one highly functional aerogel to adsorption removal of heavy metal ions from water, by entrapping MOF particles into a flexible and porous CA. The resultant hybrid cellulose aerogels had a highly porous structure with zeolitic imidazolate framework-8 (ZIF-8) loadings can reach 30 wt%. The hybrid cellulose aerogels (named as ZIF-8@CA) show good adsorption capacity for Cr(Ⅵ). The adsorption process of ZIF-8@CA is better described by pseudo-second-order kinetic model and Langmuir isotherm, with maximum monolayer adsorption capacity of 41.8 mg g-1 for Cr(Ⅵ), whose adsorption capacity has greatly improved when compared with a single CA or ZIF-8. Thus, such a flexible and durable hybrid cellulose aerogel is a very prospective material for metal ions cleanup and industrial wastewater purification.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Tribble, G.W.

A combination of field and theoretical work is used to study controls on the saturation state of aragonite inside a coral-reef framework. A closed-system ion-speciation model is used to evaluate the effect of organic-matter oxidation on the saturation state of aragonite. The aragonite saturation state initially drops below 1 but becomes oversaturated during sulfate reduction. The C:N ratio of the organic matter affects the degree of oversaturation with N-poor organic material resulting in a system more corrosive to aragonite. Precipitation of sulfide as FeS strongly affects the aragonite saturation state, and systems with much FeS formation will have a strongermore » tendency to become oversaturated with respect to aragonite. Both precipitation and dissolution of aragonite are predicted at different stages of the organic reaction pathway if the model system is maintained at aragonite saturation. Field data from a coral-reef framework indicate that the system maintains itself at aragonite saturation, and model-predicted changes in dissolved calcium follow those observed in the interstitial waters of the reef. Aragonite probably acts as a solid-phase buffer in regulating the pH of interstitial waters. Because interstitial water in the reef has a short residence time, the observed equilibration suggests rapid kinetics.« less
Active mechanics in living oocytes reveal molecular-scale force kinetics

NASA Astrophysics Data System (ADS)

Ahmed, Wylie; Fodor, Etienne; Almonacid, Maria; Bussonnier, Matthias; Verlhac, Marie-Helene; Gov, Nir; Visco, Paolo; van Wijland, Frederic; Betz, Timo

Unlike traditional materials, living cells actively generate forces at the molecular scale that change their structure and mechanical properties. This nonequilibrium activity is essential for cellular function, and drives processes such as cell division. Single molecule studies have uncovered the detailed force kinetics of isolated motor proteins in-vitro, however their behavior in-vivo has been elusive due to the complex environment inside the cell. Here, we quantify active forces and intracellular mechanics in living oocytes using in-vivo optical trapping and laser interferometry of endogenous vesicles. We integrate an experimental and theoretical framework to connect mesoscopic measurements of nonequilibrium properties to the underlying molecular- scale force kinetics. Our results show that force generation by myosin-V drives the cytoplasmic-skeleton out-of-equilibrium (at frequencies below 300 Hz) and actively softens the environment. In vivo myosin-V activity generates a force of F ~ 0 . 4 pN, with a power-stroke of length Δx ~ 20 nm and duration τ ~ 300 μs, that drives vesicle motion at vv ~ 320 nm/s. This framework is widely applicable to characterize living cells and other soft active materials.
Collective behaviours: from biochemical kinetics to electronic circuits.

PubMed

Agliari, Elena; Barra, Adriano; Burioni, Raffaella; Di Biasio, Aldo; Uguzzoni, Guido

2013-12-10

In this work we aim to highlight a close analogy between cooperative behaviors in chemical kinetics and cybernetics; this is realized by using a common language for their description, that is mean-field statistical mechanics. First, we perform a one-to-one mapping between paradigmatic behaviors in chemical kinetics (i.e., non-cooperative, cooperative, ultra-sensitive, anti-cooperative) and in mean-field statistical mechanics (i.e., paramagnetic, high and low temperature ferromagnetic, anti-ferromagnetic). Interestingly, the statistical mechanics approach allows a unified, broad theory for all scenarios and, in particular, Michaelis-Menten, Hill and Adair equations are consistently recovered. This framework is then tested against experimental biological data with an overall excellent agreement. One step forward, we consistently read the whole mapping from a cybernetic perspective, highlighting deep structural analogies between the above-mentioned kinetics and fundamental bricks in electronics (i.e. operational amplifiers, flashes, flip-flops), so to build a clear bridge linking biochemical kinetics and cybernetics.

Collective behaviours: from biochemical kinetics to electronic circuits

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Burioni, Raffaella; di Biasio, Aldo; Uguzzoni, Guido

2013-12-01

In this work we aim to highlight a close analogy between cooperative behaviors in chemical kinetics and cybernetics; this is realized by using a common language for their description, that is mean-field statistical mechanics. First, we perform a one-to-one mapping between paradigmatic behaviors in chemical kinetics (i.e., non-cooperative, cooperative, ultra-sensitive, anti-cooperative) and in mean-field statistical mechanics (i.e., paramagnetic, high and low temperature ferromagnetic, anti-ferromagnetic). Interestingly, the statistical mechanics approach allows a unified, broad theory for all scenarios and, in particular, Michaelis-Menten, Hill and Adair equations are consistently recovered. This framework is then tested against experimental biological data with an overall excellent agreement. One step forward, we consistently read the whole mapping from a cybernetic perspective, highlighting deep structural analogies between the above-mentioned kinetics and fundamental bricks in electronics (i.e. operational amplifiers, flashes, flip-flops), so to build a clear bridge linking biochemical kinetics and cybernetics.
Nucleation theory with delayed interactions: An application to the early stages of the receptor-mediated adhesion/fusion kinetics of lipid vesicles

NASA Astrophysics Data System (ADS)

Raudino, Antonio; Pannuzzo, Martina

2010-01-01

A semiquantitative theory aimed to describe the adhesion kinetics between soft objects, such as living cells or vesicles, has been developed. When rigid bodies are considered, the adhesion kinetics is successfully described by the classical Derjaguin, Landau, Verwey, and Overbeek (DLVO) picture, where the energy profile of two approaching bodies is given by a two asymmetrical potential wells separated by a barrier. The transition probability from the long-distance to the short-distance minimum defines the adhesion rate. Conversely, soft bodies might follow a different pathway to reach the short-distance minimum: thermally excited fluctuations give rise to local protrusions connecting the approaching bodies. These transient adhesion sites are stabilized by short-range adhesion forces (e.g., ligand-receptor interactions between membranes brought at contact distance), while they are destabilized both by repulsive forces and by the elastic deformation energy. Above a critical area of the contact site, the adhesion forces prevail: the contact site grows in size until the complete adhesion of the two bodies inside a short-distance minimum is attained. This nucleation mechanism has been developed in the framework of a nonequilibrium Fokker-Planck picture by considering both the adhesive patch growth and dissolution processes. In addition, we also investigated the effect of the ligand-receptor pairing kinetics at the adhesion site in the time course of the patch expansion. The ratio between the ligand-receptor pairing kinetics and the expansion rate of the adhesion site is of paramount relevance in determining the overall nucleation rate. The theory enables one to self-consistently include both thermodynamics (energy barrier height) and dynamic (viscosity) parameters, giving rise in some limiting cases to simple analytical formulas. The model could be employed to rationalize fusion kinetics between vesicles, provided the short-range adhesion transition is the rate-limiting step to the whole adhesion process. Approximate relationships between the experimental fusion rates reported in the literature and parameters such as membrane elastic bending modulus, repulsion strength, temperature, osmotic forces, ligand-receptor binding energy, solvent and membrane viscosities are satisfactory explained by our model. The present results hint a possible role of the initial long-distance→short-distance transition in determining the whole fusion kinetics.
Nucleation theory with delayed interactions: an application to the early stages of the receptor-mediated adhesion/fusion kinetics of lipid vesicles.

PubMed

Raudino, Antonio; Pannuzzo, Martina

2010-01-28

A semiquantitative theory aimed to describe the adhesion kinetics between soft objects, such as living cells or vesicles, has been developed. When rigid bodies are considered, the adhesion kinetics is successfully described by the classical Derjaguin, Landau, Verwey, and Overbeek (DLVO) picture, where the energy profile of two approaching bodies is given by a two asymmetrical potential wells separated by a barrier. The transition probability from the long-distance to the short-distance minimum defines the adhesion rate. Conversely, soft bodies might follow a different pathway to reach the short-distance minimum: thermally excited fluctuations give rise to local protrusions connecting the approaching bodies. These transient adhesion sites are stabilized by short-range adhesion forces (e.g., ligand-receptor interactions between membranes brought at contact distance), while they are destabilized both by repulsive forces and by the elastic deformation energy. Above a critical area of the contact site, the adhesion forces prevail: the contact site grows in size until the complete adhesion of the two bodies inside a short-distance minimum is attained. This nucleation mechanism has been developed in the framework of a nonequilibrium Fokker-Planck picture by considering both the adhesive patch growth and dissolution processes. In addition, we also investigated the effect of the ligand-receptor pairing kinetics at the adhesion site in the time course of the patch expansion. The ratio between the ligand-receptor pairing kinetics and the expansion rate of the adhesion site is of paramount relevance in determining the overall nucleation rate. The theory enables one to self-consistently include both thermodynamics (energy barrier height) and dynamic (viscosity) parameters, giving rise in some limiting cases to simple analytical formulas. The model could be employed to rationalize fusion kinetics between vesicles, provided the short-range adhesion transition is the rate-limiting step to the whole adhesion process. Approximate relationships between the experimental fusion rates reported in the literature and parameters such as membrane elastic bending modulus, repulsion strength, temperature, osmotic forces, ligand-receptor binding energy, solvent and membrane viscosities are satisfactory explained by our model. The present results hint a possible role of the initial long-distance-->short-distance transition in determining the whole fusion kinetics.
Palladium-catalyzed hydrodehalogenation of 1,2,4,5-tetrachlorobenzene in water-ethanol mixtures.

PubMed

Wee, Hun-Young; Cunningham, Jeffrey A

2008-06-30

Palladium-catalyzed hydrodehalogenation (HDH) was applied for destroying 1,2,4,5-tetrachlorobenzene (TeCB) in mixtures of water and ethanol. This investigation was performed as a critical step in the development of a new technology for clean-up of soil contaminated by halogenated hydrophobic organic contaminants. The main goals of the investigation were to demonstrate the feasibility of the technology, to determine the effect of the solvent composition (water:ethanol ratio), and to develop a model for the kinetics of the dehalogenation process. All experiments were conducted in a batch reactor at ambient temperature under mild hydrogen pressure. The experimental results are all consistent with a Langmuir-Hinshelwood model for heterogeneous catalysis. Major findings that can be interpreted within the Langmuir-Hinshelwood framework include: (1) the rate of hydrodehalogenation depends strongly on the solvent composition, increasing as the water fraction of the solvent increases; (2) the HDH rate increases as the catalyst concentration in the reactor increases; (3) when enough catalyst is present, the HDH reaction appears to follow first-order kinetics, but the kinetics appear to be zero-order at low catalyst concentrations. TeCB is converted rapidly and quantitatively to benzene, with only trace concentrations of 1,2,4-trichlorobenzene appearing as a reactive intermediate. The results obtained here have important implications for the further development of the proposed soil remediation technology, and may also be important for the treatment of other hazardous waste streams.
Removal of monoethylene glycol from wastewater by using Zr-metal organic frameworks.

PubMed

Zaboon, Sami; Abid, Hussein Rasool; Yao, Zhengxin; Gubner, Rolf; Wang, Shaobin; Barifcani, Ahmed

2018-08-01

Mono-ethylene glycol (MEG), used in the oil and gas industries as a gas hydrate inhibitor, is a hazardous chemical present in wastewater from those processes. Metal-organic frameworks (MOFs) (modified UiO-66 ∗ and UiO-66-2OH) were used for the effective removal of MEG waste from effluents of distillation columns (MEG recovery units). Batch contact adsorption method was used to study the adsorption behavior toward these types of MOFs. Adsorption experiments showed that these MOFs had very high affinity toward MEG. Significant adsorption capacity was demonstrated on UiO-66-2OH and modified UiO-66 at 1000 mg·g -1 and 800 mg·g -1 respectively. The adsorption kinetics were fitted to a pseudo first-order model. UiO-66-2OH showed a higher adsorption capacity due to the presence of hydroxyl groups in its structure. A Langmuir model gave the best fitting for isotherm of experimental data at pH = 7. Copyright © 2018 Elsevier Inc. All rights reserved.
Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

PubMed Central

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data. PMID:16788595
Thermodynamic framework for identifying free energy inventories of enzyme catalytic cycles

PubMed Central

Fried, Stephen D.; Boxer, Steven G.

2013-01-01

Pauling’s suggestion that enzymes are complementary in structure to the activated complexes of the reactions they catalyze has provided the conceptual basis to explain how enzymes obtain their fantastic catalytic prowess, and has served as a guiding principle in drug design for over 50 y. However, this model by itself fails to predict the magnitude of enzymes’ rate accelerations. We construct a thermodynamic framework that begins with the classic concept of differential binding but invokes additional terms that are needed to account for subtle effects in the catalytic cycle’s proton inventory. Although the model presented can be applied generally, this analysis focuses on ketosteroid isomerase (KSI) as an example, where recent experiments along with a large body of kinetic and thermodynamic data have provided strong support for the noncanonical thermodynamic contribution described. The resulting analysis precisely predicts the free energy barrier of KSI’s reaction as determined from transition-state theory using only empirical thermodynamic data. This agreement is suggestive that a complete free energy inventory of the KSI catalytic cycle has been identified. PMID:23840058
Computational modeling of chemical reactions and interstitial growth and remodeling involving charged solutes and solid-bound molecules

PubMed Central

Nims, Robert J.; Maas, Steve; Weiss, Jeffrey A.

2014-01-01

Mechanobiological processes are rooted in mechanics and chemistry, and such processes may be modeled in a framework that couples their governing equations starting from fundamental principles. In many biological applications, the reactants and products of chemical reactions may be electrically charged, and these charge effects may produce driving forces and constraints that significantly influence outcomes. In this study, a novel formulation and computational implementation are presented for modeling chemical reactions in biological tissues that involve charged solutes and solid-bound molecules within a deformable porous hydrated solid matrix, coupling mechanics with chemistry while accounting for electric charges. The deposition or removal of solid-bound molecules contributes to the growth and remodeling of the solid matrix; in particular, volumetric growth may be driven by Donnan osmotic swelling, resulting from charged molecular species fixed to the solid matrix. This formulation incorporates the state of strain as a state variable in the production rate of chemical reactions, explicitly tying chemistry with mechanics for the purpose of modeling mechanobiology. To achieve these objectives, this treatment identifies the specific theoretical and computational challenges faced in modeling complex systems of interacting neutral and charged constituents while accommodating any number of simultaneous reactions where reactants and products may be modeled explicitly or implicitly. Several finite element verification problems are shown to agree with closed-form analytical solutions. An illustrative tissue engineering analysis demonstrates tissue growth and swelling resulting from the deposition of chondroitin sulfate, a charged solid-bound molecular species. This implementation is released in the open-source program FEBio (www.febio.org). The availability of this framework may be particularly beneficial to optimizing tissue engineering culture systems by examining the influence of nutrient availability on the evolution of inhomogeneous tissue composition and mechanical properties, the evolution of construct dimensions with growth, the influence of solute and solid matrix electric charge on the transport of cytokines, the influence of binding kinetics on transport, the influence of loading on binding kinetics, and the differential growth response to dynamically loaded versus free-swelling culture conditions. PMID:24558059
Computational modeling of chemical reactions and interstitial growth and remodeling involving charged solutes and solid-bound molecules.

PubMed

Ateshian, Gerard A; Nims, Robert J; Maas, Steve; Weiss, Jeffrey A

2014-10-01

Mechanobiological processes are rooted in mechanics and chemistry, and such processes may be modeled in a framework that couples their governing equations starting from fundamental principles. In many biological applications, the reactants and products of chemical reactions may be electrically charged, and these charge effects may produce driving forces and constraints that significantly influence outcomes. In this study, a novel formulation and computational implementation are presented for modeling chemical reactions in biological tissues that involve charged solutes and solid-bound molecules within a deformable porous hydrated solid matrix, coupling mechanics with chemistry while accounting for electric charges. The deposition or removal of solid-bound molecules contributes to the growth and remodeling of the solid matrix; in particular, volumetric growth may be driven by Donnan osmotic swelling, resulting from charged molecular species fixed to the solid matrix. This formulation incorporates the state of strain as a state variable in the production rate of chemical reactions, explicitly tying chemistry with mechanics for the purpose of modeling mechanobiology. To achieve these objectives, this treatment identifies the specific theoretical and computational challenges faced in modeling complex systems of interacting neutral and charged constituents while accommodating any number of simultaneous reactions where reactants and products may be modeled explicitly or implicitly. Several finite element verification problems are shown to agree with closed-form analytical solutions. An illustrative tissue engineering analysis demonstrates tissue growth and swelling resulting from the deposition of chondroitin sulfate, a charged solid-bound molecular species. This implementation is released in the open-source program FEBio ( www.febio.org ). The availability of this framework may be particularly beneficial to optimizing tissue engineering culture systems by examining the influence of nutrient availability on the evolution of inhomogeneous tissue composition and mechanical properties, the evolution of construct dimensions with growth, the influence of solute and solid matrix electric charge on the transport of cytokines, the influence of binding kinetics on transport, the influence of loading on binding kinetics, and the differential growth response to dynamically loaded versus free-swelling culture conditions.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirano, Shin'ichi; Nishi, Sakine; Kobayashi, Tsutomu, E-mail: s.hirano@rikkyo.ac.jp, E-mail: sakine@rikkyo.ac.jp, E-mail: tsutomu@rikkyo.ac.jp

We study the stability of a recently proposed model of scalar-field matter called mimetic dark matter or imperfect dark matter. It has been known that mimetic matter with higher derivative terms suffers from gradient instabilities in scalar perturbations. To seek for an instability-free extension of imperfect dark matter, we develop an effective theory of cosmological perturbations subject to the constraint on the scalar field's kinetic term. This is done by using the unifying framework of general scalar-tensor theories based on the ADM formalism. We demonstrate that it is indeed possible to construct a model of imperfect dark matter which ismore » free from ghost and gradient instabilities. As a side remark, we also show that mimetic F (R) theory is plagued with the Ostrogradsky instability.« less
Sandia’s Current Energy Conversion module for the Flexible-Mesh Delft3D flow solver v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chartand, Chris; Jagers, Bert

The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares’s, environmental hydrodynamics code, Delft3D, SNL-Delft3D-CEC-FM includes a new module that simulates energy conversion (momentum withdrawal) by MHK current energy conversion devices with commensurate changes in the turbulent kinetic energy and its dissipation rate. SNL-Delft3D-CEC-FM modified the Delft3D flexible mesh flow solver, DFlowFM.
Classical nucleation theory of homogeneous freezing of water: thermodynamic and kinetic parameters.

PubMed

Ickes, Luisa; Welti, André; Hoose, Corinna; Lohmann, Ulrike

2015-02-28

The probability of homogeneous ice nucleation under a set of ambient conditions can be described by nucleation rates using the theoretical framework of Classical Nucleation Theory (CNT). This framework consists of kinetic and thermodynamic parameters, of which three are not well-defined (namely the interfacial tension between ice and water, the activation energy and the prefactor), so that any CNT-based parameterization of homogeneous ice formation is less well-constrained than desired for modeling applications. Different approaches to estimate the thermodynamic and kinetic parameters of CNT are reviewed in this paper and the sensitivity of the calculated nucleation rate to the choice of parameters is investigated. We show that nucleation rates are very sensitive to this choice. The sensitivity is governed by one parameter - the interfacial tension between ice and water, which determines the energetic barrier of the nucleation process. The calculated nucleation rate can differ by more than 25 orders of magnitude depending on the choice of parameterization for this parameter. The second most important parameter is the activation energy of the nucleation process. It can lead to a variation of 16 orders of magnitude. By estimating the nucleation rate from a collection of droplet freezing experiments from the literature, the dependence of these two parameters on temperature is narrowed down. It can be seen that the temperature behavior of these two parameters assumed in the literature does not match with the predicted nucleation rates from the fit in most cases. Moreover a comparison of all possible combinations of theoretical parameterizations of the dominant two free parameters shows that one combination fits the fitted nucleation rates best, which is a description of the interfacial tension coming from a molecular model [Reinhardt and Doye, J. Chem. Phys., 2013, 139, 096102] in combination with the activation energy derived from self-diffusion measurements [Zobrist et al., J. Phys. Chem. C, 2007, 111, 2149]. However, some fundamental understanding of the processes is still missing. Further research in future might help to tackle this problem. The most important questions, which need to be answered to constrain CNT, are raised in this study.
kmos: A lattice kinetic Monte Carlo framework

NASA Astrophysics Data System (ADS)

Hoffmann, Max J.; Matera, Sebastian; Reuter, Karsten

2014-07-01

Kinetic Monte Carlo (kMC) simulations have emerged as a key tool for microkinetic modeling in heterogeneous catalysis and other materials applications. Systems, where site-specificity of all elementary reactions allows a mapping onto a lattice of discrete active sites, can be addressed within the particularly efficient lattice kMC approach. To this end we describe the versatile kmos software package, which offers a most user-friendly implementation, execution, and evaluation of lattice kMC models of arbitrary complexity in one- to three-dimensional lattice systems, involving multiple active sites in periodic or aperiodic arrangements, as well as site-resolved pairwise and higher-order lateral interactions. Conceptually, kmos achieves a maximum runtime performance which is essentially independent of lattice size by generating code for the efficiency-determining local update of available events that is optimized for a defined kMC model. For this model definition and the control of all runtime and evaluation aspects kmos offers a high-level application programming interface. Usage proceeds interactively, via scripts, or a graphical user interface, which visualizes the model geometry, the lattice occupations and rates of selected elementary reactions, while allowing on-the-fly changes of simulation parameters. We demonstrate the performance and scaling of kmos with the application to kMC models for surface catalytic processes, where for given operation conditions (temperature and partial pressures of all reactants) central simulation outcomes are catalytic activity and selectivities, surface composition, and mechanistic insight into the occurrence of individual elementary processes in the reaction network.
Online optimal experimental re-design in robotic parallel fed-batch cultivation facilities.

PubMed

Cruz Bournazou, M N; Barz, T; Nickel, D B; Lopez Cárdenas, D C; Glauche, F; Knepper, A; Neubauer, P

2017-03-01

We present an integrated framework for the online optimal experimental re-design applied to parallel nonlinear dynamic processes that aims to precisely estimate the parameter set of macro kinetic growth models with minimal experimental effort. This provides a systematic solution for rapid validation of a specific model to new strains, mutants, or products. In biosciences, this is especially important as model identification is a long and laborious process which is continuing to limit the use of mathematical modeling in this field. The strength of this approach is demonstrated by fitting a macro-kinetic differential equation model for Escherichia coli fed-batch processes after 6 h of cultivation. The system includes two fully-automated liquid handling robots; one containing eight mini-bioreactors and another used for automated at-line analyses, which allows for the immediate use of the available data in the modeling environment. As a result, the experiment can be continually re-designed while the cultivations are running using the information generated by periodical parameter estimations. The advantages of an online re-computation of the optimal experiment are proven by a 50-fold lower average coefficient of variation on the parameter estimates compared to the sequential method (4.83% instead of 235.86%). The success obtained in such a complex system is a further step towards a more efficient computer aided bioprocess development. Biotechnol. Bioeng. 2017;114: 610-619. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Kinetic parameter estimation model for anaerobic co-digestion of waste activated sludge and microalgae.

PubMed

Lee, Eunyoung; Cumberbatch, Jewel; Wang, Meng; Zhang, Qiong

2017-03-01

Anaerobic co-digestion has a potential to improve biogas production, but limited kinetic information is available for co-digestion. This study introduced regression-based models to estimate the kinetic parameters for the co-digestion of microalgae and Waste Activated Sludge (WAS). The models were developed using the ratios of co-substrates and the kinetic parameters for the single substrate as indicators. The models were applied to the modified first-order kinetics and Monod model to determine the rate of hydrolysis and methanogenesis for the co-digestion. The results showed that the model using a hyperbola function was better for the estimation of the first-order kinetic coefficients, while the model using inverse tangent function closely estimated the Monod kinetic parameters. The models can be used for estimating kinetic parameters for not only microalgae-WAS co-digestion but also other substrates' co-digestion such as microalgae-swine manure and WAS-aquatic plants. Copyright © 2016 Elsevier Ltd. All rights reserved.
Controls of Polysaccharide Chemistry on the Kinetics and Thermodynamics of Heterogeneous Calcium Carbonate Nucleation

NASA Astrophysics Data System (ADS)

Giuffre, A. J.; Han, N.; Dove, P. M.

2011-12-01

Polysaccharide fibrils control the orientation of calcium carbonate (CaCO3) biominerals. Good examples are found in the multilayered extracellular mucilaginous sheath of green algae and cyanobacteria and in specialized vesicles inside coccolithophorids. More complex organisms such as arthropods and mollusks form biomineralized exoskeletons and shells that consist of insoluble polysaccharides and soluble acid-rich proteins. In these structures, CaCO3 mineral orientation occurs along fibers of the polysaccharide chitin. This raises the question of whether polysaccharide chemistry has specific roles in directing biomineralization. The last three decades of research show that acidic proteins influence CaCO3 polymorph selection, crystallographic orientation, and nucleation and growth rates but little is known about the function of polysaccharides. In fact, polysaccharides are long considered an inert component of organic frameworks. In this experimental investigation, we test the hypothesis that polysaccharides have chemistry-specific influences on calcification by measuring the kinetics of calcite nucleation onto three types of polysaccharide films under controlled solution compositions. Characterized polysaccharides of simple repeating monomer sequences were chosen as model compounds to represent the major carbohydrates seen in microbial and calcifying environments: 1) alginic acid with carboxyl groups, 2) hyaluronic acid with alternating carboxyl and acetylamine groups, and 3) chitosan with amine and acetylamine groups. Biosubstrates were prepared by electrodeposition of these compounds as thin gel-like films onto gold-coated silicon wafers. Using a flow-through cell, heterogeneous nucleation rates of calcite were measured for a suite of supersaturation conditions. These rate data were compared to similar measurements for carboxyl- and hydroxyl-terminated self-assembled monolayers. Calcite nucleation rates onto the three polysaccharides vary by a factor of 400x. Preliminary analyses of the data attribute these differences to changes in both kinetic and thermodynamic barriers to nucleation. These initial findings indicate that polysaccharide chemistry can have active roles in regulating the kinetics of calcite formation. It may be time to reconsider their presumed function as inert framework molecules for mineralized structures. Future work will investigate CaCO3 nucleation on substrates of polysaccharides with more complex functionalization and monomer sequences to decipher the origins of these effects in promoting or inhibiting mineralization.
Harvesting multiple electron-hole pairs generated through plasmonic excitation of Au nanoparticles.

PubMed

Kim, Youngsoo; Smith, Jeremy G; Jain, Prashant K

2018-05-07

Multi-electron redox reactions, although central to artificial photosynthesis, are kinetically sluggish. Amidst the search for synthetic catalysts for such processes, plasmonic nanoparticles have been found to catalyse multi-electron reduction of CO 2 under visible light. This example motivates the need for a general, insight-driven framework for plasmonic catalysis of such multi-electron chemistry. Here, we elucidate the principles underlying the extraction of multiple redox equivalents from a plasmonic photocatalyst. We measure the kinetics of electron harvesting from a gold nanoparticle photocatalyst as a function of photon flux. Our measurements, supported by theoretical modelling, reveal a regime where two-electron transfer from the excited gold nanoparticle becomes prevalent. Multiple electron harvesting becomes possible under continuous-wave, visible-light excitation of moderate intensity due to strong interband transitions in gold and electron-hole separation accomplished using a hole scavenger. These insights will help expand the utility of plasmonic photocatalysis beyond CO 2 reduction to other challenging multi-electron, multi-proton transformations such as N 2 fixation.
Prompt isothermal decay of thermoluminescence in an apatite exhibiting strong anomalous fading

NASA Astrophysics Data System (ADS)

Sfampa, I. K.; Polymeris, G. S.; Tsirliganis, N. C.; Pagonis, V.; Kitis, G.

2014-02-01

Anomalous fading (AF) is one of the most serious drawbacks in thermoluminescence (TL) and optically stimulated luminescence (OSL) dating. In the present work the isothermal decay of TL signals from Durango apatite is studied for temperatures located on the rising part of the main TL peak. This material is known to exhibit strong AF phenomena, and its isothermal TL decay properties have not been studied previously. The experimental results show that the characteristic decay time of the isothermal signal does not depend of the temperature, and that this signal does not exhibit the strong temperature dependence expected from conventional TL kinetic theories. This is further direct experimental evidence for the possible presence of tunneling phenomena in this material. The isothermal decay curves are analyzed and discussed within the framework of conventional theories of TL, as well as within the context of a recently developed tunneling kinetic model for random distributions of electron-hole pairs in luminescent materials.
Transient loading of CD34+ hematopoietic progenitor cells with polystyrene nanoparticles.

PubMed

Deville, Sarah; Hadiwikarta, Wahyu Wijaya; Smisdom, Nick; Wathiong, Bart; Ameloot, Marcel; Nelissen, Inge; Hooyberghs, Jef

2017-01-01

CD34 + hematopoietic progenitor cells (HPCs) offer great opportunities to develop new treatments for numerous malignant and non-malignant diseases. Nanoparticle (NP)-based strategies can further enhance this potential, and therefore a thorough understanding of the loading behavior of HPCs towards NPs is essential for a successful application. The present study focusses on the interaction kinetics of 40 nm sized carboxylated polystyrene (PS) NPs with HPCs. Interestingly, a transient association of the NPs with HPCs is observed, reaching a maximum within 1 hour and declining afterwards. This behavior is not seen in dendritic cells (CD34-DCs) differentiated from HPCs, which display a monotonic increase in NP load. We demonstrate that this transient interaction requires an energy-dependent cellular process, suggesting active loading and release of NPs by HPCs. This novel observation offers a unique approach to transiently equip HPCs. A simple theoretical approach modeling the kinetics of NP loading and release is presented, contributing to a framework of describing this phenomenon.
Numerical simulation of two-phase flow for sediment transport in the inner-surf and swash zones

NASA Astrophysics Data System (ADS)

Bakhtyar, R.; Barry, D. A.; Yeganeh-Bakhtiary, A.; Li, L.; Parlange, J.-Y.; Sander, G. C.

2010-03-01

A two-dimensional two-phase flow framework for fluid-sediment flow simulation in the surf and swash zones was described. Propagation, breaking, uprush and backwash of waves on sloping beaches were studied numerically with an emphasis on fluid hydrodynamics and sediment transport characteristics. The model includes interactive fluid-solid forces and intergranular stresses in the moving sediment layer. In the Euler-Euler approach adopted, two phases were defined using the Navier-Stokes equations with interphase coupling for momentum conservation. The k-ɛ closure model and volume of fluid approach were used to describe the turbulence and tracking of the free surface, respectively. Numerical simulations explored incident wave conditions, specifically spilling and plunging breakers, on both dissipative and intermediate beaches. It was found that the spatial variation of sediment concentration in the swash zone is asymmetric, while the temporal behavior is characterized by maximum sediment concentrations at the start and end of the swash cycle. The numerical results also indicated that the maximum turbulent kinetic energy and sediment flux occurs near the wave-breaking point. These predictions are in general agreement with previous observations, while the model describes the fluid and sediment phase characteristics in much more detail than existing measurements. With direct quantifications of velocity, turbulent kinetic energy, sediment concentration and flux, the model provides a useful approach to improve mechanistic understanding of hydrodynamic and sediment transport in the nearshore zone.

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

PubMed

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.
Geometric and material determinants of patterning efficiency by dielectrophoresis.

PubMed

Albrecht, Dirk R; Sah, Robert L; Bhatia, Sangeeta N

2004-10-01

Dielectrophoretic (DEP) forces have been used extensively to manipulate, separate, and localize biological cells and bioparticles via high-gradient electric fields. However, minimization of DEP exposure time is desirable, because of possible untoward effects on cell behavior. Toward this goal, this article investigates the geometric and material determinants of particle patterning kinetics and efficiency. In particular, the time required to achieve a steady-state pattern is theoretically modeled and experimentally validated for a planar, interdigitated bar electrode array energized in a standing-wave configuration. This measure of patterning efficiency is calculated from an improved Fourier series solution of DEP force, in which realistic boundary conditions and a finite chamber height are imposed to reflect typical microfluidic applications. The chamber height, electrode spacing, and fluid viscosity and conductivity are parameters that profoundly affect patterning efficiency, and optimization can reduce electric field exposure by orders of magnitude. Modeling strategies are generalizable to arbitrary electrode design as well as to conditions where DEP force may not act alone to cause particle motion. This improved understanding of DEP patterning kinetics provides a framework for new advances in the development of DEP-based biological devices and assays with minimal perturbation of cell behavior. Copyright 2004 Biophysical Society
Evaluation of stochastic differential equation approximation of ion channel gating models.

PubMed

Bruce, Ian C

2009-04-01

Fox and Lu derived an algorithm based on stochastic differential equations for approximating the kinetics of ion channel gating that is simpler and faster than "exact" algorithms for simulating Markov process models of channel gating. However, the approximation may not be sufficiently accurate to predict statistics of action potential generation in some cases. The objective of this study was to develop a framework for analyzing the inaccuracies and determining their origin. Simulations of a patch of membrane with voltage-gated sodium and potassium channels were performed using an exact algorithm for the kinetics of channel gating and the approximate algorithm of Fox & Lu. The Fox & Lu algorithm assumes that channel gating particle dynamics have a stochastic term that is uncorrelated, zero-mean Gaussian noise, whereas the results of this study demonstrate that in many cases the stochastic term in the Fox & Lu algorithm should be correlated and non-Gaussian noise with a non-zero mean. The results indicate that: (i) the source of the inaccuracy is that the Fox & Lu algorithm does not adequately describe the combined behavior of the multiple activation particles in each sodium and potassium channel, and (ii) the accuracy does not improve with increasing numbers of channels.
Low pressure characteristics of the multipole resonance probe

NASA Astrophysics Data System (ADS)

Brinkmann, Ralf Peter; Oberrath, Jens

2014-10-01

The term ``Active plasma resonance spectroscopy'' (APRS) denotes a class of related techniques which utilize, for diagnostic purposes, the natural ability of plasmas to resonate on or near the electron plasma frequency ωpe. The basic idea dates back to the early days of discharge physics but has recently found renewed interest as an approach to industry-compatible plasma diagnostics: A radio frequent signal (in the GHz range) is coupled into the plasma via an antenna or probe, the spectral response is recorded (with the same or another antenna or probe), and a mathematical model is used to determine plasma parameters like the electron density or the electron temperature. When the method is applied to low pressure plasmas (of a few Pa and lower), kinetic effects must be accounted for in the mathematical model. This contribution studies a particular realization of the APRS scheme, the geometrically and electrically symmetric Multipole Resonance Probe (MRP). It is shown that the resonances of the MRP exhibit a residual damping in the limit p --> 0 which cannot be explained by Ohmic dissipation but only by kinetic effects. Supported by the German Federal Ministry of Education and Research (BMBF) in the framework of the PluTO project.
Geometric and Material Determinants of Patterning Efficiency by Dielectrophoresis

PubMed Central

Albrecht, Dirk R.; Sah, Robert L.; Bhatia, Sangeeta N.

2004-01-01

Dielectrophoretic (DEP) forces have been used extensively to manipulate, separate, and localize biological cells and bioparticles via high-gradient electric fields. However, minimization of DEP exposure time is desirable, because of possible untoward effects on cell behavior. Toward this goal, this article investigates the geometric and material determinants of particle patterning kinetics and efficiency. In particular, the time required to achieve a steady-state pattern is theoretically modeled and experimentally validated for a planar, interdigitated bar electrode array energized in a standing-wave configuration. This measure of patterning efficiency is calculated from an improved Fourier series solution of DEP force, in which realistic boundary conditions and a finite chamber height are imposed to reflect typical microfluidic applications. The chamber height, electrode spacing, and fluid viscosity and conductivity are parameters that profoundly affect patterning efficiency, and optimization can reduce electric field exposure by orders of magnitude. Modeling strategies are generalizable to arbitrary electrode design as well as to conditions where DEP force may not act alone to cause particle motion. This improved understanding of DEP patterning kinetics provides a framework for new advances in the development of DEP-based biological devices and assays with minimal perturbation of cell behavior. PMID:15454417
WKB approximation and tunneling in theories with noncanonical kinetic terms

NASA Astrophysics Data System (ADS)

González, Mariana Carrillo; Masoumi, Ali; Solomon, Adam R.; Trodden, Mark

2017-09-01

Tunneling is a fascinating aspect of quantum mechanics that renders the local minima of a potential meta-stable, with important consequences for particle physics, for the early hot stage of the universe, and more speculatively, for the behavior of the putative multiverse. While this phenomenon has been studied extensively for systems which have canonical kinetic terms, many theories of fundamental physics contain fields with noncanonical kinetic structures. It is therefore desirable to have a detailed framework for calculating tunneling rates and initial states after tunneling for these theories. In this work we present such a rigorous formulation and illustrate its use by applying it to a number of examples.
Kinetics and thermodynamics of exonuclease-deficient DNA polymerases

NASA Astrophysics Data System (ADS)

Gaspard, Pierre

2016-04-01

A kinetic theory is developed for exonuclease-deficient DNA polymerases, based on the experimental observation that the rates depend not only on the newly incorporated nucleotide, but also on the previous one, leading to the growth of Markovian DNA sequences from a Bernoullian template. The dependencies on nucleotide concentrations and template sequence are explicitly taken into account. In this framework, the kinetic and thermodynamic properties of DNA replication, in particular, the mean growth velocity, the error probability, and the entropy production are calculated analytically in terms of the rate constants and the concentrations. Theory is compared with numerical simulations for the DNA polymerases of T7 viruses and human mitochondria.
The transport of drug in fibrosis. Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

NASA Astrophysics Data System (ADS)

Ivancevic, Vladimir

2016-07-01

The topic of the review article [1] is the derivation of a multiscale paradigm for the modeling of fibrosis. Firstly, the biological process of the physiological and pathological fibrosis including therapeutical actions is reviewed. Fibrosis can be a consequence of tissue damage, infections and autoimmune diseases, foreign material, tumors. Some questions regarding the pathogenesis, progression and possible regression of fibrosis are lacking. At each scale of observation, different theoretical tools coming from computational, mathematical and physical biology have been proposed. However a complete framework that takes into account the different mechanisms occurring at different scales is still missing. Therefore with the main aim to define a multiscale approach for the modeling of fibrosis, the authors of [1] have presented different top-down and bottom-up approaches that have been developed in the literature. Specifically, their description refers to models for fibrosis diseases based on ordinary and partial differential equation, agents [2], thermostatted kinetic theory [3-5], coarse-grained structures [6-8] and constitutive laws for fibrous collagen networks [9]. A critical analysis has been addressed for all frameworks discussed in the paper. Open problems and future research directions referring to both biological and modeling insight of fibrosis are presented. The paper concludes with the ambitious aim of a multiscale model.
Mode of action in relevance of rodent liver tumors to human cancer risk.

PubMed

Holsapple, Michael P; Pitot, Henri C; Cohen, Samuel M; Cohen, Samuel H; Boobis, Alan R; Klaunig, James E; Pastoor, Timothy; Dellarco, Vicki L; Dragan, Yvonne P

2006-01-01

Hazard identification and risk assessment paradigms depend on the presumption of the similarity of rodents to humans, yet species specific responses, and the extrapolation of high-dose effects to low-dose exposures can affect the estimation of human risk from rodent data. As a consequence, a human relevance framework concept was developed by the International Programme on Chemical Safety (IPCS) and International Life Sciences Institute (ILSI) Risk Science Institute (RSI) with the central tenet being the identification of a mode of action (MOA). To perform a MOA analysis, the key biochemical, cellular, and molecular events need to first be established, and the temporal and dose-dependent concordance of each of the key events in the MOA can then be determined. The key events can be used to bridge species and dose for a given MOA. The next step in the MOA analysis is the assessment of biological plausibility for determining the relevance of the specified MOA in an animal model for human cancer risk based on kinetic and dynamic parameters. Using the framework approach, a MOA in animals could not be defined for metal overload. The MOA for phenobarbital (PB)-like P450 inducers was determined to be unlikely in humans after kinetic and dynamic factors were considered. In contrast, after these factors were considered with reference to estrogen, the conclusion was drawn that estrogen-induced tumors were plausible in humans. Finally, it was concluded that the induction of rodent liver tumors by porphyrogenic compounds followed a cytotoxic MOA, and that liver tumors formed as a result of sustained cytotoxicity and regenerative proliferation are considered relevant for evaluating human cancer risk if appropriate metabolism occurs in the animal models and in humans.
Upscaling anomalous reactive kinetics (A+B-->C) from pore scale Lagrangian velocity analysis

NASA Astrophysics Data System (ADS)

De Anna, P.; Tartakovsky, A. M.; Le Borgne, T.; Dentz, M.

2011-12-01

Natural flow fields in porous media display a complex spatio-temporal organization due to heterogeneous geological structures at different scales. This multiscale disorder implies anomalous dispersion, mixing and reaction kinetics (Berkowitz et al. RG 2006, Tartakovsky PRE 2010). Here, we focus on the upscaling of anomalous kinetics arising from pore scale, non Gaussian and correlated, velocity distributions. We consider reactive front simulations, where a component A displaces a component B that saturates initially the porous domain. The reactive component C is produced at the dispersive front located at interface between the A and B domains. The simulations are performed with the SPH method. As the mixing zone grows, the total mass of C produced increases with time. The scaling of this evolution with time is different from that which would be obtained from the homogeneous advection dispersion reaction equation. This anomalous kinetics property is related to spatial structure of the reactive mixture, and its evolution with time under the combined action of advective and diffusive processes. We discuss the different scaling regimes arising depending on the dominant process that governs mixing. In order to upscale these processes, we analyze the Lagrangian velocity properties, which are characterized by the non Gaussian distributions and long range temporal correlation. The main origin of these properties is the existence of very low velocity regions where solute particles can remain trapped for a long time. Another source of strong correlation is the channeling of flow in localized high velocity regions, which created finger-like structures in the concentration field. We show the spatial Markovian, and temporal non Markovian, nature of the Lagrangian velocity field. Therefore, an upscaled model can be defined as a correlated Continuous Time Random Walk (Le Borgne et al. PRL 2008). A key feature of this model is the definition of a transition probability density for Lagrangian velocities across a characteristic correlation distance. We quantify this transition probability density from pore scale simulations and use it in the effective stochastic model. In this framework, we investigate the ability of this effective model to represent correctly dispersion and mixing.
Model reduction of multiscale chemical langevin equations: a numerical case study.

PubMed

Sotiropoulos, Vassilios; Contou-Carrere, Marie-Nathalie; Daoutidis, Prodromos; Kaznessis, Yiannis N

2009-01-01

Two very important characteristics of biological reaction networks need to be considered carefully when modeling these systems. First, models must account for the inherent probabilistic nature of systems far from the thermodynamic limit. Often, biological systems cannot be modeled with traditional continuous-deterministic models. Second, models must take into consideration the disparate spectrum of time scales observed in biological phenomena, such as slow transcription events and fast dimerization reactions. In the last decade, significant efforts have been expended on the development of stochastic chemical kinetics models to capture the dynamics of biomolecular systems, and on the development of robust multiscale algorithms, able to handle stiffness. In this paper, the focus is on the dynamics of reaction sets governed by stiff chemical Langevin equations, i.e., stiff stochastic differential equations. These are particularly challenging systems to model, requiring prohibitively small integration step sizes. We describe and illustrate the application of a semianalytical reduction framework for chemical Langevin equations that results in significant gains in computational cost.
Neural Network Based Models for Fusion Applications

NASA Astrophysics Data System (ADS)

Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff

2017-10-01

Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-Ânetwork (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.
Electronic Excitation in Molecular Collisions: Structural, Dynamic and Kinetic Considerations.

DTIC Science & Technology

1981-08-01

electronically excited species are examined. The problem is studied both in general terms (i.e., the development of the required theoretical framework ) and in application to specific systems. (Author)
Electronic Excitation in Molecular Collisions: Structural, Dynamic and Kinetic Considerations.

DTIC Science & Technology

1980-09-01

electronically excited species are examined. The problem is studied both in general terms (i.e., the development of the required theoretical framework ) and in application to specific systems. (Author)
Electronic Excitation in Molecular Collisions: Structural, Dynamic and Kinetic Considerations.

DTIC Science & Technology

1979-09-01

electronically excited species are examined. The problem is studied both in general terms (i.e., the development of the required theoretical framework ) and in application to specific systems. (Author)
Electronic Excitation in Molecular Collisions: Structural, Dynamic and Kinetic Considerations.

DTIC Science & Technology

electronically excited specied are examined. The problem is studied both in general terms (i.e., the development of the required theoretical framework ) and in application to specific systems. (Author)
Predicting heavy metals' adsorption edges and adsorption isotherms on MnO2 with the parameters determined from Langmuir kinetics.

PubMed

Hu, Qinghai; Xiao, Zhongjin; Xiong, Xinmei; Zhou, Gongming; Guan, Xiaohong

2015-01-01

Although surface complexation models have been widely used to describe the adsorption of heavy metals, few studies have verified the feasibility of modeling the adsorption kinetics, edge, and isotherm data with one pH-independent parameter. A close inspection of the derivation process of Langmuir isotherm revealed that the equilibrium constant derived from the Langmuir kinetic model, KS-kinetic, is theoretically equivalent to the adsorption constant in Langmuir isotherm, KS-Langmuir. The modified Langmuir kinetic model (MLK model) and modified Langmuir isotherm model (MLI model) incorporating pH factor were developed. The MLK model was employed to simulate the adsorption kinetics of Cu(II), Co(II), Cd(II), Zn(II) and Ni(II) on MnO2 at pH3.2 or 3.3 to get the values of KS-kinetic. The adsorption edges of heavy metals could be modeled with the modified metal partitioning model (MMP model), and the values of KS-Langmuir were obtained. The values of KS-kinetic and KS-Langmuir are very close to each other, validating that the constants obtained by these two methods are basically the same. The MMP model with KS-kinetic constants could predict the adsorption edges of heavy metals on MnO2 very well at different adsorbent/adsorbate concentrations. Moreover, the adsorption isotherms of heavy metals on MnO2 at various pH levels could be predicted reasonably well by the MLI model with the KS-kinetic constants. Copyright © 2014. Published by Elsevier B.V.
A study of the effect of space-dependent neutronics on stochastically-induced bifurcations in BWR dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Analytis, G.T.

1995-09-01

A non-linear one-group space-dependent neutronic model for a finite one-dimensional core is coupled with a simple BWR feed-back model. In agreement with results obtained by the authors who originally developed the point-kinetics version of this model, we shall show numerically that stochastic reactivity excitations may result in limit-cycles and eventually in a chaotic behaviour, depending on the magnitude of the feed-back coefficient K. In the framework of this simple space-dependent model, the effect of the non-linearities on the different spatial harmonics is studied and the importance of the space-dependent effects is exemplified and assessed in terms of the importance ofmore » the higher harmonics. It is shown that under certain conditions, when the limit-cycle-type develop, the neutron spectra may exhibit strong space-dependent effects.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Doktorov, Alexander B., E-mail: doktorov@kinetics.nsc.ru

Manifestations of the “cage” effect at the encounters of reactants have been theoretically treated on the example of multistage reactions (including bimolecular exchange reactions as elementary stages) proceeding from different active sites in liquid solutions. It is shown that for reactions occurring near the contact of reactants, consistent consideration of quasi-stationary kinetics of such multistage reactions (possible in the framework of the encounter theory only) can be made on the basis of chemical concepts of the “cage complex,” just as in the case of one-site model described in the literature. Exactly as in the one-site model, the presence of themore » “cage” effect gives rise to new channels of reactant transformation that cannot result from elementary event of chemical conversion for the given reaction mechanism. Besides, the multisite model demonstrates new (as compared to one-site model) features of multistage reaction course.« less
The influence of the "cage" effect on the mechanism of reversible bimolecular multistage chemical reactions proceeding from different sites in solutions.

PubMed

Doktorov, Alexander B

2016-08-28

Manifestations of the "cage" effect at the encounters of reactants have been theoretically treated on the example of multistage reactions (including bimolecular exchange reactions as elementary stages) proceeding from different active sites in liquid solutions. It is shown that for reactions occurring near the contact of reactants, consistent consideration of quasi-stationary kinetics of such multistage reactions (possible in the framework of the encounter theory only) can be made on the basis of chemical concepts of the "cage complex," just as in the case of one-site model described in the literature. Exactly as in the one-site model, the presence of the "cage" effect gives rise to new channels of reactant transformation that cannot result from elementary event of chemical conversion for the given reaction mechanism. Besides, the multisite model demonstrates new (as compared to one-site model) features of multistage reaction course.

Fractional kinetics of glioma treatment by a radio-frequency electric field

NASA Astrophysics Data System (ADS)

Iomin, A.

2013-09-01

A realistic model for estimation of the medical effect of brain cancer (glioma) treatment by a radio-frequency (RF) electric field is suggested. This low intensity, intermediate-frequency alternating electric field is known as the tumor-treating field (TTF). The model is based on a construction of 3D comb model for a description of the cancer cells dynamics, where the migration-proliferation dichotomy becomes naturally apparent, and the outer-invasive region of glioma cancer is considered as a fractal composite embedded in the 3D space. In the framework of this model, the interplay between the TTF and the migration-proliferation dichotomy of cancer cells is considered, and the efficiency of this TTF is estimated. It is shown that the efficiency of the medical treatment by the TTF depends essentially on the mass fractal dimension of the cancer in the outer-invasive region.
Four-Wave-Mixing Oscillations in a simplified Boltzmannian semiconductor model with LO-phonons

NASA Astrophysics Data System (ADS)

Tamborenea, P. I.; Bányai, L.; Haug, H.

1996-03-01

The recently discovered(L. Bányai, D. B. Tran Thoai, E. Reitsamer, H. Haug, D. Steinbach, M. U. Wehner, M. Wegener, T. Marschner and W. Stolz, Phys. Rev. Lett. 75), 2188 (1995). oscillations of the integrated four-wave-mixing signal in semiconductors due to electron-LO-phonon scattering are studied within a simplified Boltzmann-type model. Although several aspects of the experimental results require a description within the framework of non-Markovian quantum-kinetic theory, our simplified Boltzmannian model is well suited to analyze the origin of the observed novel oscillations of frequency (1+m_e/m_h) hbarω_LO. To this end, we developed a third-order, analytic solution of the semiconductor Bloch equations (SBE) with Boltzmann-type, LO-phonon collision terms. Results of this theory along with numerical solutions of the SBE will be presented.
Competition between monomeric and dimeric crystals in schematic models for globular proteins.

PubMed

Fusco, Diana; Charbonneau, Patrick

2014-07-17

Advances in experimental techniques and in theoretical models have improved our understanding of protein crystallization. However, they have also left open questions regarding the protein phase behavior and self-assembly kinetics, such as why (nearly) identical crystallization conditions can sometimes result in the formation of different crystal forms. Here, we develop a patchy particle model with competing sets of patches that provides a microscopic explanation of this phenomenon. We identify different regimes in which one or two crystal forms can coexist with a low-density fluid. Using analytical approximations, we extend our findings to different crystal phases, providing a general framework for treating protein crystallization when multiple crystal forms compete. Our results also suggest different experimental routes for targeting a specific crystal form, and for reducing the dynamical competition between the two forms, thus facilitating protein crystal assembly.
An advanced model framework for solid electrolyte intercalation batteries.

PubMed

Landstorfer, Manuel; Funken, Stefan; Jacob, Timo

2011-07-28

Recent developments of solid electrolytes, especially lithium ion conductors, led to all solid state batteries for various applications. In addition, mathematical models sprout for different electrode materials and battery types, but are missing for solid electrolyte cells. We present a mathematical model for ion flux in solid electrolytes, based on non-equilibrium thermodynamics and functional derivatives. Intercalated ion diffusion within the electrodes is further considered, allowing the computation of the ion concentration at the electrode/electrolyte interface. A generalized Frumkin-Butler-Volmer equation describes the kinetics of (de-)intercalation reactions and is here extended to non-blocking electrodes. Using this approach, numerical simulations were carried out to investigate the space charge region at the interface. Finally, discharge simulations were performed to study different limitations of an all solid state battery cell. This journal is © the Owner Societies 2011
Mathematical modeling of cell adhesion in shear flow: application to targeted drug delivery in inflammation and cancer metastasis.

PubMed

Jadhav, Sameer; Eggleton, Charles D; Konstantopoulos, Konstantinos

2007-01-01

Cell adhesion plays a pivotal role in diverse biological processes that occur in the dynamic setting of the vasculature, including inflammation and cancer metastasis. Although complex, the naturally occurring processes that have evolved to allow for cell adhesion in the vasculature can be exploited to direct drug carriers to targeted cells and tissues. Fluid (blood) flow influences cell adhesion at the mesoscale by affecting the mechanical response of cell membrane, the intercellular contact area and collisional frequency, and at the nanoscale level by modulating the kinetics and mechanics of receptor-ligand interactions. Consequently, elucidating the molecular and biophysical nature of cell adhesion requires a multidisciplinary approach involving the synthesis of fundamentals from hydrodynamic flow, molecular kinetics and cell mechanics with biochemistry/molecular cell biology. To date, significant advances have been made in the identification and characterization of the critical cell adhesion molecules involved in inflammatory disorders, and, to a lesser degree, in cancer metastasis. Experimental work at the nanoscale level to determine the lifetime, interaction distance and strain responses of adhesion receptor-ligand bonds has been spurred by the advent of atomic force microscopy and biomolecular force probes, although our current knowledge in this area is far from complete. Micropipette aspiration assays along with theoretical frameworks have provided vital information on cell mechanics. Progress in each of the aforementioned research areas is key to the development of mathematical models of cell adhesion that incorporate the appropriate biological, kinetic and mechanical parameters that would lead to reliable qualitative and quantitative predictions. These multiscale mathematical models can be employed to predict optimal drug carrier-cell binding through isolated parameter studies and engineering optimization schemes, which will be essential for developing effective drug carriers for delivery of therapeutic agents to afflicted sites of the host.
Quantitative collision induced mass spectrometry of substituted piperazines - A correlative analysis between theory and experiment

NASA Astrophysics Data System (ADS)

Ivanova, Bojidarka; Spiteller, Michael

2017-12-01

The present paper deals with quantitative kinetics and thermodynamics of collision induced dissociation (CID) reactions of piperazines under different experimental conditions together with a systematic description of effect of counter-ions on common MS fragment reactions of piperazines; and intra-molecular effect of quaternary cyclization of substituted piperazines yielding to quaternary salts. There are discussed quantitative model equations of rate constants as well as free Gibbs energies of series of m-independent CID fragment processes in GP, which have been evidenced experimentally. Both kinetic and thermodynamic parameters are also predicted by computational density functional theory (DFT) and ab initio both static and dynamic methods. The paper examines validity of Maxwell-Boltzmann distribution to non-Boltzmann CID processes in quantitatively as well. The experiments conducted within the latter framework yield to an excellent correspondence with theoretical quantum chemical modeling. The important property of presented model equations of reaction kinetics is the applicability in predicting unknown and assigning of known mass spectrometric (MS) patterns. The nature of "GP" continuum of CID-MS coupled scheme of measurements with electrospray ionization (ESI) source is discussed, performing parallel computations in gas-phase (GP) and polar continuum at different temperatures and ionic strengths. The effect of pressure is presented. The study contributes significantly to methodological and phenomenological developments of CID-MS and its analytical implementations for quantitative and structural analyses. It also demonstrates great prospective of a complementary application of experimental CID-MS and computational quantum chemistry studying chemical reactivity, among others. To a considerable extend this work underlies the place of computational quantum chemistry to the field of experimental analytical chemistry in particular highlighting the structural analysis.
Communication: Analysing kinetic transition networks for rare events.

PubMed

Stevenson, Jacob D; Wales, David J

2014-07-28

The graph transformation approach is a recently proposed method for computing mean first passage times, rates, and committor probabilities for kinetic transition networks. Here we compare the performance to existing linear algebra methods, focusing on large, sparse networks. We show that graph transformation provides a much more robust framework, succeeding when numerical precision issues cause the other methods to fail completely. These are precisely the situations that correspond to rare event dynamics for which the graph transformation was introduced.
Fabrication of magnetite nano particles and modification with metal organic framework of Zn(2+) for sorption of doxycyline.

PubMed

Ghassemi Nooreini, Mahsa; Ahmad Panahi, Homayon

2016-10-15

This study presents a novel method for synthesis and characterization of a metal-organic framework and application in drug delivery. The first step was synthesis of amino functionalized magnetite that was then modified by a metal-organic framework of Zn(2+). This newly developed nano-sorbent was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive x-ray spectroscopy, thermogravimetric analysis, vibrating sample magnetometer and x-ray diffraction. Doxycycline was loaded to the nano-sorbent and effects of the variable parameters, kinetics of adsorption, release and capacity of adsorption were investigated. Test results specified maximum sorption of 21.5mgg(-1) for doxycycline in conditions of nano-sorbent at pH 7 and optimum time of 10min. Equilibrium adsorption data were analyzed by the Langmuir, Freundlich and Temkin models. Results showed that about 40% of doxycycline was released in simulated gastric fluid for the 30min and more than 70% was released in simulated intestinal fluid during 12h. These results were satisfactory and demonstrate that this new nano-sorbent modified with metal-organic framework had a good level of efficiency for drug delivery of doxycycline. Copyright © 2016 Elsevier B.V. All rights reserved.
A network dynamics approach to chemical reaction networks

NASA Astrophysics Data System (ADS)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.
Polymer Fluid Dynamics: Continuum and Molecular Approaches.

PubMed

Bird, R B; Giacomin, A J

2016-06-07

To solve problems in polymer fluid dynamics, one needs the equations of continuity, motion, and energy. The last two equations contain the stress tensor and the heat-flux vector for the material. There are two ways to formulate the stress tensor: (a) One can write a continuum expression for the stress tensor in terms of kinematic tensors, or (b) one can select a molecular model that represents the polymer molecule and then develop an expression for the stress tensor from kinetic theory. The advantage of the kinetic theory approach is that one gets information about the relation between the molecular structure of the polymers and the rheological properties. We restrict the discussion primarily to the simplest stress tensor expressions or constitutive equations containing from two to four adjustable parameters, although we do indicate how these formulations may be extended to give more complicated expressions. We also explore how these simplest expressions are recovered as special cases of a more general framework, the Oldroyd 8-constant model. Studying the simplest models allows us to discover which types of empiricisms or molecular models seem to be worth investigating further. We also explore equivalences between continuum and molecular approaches. We restrict the discussion to several types of simple flows, such as shearing flows and extensional flows, which are of greatest importance in industrial operations. Furthermore, if these simple flows cannot be well described by continuum or molecular models, then it is not necessary to lavish time and energy to apply them to more complex flow problems.
A computational kinetic model of diffusion for molecular systems.

PubMed

Teo, Ivan; Schulten, Klaus

2013-09-28

Regulation of biomolecular transport in cells involves intra-protein steps like gating and passage through channels, but these steps are preceded by extra-protein steps, namely, diffusive approach and admittance of solutes. The extra-protein steps develop over a 10-100 nm length scale typically in a highly particular environment, characterized through the protein's geometry, surrounding electrostatic field, and location. In order to account for solute energetics and mobility of solutes in this environment at a relevant resolution, we propose a particle-based kinetic model of diffusion based on a Markov State Model framework. Prerequisite input data consist of diffusion coefficient and potential of mean force maps generated from extensive molecular dynamics simulations of proteins and their environment that sample multi-nanosecond durations. The suggested diffusion model can describe transport processes beyond microsecond duration, relevant for biological function and beyond the realm of molecular dynamics simulation. For this purpose the systems are represented by a discrete set of states specified by the positions, volumes, and surface elements of Voronoi grid cells distributed according to a density function resolving the often intricate relevant diffusion space. Validation tests carried out for generic diffusion spaces show that the model and the associated Brownian motion algorithm are viable over a large range of parameter values such as time step, diffusion coefficient, and grid density. A concrete application of the method is demonstrated for ion diffusion around and through the Eschericia coli mechanosensitive channel of small conductance ecMscS.
Fit reduced GUTS models online: From theory to practice.

PubMed

Baudrot, Virgile; Veber, Philippe; Gence, Guillaume; Charles, Sandrine

2018-05-20

Mechanistic modeling approaches, such as the toxicokinetic-toxicodynamic (TKTD) framework, are promoted by international institutions such as the European Food Safety Authority and the Organization for Economic Cooperation and Development to assess the environmental risk of chemical products generated by human activities. TKTD models can encompass a large set of mechanisms describing the kinetics of compounds inside organisms (e.g., uptake and elimination) and their effect at the level of individuals (e.g., damage accrual, recovery, and death mechanism). Compared to classical dose-response models, TKTD approaches have many advantages, including accounting for temporal aspects of exposure and toxicity, considering data points all along the experiment and not only at the end, and making predictions for untested situations as realistic exposure scenarios. Among TKTD models, the general unified threshold model of survival (GUTS) is within the most recent and innovative framework but is still underused in practice, especially by risk assessors, because specialist programming and statistical skills are necessary to run it. Making GUTS models easier to use through a new module freely available from the web platform MOSAIC (standing for MOdeling and StAtistical tools for ecotoxIClogy) should promote GUTS operability in support of the daily work of environmental risk assessors. This paper presents the main features of MOSAIC_GUTS: uploading of the experimental data, GUTS fitting analysis, and LCx estimates with their uncertainty. These features will be exemplified from literature data. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC. © 2018 SETAC.
A Model for Partitioning CO2 Flux and Calculating Transformation of Soil C Fractions

NASA Astrophysics Data System (ADS)

Zhang, S.; Noormets, A.; Tu, C.; King, J.

2011-12-01

It has been recognized that mechanistic understanding of soil organic carbon (SOC) mineralization requires partitioning of SOM to different sub-pools, whose turnover kinetics differ. Different fractionation methods have been developed to separate and analyze SOC fractions with different turnover rates, but some recent studies have called to questions earlier assumptions about chemical structure of C compounds and their recalcitrance to decomposition. To our knowledge, there is also no model that would bring together the information on various indicators of recalcitrance in a kinetic model framework . Here we deploy an analytical framework to partition soil net CO2 emissions to three density fractions (F1, F2, and F3, in the order of increasing density) in a peat soil and follow mineralization-related transformations (from lighter to heavier fractions). We followed the changes in total C content [C] and 13C of each three density fractions through a 3-month incubation study. We partitioned the CO2 produced by the soil between the different fractions using 13C and [C] change data. Applying this approach to a factorial experiment, we found that partitioning of CO2 emission and transformation rates among fractions differed between the organic top soil and deeper sandy soil. At depth of 45-75cm, almost no C was released through CO2 emission for all three fractions, while at 0-30cm, emission reached 0.2 g C/g soil over the incubation period, an average of 99% of which was from F2. Mineralization-related transformation rate at 45-75cm was 0.02 g soil/g soil with no significant differences among fractions. At 0-30cm, out of one gram of initial bulk soil, an average of 0.31g F1 transformed to F2, whereas no F2 was transformed to F3. Although the current study was carried out on a high-organic soil, the partitioning method is applicable to all soil types.
Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.
Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682
Kinetic modeling of cell metabolism for microbial production.

PubMed

Costa, Rafael S; Hartmann, Andras; Vinga, Susana

2016-02-10

Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. Copyright © 2015 Elsevier B.V. All rights reserved.
Spectral method for a kinetic swarming model

DOE PAGES

Gamba, Irene M.; Haack, Jeffrey R.; Motsch, Sebastien

2015-04-28

Here we present the first numerical method for a kinetic description of the Vicsek swarming model. The kinetic model poses a unique challenge, as there is a distribution dependent collision invariant to satisfy when computing the interaction term. We use a spectral representation linked with a discrete constrained optimization to compute these interactions. To test the numerical scheme we investigate the kinetic model at different scales and compare the solution with the microscopic and macroscopic descriptions of the Vicsek model. Lastly, we observe that the kinetic model captures key features such as vortex formation and traveling waves.
PathCase-SB architecture and database design

PubMed Central

2011-01-01

Background Integration of metabolic pathways resources and regulatory metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation in metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks. Description PathCase Systems Biology (PathCase-SB) is built and released. The PathCase-SB database provides data and API for multiple user interfaces and software tools. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate data of selected biological data sources on the web (currently, BioModels database and KEGG), and to provide more powerful and/or new capabilities via the new web-based integrative framework. This paper describes architecture and database design issues encountered in PathCase-SB's design and implementation, and presents the current design of PathCase-SB's architecture and database. Conclusions PathCase-SB architecture and database provide a highly extensible and scalable environment with easy and fast (real-time) access to the data in the database. PathCase-SB itself is already being used by researchers across the world. PMID:22070889
Dynamic Model of Basic Oxygen Steelmaking Process Based on Multi-zone Reaction Kinetics: Model Derivation and Validation

NASA Astrophysics Data System (ADS)

Rout, Bapin Kumar; Brooks, Geoff; Rhamdhani, M. Akbar; Li, Zushu; Schrama, Frank N. H.; Sun, Jianjun

2018-04-01

A multi-zone kinetic model coupled with a dynamic slag generation model was developed for the simulation of hot metal and slag composition during the basic oxygen furnace (BOF) operation. The three reaction zones (i) jet impact zone, (ii) slag-bulk metal zone, (iii) slag-metal-gas emulsion zone were considered for the calculation of overall refining kinetics. In the rate equations, the transient rate parameters were mathematically described as a function of process variables. A micro and macroscopic rate calculation methodology (micro-kinetics and macro-kinetics) were developed to estimate the total refining contributed by the recirculating metal droplets through the slag-metal emulsion zone. The micro-kinetics involves developing the rate equation for individual droplets in the emulsion. The mathematical models for the size distribution of initial droplets, kinetics of simultaneous refining of elements, the residence time in the emulsion, and dynamic interfacial area change were established in the micro-kinetic model. In the macro-kinetics calculation, a droplet generation model was employed and the total amount of refining by emulsion was calculated by summing the refining from the entire population of returning droplets. A dynamic FetO generation model based on oxygen mass balance was developed and coupled with the multi-zone kinetic model. The effect of post-combustion on the evolution of slag and metal composition was investigated. The model was applied to a 200-ton top blowing converter and the simulated value of metal and slag was found to be in good agreement with the measured data. The post-combustion ratio was found to be an important factor in controlling FetO content in the slag and the kinetics of Mn and P in a BOF process.
On binding energy of trions in bulk materials

NASA Astrophysics Data System (ADS)

Filikhin, Igor; Kezerashvili, Roman Ya.; Vlahovic, Branislav

2018-03-01

We study the negatively T- and positively T+ charged trions in bulk materials in the effective mass approximation within the framework of a potential model. The binding energies of trions in various semiconductors are calculated by employing Faddeev equation in configuration space. Results of calculations of the binding energies for T- are consistent with previous computational studies and are in reasonable agreement with experimental measurements, while the T+ is unbound for all considered cases. The mechanism of formation of the binding energy of trions is analyzed by comparing contributions of a mass-polarization term related to kinetic energy operators and a term related to the Coulomb repulsion of identical particles.

Multi-scale modeling of spin transport in organic semiconductors

NASA Astrophysics Data System (ADS)

Hemmatiyan, Shayan; Souza, Amaury; Kordt, Pascal; McNellis, Erik; Andrienko, Denis; Sinova, Jairo

In this work, we present our theoretical framework to simulate simultaneously spin and charge transport in amorphous organic semiconductors. By combining several techniques e.g. molecular dynamics, density functional theory and kinetic Monte Carlo, we are be able to study spin transport in the presence of anisotropy, thermal effects, magnetic and electric field effects in a realistic morphologies of amorphous organic systems. We apply our multi-scale approach to investigate the spin transport in amorphous Alq3 (Tris(8-hydroxyquinolinato)aluminum) and address the underlying spin relaxation mechanism in this system as a function of temperature, bias voltage, magnetic field and sample thickness.
Steady and transient sliding under rate-and-state friction

NASA Astrophysics Data System (ADS)

Putelat, Thibaut; Dawes, Jonathan H. P.

2015-05-01

The physics of dry friction is often modelled by assuming that static and kinetic frictional forces can be represented by a pair of coefficients usually referred to as μs and μk, respectively. In this paper we re-examine this discontinuous dichotomy and relate it quantitatively to the more general, and smooth, framework of rate-and-state friction. This is important because it enables us to link the ideas behind the widely used static and dynamic coefficients to the more complex concepts that lie behind the rate-and-state framework. Further, we introduce a generic framework for rate-and-state friction that unifies different approaches found in the literature. We consider specific dynamical models for the motion of a rigid block sliding on an inclined surface. In the Coulomb model with constant dynamic friction coefficient, sliding at constant velocity is not possible. In the rate-and-state formalism steady sliding states exist, and analysing their existence and stability enables us to show that the static friction coefficient μs should be interpreted as the local maximum at very small slip rates of the steady state rate-and-state friction law. Next, we revisit the often-cited experiments of Rabinowicz (J. Appl. Phys., 22:1373-1379, 1951). Rabinowicz further developed the idea of static and kinetic friction by proposing that the friction coefficient maintains its higher and static value μs over a persistence length before dropping to the value μk. We show that there is a natural identification of the persistence length with the distance that the block slips as measured along the stable manifold of the saddle point equilibrium in the phase space of the rate-and-state dynamics. This enables us explicitly to define μs in terms of the rate-and-state variables and hence link Rabinowicz's ideas to rate-and-state friction laws. This stable manifold naturally separates two basins of attraction in the phase space: initial conditions in the first one lead to the block eventually stopping, while in the second basin of attraction the sliding motion continues indefinitely. We show that a second definition of μs is possible, compatible with the first one, as the weighted average of the rate-and-state friction coefficient over the time the block is in motion.
Kinetics of bacterial phospholipase C activity at micellar interfaces: effect of substrate aggregate microstructure and a model for the kinetic parameters.

PubMed

Singh, Jasmeet; Ranganathan, Radha; Hajdu, Joseph

2008-12-25

Activity at micellar interfaces of bacterial phospholipase C from Bacillus cereus on phospholipids solubilized in micelles was investigated with the goal of elucidating the role of the interface microstructure and developing further an existing kinetic model. Enzyme kinetics and physicochemical characterization of model substrate aggregates were combined, thus enabling the interpretation of kinetics in the context of the interface. Substrates were diacylphosphatidylcholine of different acyl chain lengths in the form of mixed micelles with dodecyldimethylammoniopropanesulfonate. An early kinetic model, reformulated to reflect the interfacial nature of the kinetics, was applied to the kinetic data. A better method of data treatment is proposed, use of which makes the presence of microstructure effects quite transparent. Models for enzyme-micelle binding and enzyme-lipid binding are developed, and expressions incorporating the microstructural properties are derived for the enzyme-micelle dissociation constant K(s) and the interface Michaelis-Menten constant, K(M). Use of these expressions in the interface kinetic model brings excellent agreement between the kinetic data and the model. Numerical values for the thermodynamic and kinetic parameters are determined. Enzyme-lipid binding is found to be an activated process with an acyl chain length dependent free energy of activation that decreases with micelle lipid molar fraction with a coefficient of about -15RT and correlates with the tightness of molecular packing in the substrate aggregate. Thus, the physical insight obtained includes a model for the kinetic parameters that shows that these parameters depend on the substrate concentration and acyl chain length of the lipid. Enzyme-micelle binding is indicated to be hydrophobic and solvent mediated with a dissociation constant of 1.2 mM.
A kinetics database and scripts for PHREEQC

NASA Astrophysics Data System (ADS)

Hu, B.; Zhang, Y.; Teng, Y.; Zhu, C.

2017-12-01

Kinetics of geochemical reactions has been increasingly used in numerical models to simulate coupled flow, mass transport, and chemical reactions. However, the kinetic data are scattered in the literature. To assemble a kinetic dataset for a modeling project is an intimidating task for most. In order to facilitate the application of kinetics in geochemical modeling, we assembled kinetics parameters into a database for the geochemical simulation program, PHREEQC (version 3.0). Kinetics data were collected from the literature. Our database includes kinetic data for over 70 minerals. The rate equations are also programmed into scripts with the Basic language. Using the new kinetic database, we simulated reaction path during the albite dissolution process using various rate equations in the literature. The simulation results with three different rate equations gave difference reaction paths at different time scale. Another application involves a coupled reactive transport model simulating the advancement of an acid plume in an acid mine drainage site associated with Bear Creek Uranium tailings pond. Geochemical reactions including calcite, gypsum, and illite were simulated with PHREEQC using the new kinetic database. The simulation results successfully demonstrated the utility of new kinetic database.
Modelling dimercaptosuccinic acid (DMSA) plasma kinetics in humans.

PubMed

van Eijkeren, Jan C H; Olie, J Daniël N; Bradberry, Sally M; Vale, J Allister; de Vries, Irma; Meulenbelt, Jan; Hunault, Claudine C

2016-11-01

No kinetic models presently exist which simulate the effect of chelation therapy on lead blood concentrations in lead poisoning. Our aim was to develop a kinetic model that describes the kinetics of dimercaptosuccinic acid (DMSA; succimer), a commonly used chelating agent, that could be used in developing a lead chelating model. This was a kinetic modelling study. We used a two-compartment model, with a non-systemic gastrointestinal compartment (gut lumen) and the whole body as one systemic compartment. The only data available from the literature were used to calibrate the unknown model parameters. The calibrated model was then validated by comparing its predictions with measured data from three different experimental human studies. The model predicted total DMSA plasma and urine concentrations measured in three healthy volunteers after ingestion of DMSA 10 mg/kg. The model was then validated by using data from three other published studies; it predicted concentrations within a factor of two, representing inter-human variability. A simple kinetic model simulating the kinetics of DMSA in humans has been developed and validated. The interest of this model lies in the future potential to use it to predict blood lead concentrations in lead-poisoned patients treated with DMSA.
Kinetic Modeling of a Heterogeneous Fenton Oxidative Treatment of Petroleum Refining Wastewater

PubMed Central

Basheer Hasan, Diya'uddeen; Abdul Raman, Abdul Aziz; Wan Daud, Wan Mohd Ashri

2014-01-01

The mineralisation kinetics of petroleum refinery effluent (PRE) by Fenton oxidation were evaluated. Within the ambit of the experimental data generated, first-order kinetic model (FKM), generalised lumped kinetic model (GLKM), and generalized kinetic model (GKM) were tested. The obtained apparent kinetic rate constants for the initial oxidation step (k 2′), their final oxidation step (k 1′), and the direct conversion to endproducts step (k 3′) were 10.12, 3.78, and 0.24 min−1 for GKM; 0.98, 0.98, and nil min−1 for GLKM; and nil, nil, and >0.005 min−1 for FKM. The findings showed that GKM is superior in estimating the mineralization kinetics. PMID:24592152
Healthy imperfect dark matter from effective theory of mimetic cosmological perturbations

NASA Astrophysics Data System (ADS)

Hirano, Shin'ichi; Nishi, Sakine; Kobayashi, Tsutomu

2017-07-01

We study the stability of a recently proposed model of scalar-field matter called mimetic dark matter or imperfect dark matter. It has been known that mimetic matter with higher derivative terms suffers from gradient instabilities in scalar perturbations. To seek for an instability-free extension of imperfect dark matter, we develop an effective theory of cosmological perturbations subject to the constraint on the scalar field's kinetic term. This is done by using the unifying framework of general scalar-tensor theories based on the ADM formalism. We demonstrate that it is indeed possible to construct a model of imperfect dark matter which is free from ghost and gradient instabilities. As a side remark, we also show that mimetic F(Script R) theory is plagued with the Ostrogradsky instability.
Simulation of methylene blue adsorption by salts-treated beech sawdust in batch and fixed-bed systems.

PubMed

Batzias, F A; Sidiras, D K

2007-10-01

Batch and column kinetics of methylene blue adsorption on calcium chloride, zinc chloride, magnesium chloride and sodium chloride treated beech sawdust were simulated, using untreated beech sawdust as control, in order to explore its potential use as a low-cost adsorbent for wastewater dye removal. The adsorption capacity, estimated according to Freundlich's model, the Langmuir constant K(L) and the adsorption capacity coefficient values, determined using the Bohart and Adams' bed depth service model indicate that salts treatment enhanced the adsorption properties of the original material. Since sawdust is an industrial waste/byproduct and the salts used can be recovered as spent liquids from various chemical operations, this process of adsorbent upgrading/modification might be considered to take place within an 'Industrial Ecology' framework.
UV-extending ghost inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, Mikhail M.; Sibiryakov, Sergey, E-mail: mm.ivanov@physics.msu.ru, E-mail: sergey.sibiryakov@cern.ch

2014-05-01

We present a setup that provides a partial UV-completion of the ghost inflation model up to a scale which can be almost as high as the Planck mass. This is achieved by coupling the inflaton to the Lorentz-violating sector described by the Einstein-aether theory or its khronometric version. Compared to previous works on ghost inflation our setup allows to go beyond the study of small perturbations and include the background dynamics in a unified framework. In the specific regime when the expansion of the Universe is dominated by the kinetic energy of the inflaton we find that the model predictsmore » rather high tensor-to-scalar ratio r ∼ 0.02÷0.2 and non-Gaussianity of equilateral type with f{sub NL} in the range from -50 to -5.« less
Mark R. Nimlos | NREL

Science.gov Websites

, reaction kinetics, computational modeling, photochemistry, and molecular spectroscopy. Nimlos has served as Chemical reaction energetics and kinetics Biomass pyrolysis and gasification Heterogeneous catalysis in zeolites Quantum modeling and kinetic modeling of reaction Molecular dynamics modeling
Carbonate mineral dissolution kinetics in high pressure experiments

NASA Astrophysics Data System (ADS)

Dethlefsen, F.; Dörr, C.; Schäfer, D.; Ebert, M.

2012-04-01

The potential CO2 reservoirs in the North German Basin are overlain by a series of Mesozoic barrier rocks and aquifers and finally mostly by Tertiary and Quaternary close-to-surface aquifers. The unexpected rise of stored CO2 from its reservoir into close-to-surface aquifer systems, perhaps through a broken well casing, may pose a threat to groundwater quality because of the acidifying effect of CO2 dissolution in water. The consequences may be further worsening of the groundwater quality due to the mobilization of heavy metals. Buffer mechanisms counteracting the acidification are for instance the dissolution of carbonates. Carbonate dissolution kinetics is comparably fast and carbonates can be abundant in close-to-surface aquifers. The disadvantages of batch experiments compared to column experiments in order to determine rate constants are well known and have for instance been described by v. GRINSVEN and RIEMSDIJK (1992). Therefore, we have designed, developed, tested, and used a high-pressure laboratory column system to simulate aquifer conditions in a flow through setup within the CO2-MoPa project. The calcite dissolution kinetics was determined for CO2-pressures of 6, 10, and 50 bars. The results were evaluated by using the PHREEQC code with a 1-D reactive transport model, applying a LASAGA (1984) -type kinetic dissolution equation (PALANDRI and KHARAKA, 2004; eq. 7). While PALANDRI and KHARAKA (2004) gave calcite dissolution rate constants originating from batch experiments of log kacid = -0.3 and log kneutral = -5.81, the data of the column experiment were best fitted using log kacid = -2.3 and log kneutral = -7.81, so that the rate constants fitted using the lab experiment applying 50 bars pCO2 were approximately 100 times lower than according to the literature data. Rate constants of experiments performed at less CO2 pressure (pCO2 = 6 bars: log kacid = -1.78; log kneutral = -7.29) were only 30 times lower than literature data. These discrepancies in the reaction kinetics should be acknowledged when using reactive transport models, especially when modeling kinetically controlled pH-buffering processes between a CO2 leakage an a receptor like a ground water well. Currently, further experiments for the determination of the dolomite dissolution kinetics are being performed. Here, the knowledge of the dissolution rate constants can be even more important compared to the (still) fast calcite dissolution. This study is being funded by the German Federal Ministry of Education and Research (BMBF), EnBW Energie Baden-Württemberg AG, E.ON Energie AG, E.ON Gas Storage AG, RWE Dea AG, Vattenfall Europe Technology Research GmbH, Wintershall Holding AG and Stadtwerke Kiel AG as part of the CO2-MoPa joint project in the framework of the Special Program GEOTECHNOLOGIEN. Literature Lasaga, A. C., 1984. Chemical Kinetics of Water-Rock Interactions. Journal of Geophysical Research 89, 4009-4025. Palandri, J. L. and Kharaka, Y. K., 2004. A compilation of rate parameters of water-mineral interaction kinetics for application to geochemical modeling. USGS, Menlo Park, CA, USA. v. Grinsven, J. J. M. and Riemsdijk, W. H., 1992. Evaluation of batch and column techniques to measure weathering rates in soils. Geoderma 52, 41-57.
Collective behaviours: from biochemical kinetics to electronic circuits

PubMed Central

Agliari, Elena; Barra, Adriano; Burioni, Raffaella; Di Biasio, Aldo; Uguzzoni, Guido

2013-01-01

In this work we aim to highlight a close analogy between cooperative behaviors in chemical kinetics and cybernetics; this is realized by using a common language for their description, that is mean-field statistical mechanics. First, we perform a one-to-one mapping between paradigmatic behaviors in chemical kinetics (i.e., non-cooperative, cooperative, ultra-sensitive, anti-cooperative) and in mean-field statistical mechanics (i.e., paramagnetic, high and low temperature ferromagnetic, anti-ferromagnetic). Interestingly, the statistical mechanics approach allows a unified, broad theory for all scenarios and, in particular, Michaelis-Menten, Hill and Adair equations are consistently recovered. This framework is then tested against experimental biological data with an overall excellent agreement. One step forward, we consistently read the whole mapping from a cybernetic perspective, highlighting deep structural analogies between the above-mentioned kinetics and fundamental bricks in electronics (i.e. operational amplifiers, flashes, flip-flops), so to build a clear bridge linking biochemical kinetics and cybernetics. PMID:24322327
Modeling coupled nanoparticle aggregation and transport in porous media: A Lagrangian approach

NASA Astrophysics Data System (ADS)

Taghavy, Amir; Pennell, Kurt D.; Abriola, Linda M.

2015-01-01

Changes in nanoparticle size and shape due to particle-particle interactions (i.e., aggregation or agglomeration) may significantly alter particle mobility and retention in porous media. To date, however, few modeling studies have considered the coupling of transport and particle aggregation processes. The majority of particle transport models employ an Eulerian modeling framework and are, consequently, limited in the types of collisions and aggregate sizes that can be considered. In this work, a more general Lagrangian modeling framework is developed and implemented to explore coupled nanoparticle aggregation and transport processes. The model was verified through comparison of model simulations to published results of an experimental and Eulerian modeling study (Raychoudhury et al., 2012) of carboxymethyl cellulose (CMC)-modified nano-sized zero-valent iron particle (nZVI) transport and retention in water-saturated sand columns. A model sensitivity analysis reveals the influence of influent particle concentration (ca. 70 to 700 mg/L), primary particle size (10-100 nm) and pore water velocity (ca. 1-6 m/day) on particle-particle, and, consequently, particle-collector interactions. Model simulations demonstrate that, when environmental conditions promote particle-particle interactions, neglecting aggregation effects can lead to under- or over-estimation of nanoparticle mobility. Results also suggest that the extent to which higher order particle-particle collisions influence aggregation kinetics will increase with the fraction of primary particles. This work demonstrates the potential importance of time-dependent aggregation processes on nanoparticle mobility and provides a numerical model capable of capturing/describing these interactions in water-saturated porous media.
Modeling coupled nanoparticle aggregation and transport in porous media: a Lagrangian approach.

PubMed

Taghavy, Amir; Pennell, Kurt D; Abriola, Linda M

2015-01-01

Changes in nanoparticle size and shape due to particle-particle interactions (i.e., aggregation or agglomeration) may significantly alter particle mobility and retention in porous media. To date, however, few modeling studies have considered the coupling of transport and particle aggregation processes. The majority of particle transport models employ an Eulerian modeling framework and are, consequently, limited in the types of collisions and aggregate sizes that can be considered. In this work, a more general Lagrangian modeling framework is developed and implemented to explore coupled nanoparticle aggregation and transport processes. The model was verified through comparison of model simulations to published results of an experimental and Eulerian modeling study (Raychoudhury et al., 2012) of carboxymethyl cellulose (CMC)-modified nano-sized zero-valent iron particle (nZVI) transport and retention in water-saturated sand columns. A model sensitivity analysis reveals the influence of influent particle concentration (ca. 70 to 700 mg/L), primary particle size (10-100 nm) and pore water velocity (ca. 1-6 m/day) on particle-particle, and, consequently, particle-collector interactions. Model simulations demonstrate that, when environmental conditions promote particle-particle interactions, neglecting aggregation effects can lead to under- or over-estimation of nanoparticle mobility. Results also suggest that the extent to which higher order particle-particle collisions influence aggregation kinetics will increase with the fraction of primary particles. This work demonstrates the potential importance of time-dependent aggregation processes on nanoparticle mobility and provides a numerical model capable of capturing/describing these interactions in water-saturated porous media. Copyright © 2014 Elsevier B.V. All rights reserved.
PAINeT: An object-oriented software package for simulations of flow-field, transport coefficients and flux terms in non-equilibrium gas mixture flows

NASA Astrophysics Data System (ADS)

Istomin, V. A.

2018-05-01

The software package Planet Atmosphere Investigator of Non-equilibrium Thermodynamics (PAINeT) has been devel-oped for studying the non-equilibrium effects associated with electronic excitation, chemical reactions and ionization. These studies are necessary for modeling process in shock tubes, in high enthalpy flows, in nozzles or jet engines, in combustion and explosion processes, in modern plasma-chemical and laser technologies. The advantages and possibilities of the package implementation are stated. Within the framework of the package implementation, based on kinetic theory approximations (one-temperature and state-to-state approaches), calculations are carried out, and the limits of applicability of a simplified description of shock-heated air flows and any other mixtures chosen by the user are given. Using kinetic theory algorithms, a numerical calculation of the heat fluxes and relaxation terms can be performed, which is necessary for further comparison of engineering simulation with experi-mental data. The influence of state-to-state distributions over electronic energy levels on the coefficients of thermal conductivity, diffusion, heat fluxes and diffusion velocities of the components of various gas mixtures behind shock waves is studied. Using the software package the accuracy of different approximations of the kinetic theory of gases is estimated. As an example state-resolved atomic ionized mixture of N/N+/O/O+/e- is considered. It is shown that state-resolved diffusion coefficients of neutral and ionized species vary from level to level. Comparing results of engineering applications with those given by PAINeT, recommendations for adequate models selection are proposed.
Kinetics of Methylmercury Production Revisited

DOE PAGES

Olsen, Todd A.; Muller, Katherine A.; Painter, Scott L.; ...

2018-01-27

Laboratory measurements of the biologically mediated methylation of mercury (Hg) to the neurotoxin monomethylmercury (MMHg) often exhibit kinetics that are inconsistent with first-order kinetic models. Using time-resolved measurements of filter passing Hg and MMHg during methylation/demethylation assays, a multisite kinetic sorption model, and reanalyses of previous assays, we show in this paper that competing kinetic sorption reactions can lead to time-varying availability and apparent non-first-order kinetics in Hg methylation and MMHg demethylation. The new model employing a multisite kinetic sorption model for Hg and MMHg can describe the range of behaviors for time-resolved methylation/demethylation data reported in the literature includingmore » those that exhibit non-first-order kinetics. Additionally, we show that neglecting competing sorption processes can confound analyses of methylation/demethylation assays, resulting in rate constant estimates that are systematically biased low. Finally, simulations of MMHg production and transport in a hypothetical periphyton biofilm bed illustrate the implications of our new model and demonstrate that methylmercury production may be significantly different than projected by single-rate first-order models.« less
Kinetic analysis of thermally relativistic flow with dissipation. II. Relativistic Boltzmann equation versus its kinetic models

NASA Astrophysics Data System (ADS)

Yano, Ryosuke; Matsumoto, Jun; Suzuki, Kojiro

2011-06-01

Thermally relativistic flow with dissipation was analyzed by solving the rarefied supersonic flow of thermally relativistic matter around a triangle prism by Yano and Suzuki [Phys. Rev. DPRVDAQ1550-7998 83, 023517 (2011)10.1103/PhysRevD.83.023517], where the Anderson-Witting (AW) model was used as a solver. In this paper, we solve the same problem, which was analyzed by Yano and Suzuki, using the relativistic Boltzmann equation (RBE). To solve the RBE, the conventional direct simulation Monte Carlo method for the nonrelativistic Boltzmann equation is extended to a new direct simulation Monte Carlo method for the RBE. Additionally, we solve the modified Marle (MM) model proposed by Yano-Suzuki-Kuroda for comparisons. The solution of the thermally relativistic shock layer around the triangle prism obtained using the relativistic Boltzmann equation is considered by focusing on profiles of macroscopic quantities, such as the density, velocity, temperature, heat flux and dynamic pressure along the stagnation streamline (SSL). Differences among profiles of the number density, velocity and temperature along the SSL obtained using the RBE, the AW and MM. models are described in the framework of the relativistic Navier-Stokes-Fourier law. Finally, distribution functions on the SSL obtained using the RBE are compared with those obtained using the AW and MM models. The distribution function inside the shock wave obtained using the RBE does not indicate a bimodal form, which is obtained using the AW and MM models, but a smooth deceleration of thermally relativistic matter inside a shock wave.
Cell-to-Cell Communication Circuits: Quantitative Analysis of Synthetic Logic Gates

PubMed Central

Hoffman-Sommer, Marta; Supady, Adriana; Klipp, Edda

2012-01-01

One of the goals in the field of synthetic biology is the construction of cellular computation devices that could function in a manner similar to electronic circuits. To this end, attempts are made to create biological systems that function as logic gates. In this work we present a theoretical quantitative analysis of a synthetic cellular logic-gates system, which has been implemented in cells of the yeast Saccharomyces cerevisiae (Regot et al., 2011). It exploits endogenous MAP kinase signaling pathways. The novelty of the system lies in the compartmentalization of the circuit where all basic logic gates are implemented in independent single cells that can then be cultured together to perform complex logic functions. We have constructed kinetic models of the multicellular IDENTITY, NOT, OR, and IMPLIES logic gates, using both deterministic and stochastic frameworks. All necessary model parameters are taken from literature or estimated based on published kinetic data, in such a way that the resulting models correctly capture important dynamic features of the included mitogen-activated protein kinase pathways. We analyze the models in terms of parameter sensitivity and we discuss possible ways of optimizing the system, e.g., by tuning the culture density. We apply a stochastic modeling approach, which simulates the behavior of whole populations of cells and allows us to investigate the noise generated in the system; we find that the gene expression units are the major sources of noise. Finally, the model is used for the design of system modifications: we show how the current system could be transformed to operate on three discrete values. PMID:22934039
Mirrored continuum and molecular scale simulations of the ignition of high-pressure phases of RDX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Kibaek; Stewart, D. Scott, E-mail: santc@illinois.edu, E-mail: dss@illinois.edu; Joshi, Kaushik

2016-05-14

We present a mirrored atomistic and continuum framework that is used to describe the ignition of energetic materials, and a high-pressure phase of RDX in particular. The continuum formulation uses meaningful averages of thermodynamic properties obtained from the atomistic simulation and a simplification of enormously complex reaction kinetics. In particular, components are identified based on molecular weight bin averages and our methodology assumes that both the averaged atomistic and continuum simulations are represented on the same time and length scales. The atomistic simulations of thermally initiated ignition of RDX are performed using reactive molecular dynamics (RMD). The continuum model ismore » based on multi-component thermodynamics and uses a kinetics scheme that describes observed chemical changes of the averaged atomistic simulations. Thus the mirrored continuum simulations mimic the rapid change in pressure, temperature, and average molecular weight of species in the reactive mixture. This mirroring enables a new technique to simplify the chemistry obtained from reactive MD simulations while retaining the observed features and spatial and temporal scales from both the RMD and continuum model. The primary benefit of this approach is a potentially powerful, but familiar way to interpret the atomistic simulations and understand the chemical events and reaction rates. The approach is quite general and thus can provide a way to model chemistry based on atomistic simulations and extend the reach of those simulations.« less
Unexpected variations in the triple oxygen isotope composition of stratospheric carbon dioxide

NASA Astrophysics Data System (ADS)

Wiegel, Aaron A.; Cole, Amanda S.; Hoag, Katherine J.; Atlas, Elliot L.; Schauffler, Sue M.; Boering, Kristie A.

2013-10-01

We report observations of stratospheric CO2 that reveal surprisingly large anomalous enrichments in 17O that vary systematically with latitude, altitude, and season. The triple isotope slopes reached 1.95 ± 0.05(1σ) in the middle stratosphere and 2.22 ± 0.07 in the Arctic vortex versus 1.71 ± 0.03 from previous observations and a remarkable factor of 4 larger than the mass-dependent value of 0.52. Kinetics modeling of laboratory measurements of photochemical ozone-CO2 isotope exchange demonstrates that non-mass-dependent isotope effects in ozone formation alone quantitatively account for the 17O anomaly in CO2 in the laboratory, resolving long-standing discrepancies between models and laboratory measurements. Model sensitivities to hypothetical mass-dependent isotope effects in reactions involving O3, O(1D), or CO2 and to an empirically derived temperature dependence of the anomalous kinetic isotope effects in ozone formation then provide a conceptual framework for understanding the differences in the isotopic composition and the triple isotope slopes between the laboratory and the stratosphere and between different regions of the stratosphere. This understanding in turn provides a firmer foundation for the diverse biogeochemical and paleoclimate applications of 17O anomalies in tropospheric CO2, O2, mineral sulfates, and fossil bones and teeth, which all derive from stratospheric CO2.

Investigation of resistance switching in SiO x RRAM cells using a 3D multi-scale kinetic Monte Carlo simulator

NASA Astrophysics Data System (ADS)

Sadi, Toufik; Mehonic, Adnan; Montesi, Luca; Buckwell, Mark; Kenyon, Anthony; Asenov, Asen

2018-02-01

We employ an advanced three-dimensional (3D) electro-thermal simulator to explore the physics and potential of oxide-based resistive random-access memory (RRAM) cells. The physical simulation model has been developed recently, and couples a kinetic Monte Carlo study of electron and ionic transport to the self-heating phenomenon while accounting carefully for the physics of vacancy generation and recombination, and trapping mechanisms. The simulation framework successfully captures resistance switching, including the electroforming, set and reset processes, by modeling the dynamics of conductive filaments in the 3D space. This work focuses on the promising yet less studied RRAM structures based on silicon-rich silica (SiO x ) RRAMs. We explain the intrinsic nature of resistance switching of the SiO x layer, analyze the effect of self-heating on device performance, highlight the role of the initial vacancy distributions acting as precursors for switching, and also stress the importance of using 3D physics-based models to capture accurately the switching processes. The simulation work is backed by experimental studies. The simulator is useful for improving our understanding of the little-known physics of SiO x resistive memory devices, as well as other oxide-based RRAM systems (e.g. transition metal oxide RRAMs), offering design and optimization capabilities with regard to the reliability and variability of memory cells.
Extracting surface diffusion coefficients from batch adsorption measurement data: application of the classic Langmuir kinetics model.

PubMed

Chu, Khim Hoong

2017-11-09

Surface diffusion coefficients may be estimated by fitting solutions of a diffusion model to batch kinetic data. For non-linear systems, a numerical solution of the diffusion model's governing equations is generally required. We report here the application of the classic Langmuir kinetics model to extract surface diffusion coefficients from batch kinetic data. The use of the Langmuir kinetics model in lieu of the conventional surface diffusion model allows derivation of an analytical expression. The parameter estimation procedure requires determining the Langmuir rate coefficient from which the pertinent surface diffusion coefficient is calculated. Surface diffusion coefficients within the 10 -9 to 10 -6 cm 2 /s range obtained by fitting the Langmuir kinetics model to experimental kinetic data taken from the literature are found to be consistent with the corresponding values obtained from the traditional surface diffusion model. The virtue of this simplified parameter estimation method is that it reduces the computational complexity as the analytical expression involves only an algebraic equation in closed form which is easily evaluated by spreadsheet computation.
Performance assessment of a pre-partitioned adaptive chemistry approach in large-eddy simulation of turbulent flames

NASA Astrophysics Data System (ADS)

Pepiot, Perrine; Liang, Youwen; Newale, Ashish; Pope, Stephen

2016-11-01

A pre-partitioned adaptive chemistry (PPAC) approach recently developed and validated in the simplified framework of a partially-stirred reactor is applied to the simulation of turbulent flames using a LES/particle PDF framework. The PPAC approach was shown to simultaneously provide significant savings in CPU and memory requirements, two major limiting factors in LES/particle PDF. The savings are achieved by providing each particle in the PDF method with a specialized reduced representation and kinetic model adjusted to its changing composition. Both representation and model are identified efficiently from a pre-determined list using a low-dimensional binary-tree search algorithm, thereby keeping the run-time overhead associated with the adaptive strategy to a minimum. The Sandia D flame is used as benchmark to quantify the performance of the PPAC algorithm in a turbulent combustion setting. In particular, the CPU and memory benefits, the distribution of the various representations throughout the computational domain, and the relationship between the user-defined error tolerances used to derive the reduced representations and models and the actual errors observed in LES/PDF are characterized. This material is based upon work supported by the U.S. Department of Energy Office of Science, Office of Basic Energy Sciences under Award Number DE-FG02-90ER14128.
A Biomonitoring Framework to Support Exposure and Risk Assessments

EPA Science Inventory

Background - Biomonitoring is used in exposure and risk assessments to reduce uncertainties along the source-to-outcome continuum. Specifically, biomarkers can help identify exposure sources, routes, and distributions, and reflect kinetic and dynamic processes following exposure ...
A Monte Carlo approach to the microdosimetric kinetic model to account for dose rate time structure effects in ion beam therapy with application in treatment planning simulations.

PubMed

Manganaro, Lorenzo; Russo, Germano; Cirio, Roberto; Dalmasso, Federico; Giordanengo, Simona; Monaco, Vincenzo; Muraro, Silvia; Sacchi, Roberto; Vignati, Anna; Attili, Andrea

2017-04-01

Advanced ion beam therapeutic techniques, such as hypofractionation, respiratory gating, or laser-based pulsed beams, have dose rate time structures which are substantially different from those found in conventional approaches. The biological impact of the time structure is mediated through the β parameter in the linear quadratic (LQ) model. The aim of this study was to assess the impact of changes in the value of the β parameter on the treatment outcomes, also accounting for noninstantaneous intrafraction dose delivery or fractionation and comparing the effects of using different primary ions. An original formulation of the microdosimetric kinetic model (MKM) is used (named MCt-MKM), in which a Monte Carlo (MC) approach was introduced to account for the stochastic spatio-temporal correlations characteristic of the irradiations and the cellular repair kinetics. A modified version of the kinetic equations, validated on experimental cell survival in vitro data, was also introduced. The model, trained on the HSG cells, was used to evaluate the relative biological effectiveness (RBE) for treatments with acute and protracted fractions. Exemplary cases of prostate cancer irradiated with different ion beams were evaluated to assess the impact of the temporal effects. The LQ parameters for a range of cell lines (V79, HSG, and T1) and ion species (H, He, C, and Ne) were evaluated and compared with the experimental data available in the literature, with good results. Notably, in contrast to the original MKM formulation, the MCt-MKM explicitly predicts an ion and LET-dependent β compatible with observations. The data from a split-dose experiment were used to experimentally determine the value of the parameter related to the cellular repair kinetics. Concerning the clinical case considered, an RBE decrease was observed, depending on the dose, ion, and LET, exceeding up to 3% of the acute value in the case of a protraction in the delivery of 10 min. The intercomparison between different ions shows that the clinical optimality is strongly dependent on a complex interplay between the different physical and biological quantities considered. The present study provides a framework for exploiting the temporal effects of dose delivery. The results show the possibility of optimizing the treatment outcomes accounting for the correlation between the specific dose rate time structure and the spatial characteristic of the LET distribution, depending on the ion type used. © 2017 American Association of Physicists in Medicine.
Viral kinetic modeling: state of the art

DOE PAGES

Canini, Laetitia; Perelson, Alan S.

2014-06-25

Viral kinetic modeling has led to increased understanding of the within host dynamics of viral infections and the effects of therapy. Here we review recent developments in the modeling of viral infection kinetics with emphasis on two infectious diseases: hepatitis C and influenza. We review how viral kinetic modeling has evolved from simple models of viral infections treated with a drug or drug cocktail with an assumed constant effectiveness to models that incorporate drug pharmacokinetics and pharmacodynamics, as well as phenomenological models that simply assume drugs have time varying-effectiveness. We also discuss multiscale models that include intracellular events in viralmore » replication, models of drug-resistance, models that include innate and adaptive immune responses and models that incorporate cell-to-cell spread of infection. Overall, viral kinetic modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs. In conclusion, we expect that viral kinetic modeling will be increasingly used in the coming years to optimize drug regimens in order to improve therapeutic outcomes and treatment tolerability for infectious diseases.« less
Nonparametric Residue Analysis of Dynamic PET Data With Application to Cerebral FDG Studies in Normals.

PubMed

O'Sullivan, Finbarr; Muzi, Mark; Spence, Alexander M; Mankoff, David M; O'Sullivan, Janet N; Fitzgerald, Niall; Newman, George C; Krohn, Kenneth A

2009-06-01

Kinetic analysis is used to extract metabolic information from dynamic positron emission tomography (PET) uptake data. The theory of indicator dilutions, developed in the seminal work of Meier and Zierler (1954), provides a probabilistic framework for representation of PET tracer uptake data in terms of a convolution between an arterial input function and a tissue residue. The residue is a scaled survival function associated with tracer residence in the tissue. Nonparametric inference for the residue, a deconvolution problem, provides a novel approach to kinetic analysis-critically one that is not reliant on specific compartmental modeling assumptions. A practical computational technique based on regularized cubic B-spline approximation of the residence time distribution is proposed. Nonparametric residue analysis allows formal statistical evaluation of specific parametric models to be considered. This analysis needs to properly account for the increased flexibility of the nonparametric estimator. The methodology is illustrated using data from a series of cerebral studies with PET and fluorodeoxyglucose (FDG) in normal subjects. Comparisons are made between key functionals of the residue, tracer flux, flow, etc., resulting from a parametric (the standard two-compartment of Phelps et al. 1979) and a nonparametric analysis. Strong statistical evidence against the compartment model is found. Primarily these differences relate to the representation of the early temporal structure of the tracer residence-largely a function of the vascular supply network. There are convincing physiological arguments against the representations implied by the compartmental approach but this is the first time that a rigorous statistical confirmation using PET data has been reported. The compartmental analysis produces suspect values for flow but, notably, the impact on the metabolic flux, though statistically significant, is limited to deviations on the order of 3%-4%. The general advantage of the nonparametric residue analysis is the ability to provide a valid kinetic quantitation in the context of studies where there may be heterogeneity or other uncertainty about the accuracy of a compartmental model approximation of the tissue residue.
Numerical simulation of the pollution formed by exhaust jets at the ground running procedure

NASA Astrophysics Data System (ADS)

Korotaeva, T. A.; Turchinovich, A. O.

2016-10-01

The paper presents an approach that is new for aviation-related ecology. The approach allows defining spatial distribution of pollutant concentrations released at engine ground running procedure (GRP) using full gas-dynamic models. For the first time such a task is modeled in three-dimensional approximation in the framework of the numerical solution of the Navier-Stokes equations with taking into account a kinetic model of interaction between the components of engine exhaust and air. The complex pattern of gas-dynamic flow that occurs at the flow around an aircraft with the jet exhausts that interact with each other, air, jet blast deflector (JBD), and surface of the airplane has been studied in the present work. The numerical technique developed for calculating the concentrations of pollutants produced at the GRP stage permits to define level, character, and area of contamination more reliable and increase accuracy in definition of sanitary protection zones.
Investigation into solar drying of potato: effect of sample geometry on drying kinetics and CO2 emissions mitigation.

PubMed

Tripathy, P P

2015-03-01

Drying experiments have been performed with potato cylinders and slices using a laboratory scale designed natural convection mixed-mode solar dryer. The drying data were fitted to eight different mathematical models to predict the drying kinetics, and the validity of these models were evaluated statistically through coefficient of determination (R(2)), root mean square error (RMSE) and reduced chi-square (χ (2)). The present investigation showed that amongst all the mathematical models studied, the Modified Page model was in good agreement with the experimental drying data for both potato cylinders and slices. A mathematical framework has been proposed to estimate the performance of the food dryer in terms of net CO2 emissions mitigation potential along with unit cost of CO2 mitigation arising because of replacement of different fossil fuels by renewable solar energy. For each fossil fuel replaced, the gross annual amount of CO2 as well as net amount of annual CO2 emissions mitigation potential considering CO2 emissions embodied in the manufacture of mixed-mode solar dryer has been estimated. The CO2 mitigation potential and amount of fossil fuels saved while drying potato samples were found to be the maximum for coal followed by light diesel oil and natural gas. It was inferred from the present study that by the year 2020, 23 % of CO2 emissions can be mitigated by the use of mixed-mode solar dryer for drying of agricultural products.
A Multiscale Computational Model of the Response of Swine Epidermis After Acute Irradiation

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2012-01-01

Radiation exposure from Solar Particle Events can lead to very high skin dose for astronauts on exploration missions outside the protection of the Earth s magnetic field [1]. Assessing the detrimental effects to human skin under such adverse conditions could be predicted by conducting territorial experiments on animal models. In this study we apply a computational approach to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis [2]. Incorporating experimentally measured histological and cell kinetic parameters into a multiscale tissue modeling framework, we obtain results of population kinetics and proliferation index comparable to unirradiated and acutely irradiated swine experiments [3]. It is noted the basal cell doubling time is 10 to 16 days in the intact population, but drops to 13.6 hr in the regenerating populations surviving irradiation. This complex 30-fold variation is proposed to be attributed to the shortening of the G1 phase duration. We investigate this radiation induced effect by considering at the sub-cellular level the expression and signaling of TGF-beta, as it is recognized as a key regulatory factor of tissue formation and wound healing [4]. This integrated model will allow us to test the validity of various basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and should lead to a fuller understanding of the pathophysiological effects of ionizing radiation on the skin.
A study of the kinetic energy generation with general circulation models

NASA Technical Reports Server (NTRS)

Chen, T.-C.; Lee, Y.-H.

1983-01-01

The history data of winter simulation by the GLAS climate model and the NCAR community climate model are used to examine the generation of atmospheric kinetic energy. The contrast between the geographic distributions of the generation of kinetic energy and divergence of kinetic energy flux shows that kinetic energy is generated in the upstream side of jets, transported to the downstream side and destroyed there. The contributions from the time-mean and transient modes to the counterbalance between generation of kinetic energy and divergence of kinetic energy flux are also investigated. It is observed that the kinetic energy generated by the time-mean mode is essentially redistributed by the time-mean flow, while that generated by the transient flow is mainly responsible for the maintenance of the kinetic energy of the entire atmospheric flow.
Modeling Flare Hard X-ray Emission from Electrons in Contracting Magnetic Islands

NASA Astrophysics Data System (ADS)

Guidoni, Silvina E.; Allred, Joel C.; Alaoui, Meriem; Holman, Gordon D.; DeVore, C. Richard; Karpen, Judith T.

2016-05-01

The mechanism that accelerates particles to the energies required to produce the observed impulsive hard X-ray emission in solar flares is not well understood. It is generally accepted that this emission is produced by a non-thermal beam of electrons that collides with the ambient ions as the beam propagates from the top of a flare loop to its footpoints. Most current models that investigate this transport assume an injected beam with an initial energy spectrum inferred from observed hard X-ray spectra, usually a power law with a low-energy cutoff. In our previous work (Guidoni et al. 2016), we proposed an analytical method to estimate particle energy gain in contracting, large-scale, 2.5-dimensional magnetic islands, based on a kinetic model by Drake et al. (2010). We applied this method to sunward-moving islands formed high in the corona during fast reconnection in a simulated eruptive flare. The overarching purpose of the present work is to test this proposed acceleration model by estimating the hard X-ray flux resulting from its predicted accelerated-particle distribution functions. To do so, we have coupled our model to a unified computational framework that simulates the propagation of an injected beam as it deposits energy and momentum along its way (Allred et al. 2015). This framework includes the effects of radiative transfer and return currents, necessary to estimate flare emission that can be compared directly to observations. We will present preliminary results of the coupling between these models.
Computational Modeling of Neurotransmitter Release Evoked by Electrical Stimulation: Nonlinear Approaches to Predicting Stimulation-Evoked Dopamine Release.

PubMed

Trevathan, James K; Yousefi, Ali; Park, Hyung Ook; Bartoletta, John J; Ludwig, Kip A; Lee, Kendall H; Lujan, J Luis

2017-02-15

Neurochemical changes evoked by electrical stimulation of the nervous system have been linked to both therapeutic and undesired effects of neuromodulation therapies used to treat obsessive-compulsive disorder, depression, epilepsy, Parkinson's disease, stroke, hypertension, tinnitus, and many other indications. In fact, interest in better understanding the role of neurochemical signaling in neuromodulation therapies has been a focus of recent government- and industry-sponsored programs whose ultimate goal is to usher in an era of personalized medicine by creating neuromodulation therapies that respond to real-time changes in patient status. A key element to achieving these precision therapeutic interventions is the development of mathematical modeling approaches capable of describing the nonlinear transfer function between neuromodulation parameters and evoked neurochemical changes. Here, we propose two computational modeling frameworks, based on artificial neural networks (ANNs) and Volterra kernels, that can characterize the input/output transfer functions of stimulation-evoked neurochemical release. We evaluate the ability of these modeling frameworks to characterize subject-specific neurochemical kinetics by accurately describing stimulation-evoked dopamine release across rodent (R 2 = 0.83 Volterra kernel, R 2 = 0.86 ANN), swine (R 2 = 0.90 Volterra kernel, R 2 = 0.93 ANN), and non-human primate (R 2 = 0.98 Volterra kernel, R 2 = 0.96 ANN) models of brain stimulation. Ultimately, these models will not only improve understanding of neurochemical signaling in healthy and diseased brains but also facilitate the development of neuromodulation strategies capable of controlling neurochemical release via closed-loop strategies.
Tuning Precursor Reactivity toward Nanometer-Size Control in Palladium Nanoparticles Studied by in Situ Small Angle X-ray Scattering

DOE PAGES

Wu, Liheng; Lian, Huada; Willis, Joshua J.; ...

2018-01-03

Synthesis of monodisperse nanoparticles (NPs) with precisely controlled size is critical for understanding their size-dependent properties. Although significant synthetic developments have been achieved, it is still challenging to synthesize well-defined NPs in a predictive way due to a lack of in-depth mechanistic understanding of reaction kinetics. Here we use synchrotron-based small-angle X-ray scattering (SAXS) to monitor in situ the formation of palladium (Pd) NPs through thermal decomposition of Pd–TOP (TOP: trioctylphosphine) complex via the “heat-up” method. We systematically study the effects of different ligands, including oleylamine, TOP, and oleic acid, on the formation kinetics of Pd NPs. Through quantitative analysismore » of the real-time SAXS data, we are able to obtain a detailed picture of the size, size distribution, and concentration of Pd NPs during the syntheses, and these results show that different ligands strongly affect the precursor reactivity. We find that oleylamine does not change the reactivity of the Pd–TOP complex but promote the formation of nuclei due to strong ligand–NP binding. On the other hand, TOP and oleic acid substantially change the precursor reactivity over more than an order of magnitude, which controls the nucleation kinetics and determines the final particle size. A theoretical model is used to demonstrate that the nucleation and growth kinetics are dependent on both precursor reactivity and ligand–NP binding affinity, thus providing a framework to explain the synthesis process and the effect of the reaction conditions. Quantitative understanding of the impacts of different ligands enables the successful synthesis of a series of monodisperse Pd NPs in the broad size range from 3 to 11 nm with nanometer-size control, which serve as a model system to study their size-dependent catalytic properties. Furthermore, the in situ SAXS probing can be readily extended to other functional NPs to greatly advance their synthetic design.« less
Tuning Precursor Reactivity toward Nanometer-Size Control in Palladium Nanoparticles Studied by in Situ Small Angle X-ray Scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Liheng; Lian, Huada; Willis, Joshua J.

Synthesis of monodisperse nanoparticles (NPs) with precisely controlled size is critical for understanding their size-dependent properties. Although significant synthetic developments have been achieved, it is still challenging to synthesize well-defined NPs in a predictive way due to a lack of in-depth mechanistic understanding of reaction kinetics. Here we use synchrotron-based small-angle X-ray scattering (SAXS) to monitor in situ the formation of palladium (Pd) NPs through thermal decomposition of Pd–TOP (TOP: trioctylphosphine) complex via the “heat-up” method. We systematically study the effects of different ligands, including oleylamine, TOP, and oleic acid, on the formation kinetics of Pd NPs. Through quantitative analysismore » of the real-time SAXS data, we are able to obtain a detailed picture of the size, size distribution, and concentration of Pd NPs during the syntheses, and these results show that different ligands strongly affect the precursor reactivity. We find that oleylamine does not change the reactivity of the Pd–TOP complex but promote the formation of nuclei due to strong ligand–NP binding. On the other hand, TOP and oleic acid substantially change the precursor reactivity over more than an order of magnitude, which controls the nucleation kinetics and determines the final particle size. A theoretical model is used to demonstrate that the nucleation and growth kinetics are dependent on both precursor reactivity and ligand–NP binding affinity, thus providing a framework to explain the synthesis process and the effect of the reaction conditions. Quantitative understanding of the impacts of different ligands enables the successful synthesis of a series of monodisperse Pd NPs in the broad size range from 3 to 11 nm with nanometer-size control, which serve as a model system to study their size-dependent catalytic properties. Furthermore, the in situ SAXS probing can be readily extended to other functional NPs to greatly advance their synthetic design.« less
Simulation-Based Design for Wearable Robotic Systems: An Optimization Framework for Enhancing a Standing Long Jump.

PubMed

Ong, Carmichael F; Hicks, Jennifer L; Delp, Scott L

2016-05-01

Technologies that augment human performance are the focus of intensive research and development, driven by advances in wearable robotic systems. Success has been limited by the challenge of understanding human-robot interaction. To address this challenge, we developed an optimization framework to synthesize a realistic human standing long jump and used the framework to explore how simulated wearable robotic devices might enhance jump performance. A planar, five-segment, seven-degree-of-freedom model with physiological torque actuators, which have variable torque capacity depending on joint position and velocity, was used to represent human musculoskeletal dynamics. An active augmentation device was modeled as a torque actuator that could apply a single pulse of up to 100 Nm of extension torque. A passive design was modeled as rotational springs about each lower limb joint. Dynamic optimization searched for physiological and device actuation patterns to maximize jump distance. Optimization of the nominal case yielded a 2.27 m jump that captured salient kinematic and kinetic features of human jumps. When the active device was added to the ankle, knee, or hip, jump distance increased to between 2.49 and 2.52 m. Active augmentation of all three joints increased the jump distance to 3.10 m. The passive design increased jump distance to 3.32 m by adding torques of 135, 365, and 297 Nm to the ankle, knee, and hip, respectively. Dynamic optimization can be used to simulate a standing long jump and investigate human-robot interaction. Simulation can aid in the design of performance-enhancing technologies.
Application and theoretical analysis of the flamelet model for supersonic turbulent combustion flows in the scramjet engine

NASA Astrophysics Data System (ADS)

Gao, Zhenxun; Wang, Jingying; Jiang, Chongwen; Lee, Chunhian

2014-11-01

In the framework of Reynolds-averaged Navier-Stokes simulation, supersonic turbulent combustion flows at the German Aerospace Centre (DLR) combustor and Japan Aerospace Exploration Agency (JAXA) integrated scramjet engine are numerically simulated using the flamelet model. Based on the DLR combustor case, theoretical analysis and numerical experiments conclude that: the finite rate model only implicitly considers the large-scale turbulent effect and, due to the lack of the small-scale non-equilibrium effect, it would overshoot the peak temperature compared to the flamelet model in general. Furthermore, high-Mach-number compressibility affects the flamelet model mainly through two ways: the spatial pressure variation and the static enthalpy variation due to the kinetic energy. In the flamelet library, the mass fractions of the intermediate species, e.g. OH, are more sensible to the above two effects than the main species such as H2O. Additionally, in the combustion flowfield where the pressure is larger than the value adopted in the generation of the flamelet library or the conversion from the static enthalpy to the kinetic energy occurs, the temperature obtained by the flamelet model without taking compressibility effects into account would be undershot, and vice versa. The static enthalpy variation effect has only little influence on the temperature simulation of the flamelet model, while the effect of the spatial pressure variation may cause relatively large errors. From the JAXA case, it is found that the flamelet model cannot in general be used for an integrated scramjet engine. The existence of the inlet together with the transverse injection scheme could cause large spatial variations of pressure, so the pressure value adopted for the generation of a flamelet library should be fine-tuned according to a pre-simulation of pure mixing.
Phase-field Model for Interstitial Loop Growth Kinetics and Thermodynamic and Kinetic Models of Irradiated Fe-Cr Alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Yulan; Hu, Shenyang Y.; Sun, Xin

2011-06-15

Microstructure evolution kinetics in irradiated materials has strongly spatial correlation. For example, void and second phases prefer to nucleate and grow at pre-existing defects such as dislocations, grain boundaries, and cracks. Inhomogeneous microstructure evolution results in inhomogeneity of microstructure and thermo-mechanical properties. Therefore, the simulation capability for predicting three dimensional (3-D) microstructure evolution kinetics and its subsequent impact on material properties and performance is crucial for scientific design of advanced nuclear materials and optimal operation conditions in order to reduce uncertainty in operational and safety margins. Very recently the meso-scale phase-field (PF) method has been used to predict gas bubblemore » evolution, void swelling, void lattice formation and void migration in irradiated materials,. Although most results of phase-field simulations are qualitative due to the lake of accurate thermodynamic and kinetic properties of defects, possible missing of important kinetic properties and processes, and the capability of current codes and computers for large time and length scale modeling, the simulations demonstrate that PF method is a promising simulation tool for predicting 3-D heterogeneous microstructure and property evolution, and providing microstructure evolution kinetics for higher scale level simulations of microstructure and property evolution such as mean field methods. This report consists of two parts. In part I, we will present a new phase-field model for predicting interstitial loop growth kinetics in irradiated materials. The effect of defect (vacancy/interstitial) generation, diffusion and recombination, sink strength, long-range elastic interaction, inhomogeneous and anisotropic mobility on microstructure evolution kinetics is taken into account in the model. The model is used to study the effect of elastic interaction on interstitial loop growth kinetics, the interstitial flux, and sink strength of interstitial loop for interstitials. In part II, we present a generic phase field model and discuss the thermodynamic and kinetic properties in phase-field models including the reaction kinetics of radiation defects and local free energy of irradiated materials. In particular, a two-sublattice thermodynamic model is suggested to describe the local free energy of alloys with irradiated defects. Fe-Cr alloy is taken as an example to explain the required thermodynamic and kinetic properties for quantitative phase-field modeling. Finally the great challenges in phase-field modeling will be discussed.« less
Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Koh, Chuan Hock; Miyano, Satoru

2011-05-01

Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.
Biological dose estimation for charged-particle therapy using an improved PHITS code coupled with a microdosimetric kinetic model.

PubMed

Sato, Tatsuhiko; Kase, Yuki; Watanabe, Ritsuko; Niita, Koji; Sihver, Lembit

2009-01-01

Microdosimetric quantities such as lineal energy, y, are better indexes for expressing the RBE of HZE particles in comparison to LET. However, the use of microdosimetric quantities in computational dosimetry is severely limited because of the difficulty in calculating their probability densities in macroscopic matter. We therefore improved the particle transport simulation code PHITS, providing it with the capability of estimating the microdosimetric probability densities in a macroscopic framework by incorporating a mathematical function that can instantaneously calculate the probability densities around the trajectory of HZE particles with a precision equivalent to that of a microscopic track-structure simulation. A new method for estimating biological dose, the product of physical dose and RBE, from charged-particle therapy was established using the improved PHITS coupled with a microdosimetric kinetic model. The accuracy of the biological dose estimated by this method was tested by comparing the calculated physical doses and RBE values with the corresponding data measured in a slab phantom irradiated with several kinds of HZE particles. The simulation technique established in this study will help to optimize the treatment planning of charged-particle therapy, thereby maximizing the therapeutic effect on tumors while minimizing unintended harmful effects on surrounding normal tissues.

Direct reconstruction of pharmacokinetic parameters in dynamic fluorescence molecular tomography by the augmented Lagrangian method

NASA Astrophysics Data System (ADS)

Zhu, Dianwen; Zhang, Wei; Zhao, Yue; Li, Changqing

2016-03-01

Dynamic fluorescence molecular tomography (FMT) has the potential to quantify physiological or biochemical information, known as pharmacokinetic parameters, which are important for cancer detection, drug development and delivery etc. To image those parameters, there are indirect methods, which are easier to implement but tend to provide images with low signal-to-noise ratio, and direct methods, which model all the measurement noises together and are statistically more efficient. The direct reconstruction methods in dynamic FMT have attracted a lot of attention recently. However, the coupling of tomographic image reconstruction and nonlinearity of kinetic parameter estimation due to the compartment modeling has imposed a huge computational burden to the direct reconstruction of the kinetic parameters. In this paper, we propose to take advantage of both the direct and indirect reconstruction ideas through a variable splitting strategy under the augmented Lagrangian framework. Each iteration of the direct reconstruction is split into two steps: the dynamic FMT image reconstruction and the node-wise nonlinear least squares fitting of the pharmacokinetic parameter images. Through numerical simulation studies, we have found that the proposed algorithm can achieve good reconstruction results within a small amount of time. This will be the first step for a combined dynamic PET and FMT imaging in the future.
The decay of isotropic magnetohydrodynamics turbulence and the effects of cross-helicity

NASA Astrophysics Data System (ADS)

Briard, Antoine; Gomez, Thomas

2018-02-01

Decaying homogeneous and isotropic magnetohydrodynamics (MHD) turbulence is investigated numerically at large Reynolds numbers thanks to the eddy-damped quasi-normal Markovian (EDQNM) approximation. Without any background mean magnetic field, the total energy spectrum scales as -3/2$ in the inertial range as a consequence of the modelling. Moreover, the total energy is shown, both analytically and numerically, to decay at the same rate as kinetic energy in hydrodynamic isotropic turbulence: this differs from a previous prediction, and thus physical arguments are proposed to reconcile both results. Afterwards, the MHD turbulence is made imbalanced by an initial non-zero cross-helicity. A spectral modelling is developed for the velocity-magnetic correlation in a general homogeneous framework, which reveals that cross-helicity can contain subtle anisotropic effects. In the inertial range, as the Reynolds number increases, the slope of the cross-helical spectrum becomes closer to -5/3$ than -2$ . Furthermore, the Elsässer spectra deviate from -3/2$ with cross-helicity at large Reynolds numbers. Regarding the pressure spectrum P$ , its kinetic and magnetic parts are found to scale with -2$ in the inertial range, whereas the part due to cross-helicity rather scales in -7/3$ . Finally, the two rd laws for the total energy and cross-helicity are assessed numerically at large Reynolds numbers.
Large scale structures in the kinetic gravity braiding model that can be unbraided

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kimura, Rampei; Yamamoto, Kazuhiro, E-mail: rampei@theo.phys.sci.hiroshima-u.ac.jp, E-mail: kazuhiro@hiroshima-u.ac.jp

2011-04-01

We study cosmological consequences of a kinetic gravity braiding model, which is proposed as an alternative to the dark energy model. The kinetic braiding model we study is characterized by a parameter n, which corresponds to the original galileon cosmological model for n = 1. We find that the background expansion of the universe of the kinetic braiding model is the same as the Dvali-Turner's model, which reduces to that of the standard cold dark matter model with a cosmological constant (ΛCDM model) for n equal to infinity. We also find that the evolution of the linear cosmological perturbation inmore » the kinetic braiding model reduces to that of the ΛCDM model for n = ∞. Then, we focus our study on the growth history of the linear density perturbation as well as the spherical collapse in the nonlinear regime of the density perturbations, which might be important in order to distinguish between the kinetic braiding model and the ΛCDM model when n is finite. The theoretical prediction for the large scale structure is confronted with the multipole power spectrum of the luminous red galaxy sample of the Sloan Digital Sky survey. We also discuss future prospects of constraining the kinetic braiding model using a future redshift survey like the WFMOS/SuMIRe PFS survey as well as the cluster redshift distribution in the South Pole Telescope survey.« less
Modeling of autocatalytic hydrolysis of adefovir dipivoxil in solid formulations.

PubMed

Dong, Ying; Zhang, Yan; Xiang, Bingren; Deng, Haishan; Wu, Jingfang

2011-04-01

The stability and hydrolysis kinetics of a phosphate prodrug, adefovir dipivoxil, in solid formulations were studied. The stability relationship between five solid formulations was explored. An autocatalytic mechanism for hydrolysis could be proposed according to the kinetic behavior which fits the Prout-Tompkins model well. For the classical kinetic models could hardly describe and predict the hydrolysis kinetics of adefovir dipivoxil in solid formulations accurately when the temperature is high, a feedforward multilayer perceptron (MLP) neural network was constructed to model the hydrolysis kinetics. The build-in approaches in Weka, such as lazy classifiers and rule-based learners (IBk, KStar, DecisionTable and M5Rules), were used to verify the performance of MLP. The predictability of the models was evaluated by 10-fold cross-validation and an external test set. It reveals that MLP should be of general applicability proposing an alternative efficient way to model and predict autocatalytic hydrolysis kinetics for phosphate prodrugs.
A Study of the Optimal Model of the Flotation Kinetics of Copper Slag from Copper Mine BOR

NASA Astrophysics Data System (ADS)

Stanojlović, Rodoljub D.; Sokolović, Jovica M.

2014-10-01

In this study the effect of mixtures of copper slag and flotation tailings from copper mine Bor, Serbia on the flotation results of copper recovery and flotation kinetics parameters in a batch flotation cell has been investigated. By simultaneous adding old flotation tailings in the ball mill at the rate of 9%, it is possible to increase copper recovery for about 20%. These results are compared with obtained copper recovery of pure copper slag. The results of batch flotation test were fitted by MatLab software for modeling the first-order flotation kinetics in order to determine kinetics parameters and define an optimal model of the flotation kinetics. Six kinetic models are tested on the batch flotation copper recovery against flotation time. All models showed good correlation, however the modified Kelsall model provided the best fit.
Kinetic Equations for Describing the Liquid-Glass Transition in Polymers

NASA Astrophysics Data System (ADS)

Aksenov, V. L.; Tropin, T. V.; Schmelzer, J. V. P.

2018-01-01

We present a theoretical approach based on nonequilibrium thermodynamics and used to describe the kinetics of the transition from the liquid to the glassy state (glass transition). In the framework of this approach, we construct kinetic equations describing the time and temperature evolution of the structural parameter. We discuss modifications of the equations required for taking the nonexponential, nonlinear character of the relaxation in the vitrification region into account. To describe the formation of polymer glasses, we present modified expressions for the system relaxation time. We compare the obtained results with experimental data, measurements of the polystyrene glass transition for different cooling rates using the method of differential scanning calorimetry. We discuss prospects for developing a method for describing the polymer glass transition.
Trapping guests within a nanoporous metal-organic framework through pressure-induced amorphization.

PubMed

Chapman, Karena W; Sava, Dorina F; Halder, Gregory J; Chupas, Peter J; Nenoff, Tina M

2011-11-23

The release of guest species from within a nanoporous metal-organic framework (MOF) has been inhibited by amorphization of the guest-loaded framework structure under applied pressure. Thermogravimetric analyses have shown that by amorphizing ZIF-8 following sorption of molecular I(2), a hazardous radiological byproduct of nuclear energy production, the pore apertures in the framework are sufficiently distorted to kinetically trap I(2) and improve I(2) retention. Pair distribution function (PDF) analysis indicates that the local structure of the captive I(2) remains essentially unchanged upon amorphization of the framework, with the amorphization occurring under the same conditions for the vacant and guest-loaded framework. The low, accessible pressure range needed to effect this change in desorption is much lower than in tradition sorbents such as zeolites, opening the possibility for new molecular capture, interim storage, or controlled release applications.
Geometric decompositions of collective motion

NASA Astrophysics Data System (ADS)

Mischiati, Matteo; Krishnaprasad, P. S.

2017-04-01

Collective motion in nature is a captivating phenomenon. Revealing the underlying mechanisms, which are of biological and theoretical interest, will require empirical data, modelling and analysis techniques. Here, we contribute a geometric viewpoint, yielding a novel method of analysing movement. Snapshots of collective motion are portrayed as tangent vectors on configuration space, with length determined by the total kinetic energy. Using the geometry of fibre bundles and connections, this portrait is split into orthogonal components each tangential to a lower dimensional manifold derived from configuration space. The resulting decomposition, when interleaved with classical shape space construction, is categorized into a family of kinematic modes-including rigid translations, rigid rotations, inertia tensor transformations, expansions and compressions. Snapshots of empirical data from natural collectives can be allocated to these modes and weighted by fractions of total kinetic energy. Such quantitative measures can provide insight into the variation of the driving goals of a collective, as illustrated by applying these methods to a publicly available dataset of pigeon flocking. The geometric framework may also be profitably employed in the control of artificial systems of interacting agents such as robots.
Dilatometric investigation of α(orthorhombic)→β(tetragonal) transformation in U-15 wt.% Cr alloy

NASA Astrophysics Data System (ADS)

Rameshkumar, Santhosh; Raju, Subramanian; Saibaba, Saroja

2018-04-01

The α→β transformation characteristics in U-15wt.% Cr alloy have been investigated by dilatometry at slow heating rates (3-10 K min-1). The starting microstructure of U-15Cr alloy consists of a mixture of metastable βm-U(body centred tetroganal), α-U(orthorhombic) and elemental Cr(bcc) phases. Upon heating, the metastable βmU phase has progressively transformed to equilibrium α-U structure; before, finally undergoing equilibrium α→β transformation with further increase in temperature. The measured α→β transformation temperature, when extrapolated to 0 K min-1 heating rate has been found to be higher than the currently accepted equilibrium phase diagram estimate. This is due to the kinetic difficulty associated with Cr-diffusion in U-15Cr alloy. The kinetics of α→β transformation upon continuous heating has been modeled in terms of a suitable framework for diffusional transformations, and the effective activation energy for overall transformation has been estimated to be in the range 160-180 kJ mol-1.
Simulation of the M13 life cycle I: Assembly of a genetically-structured deterministic chemical kinetic simulation.

PubMed

Smeal, Steven W; Schmitt, Margaret A; Pereira, Ronnie Rodrigues; Prasad, Ashok; Fisk, John D

2017-01-01

To expand the quantitative, systems level understanding and foster the expansion of the biotechnological applications of the filamentous bacteriophage M13, we have unified the accumulated quantitative information on M13 biology into a genetically-structured, experimentally-based computational simulation of the entire phage life cycle. The deterministic chemical kinetic simulation explicitly includes the molecular details of DNA replication, mRNA transcription, protein translation and particle assembly, as well as the competing protein-protein and protein-nucleic acid interactions that control the timing and extent of phage production. The simulation reproduces the holistic behavior of M13, closely matching experimentally reported values of the intracellular levels of phage species and the timing of events in the M13 life cycle. The computational model provides a quantitative description of phage biology, highlights gaps in the present understanding of M13, and offers a framework for exploring alternative mechanisms of regulation in the context of the complete M13 life cycle. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Geometric decompositions of collective motion

PubMed Central

Krishnaprasad, P. S.

2017-01-01

Collective motion in nature is a captivating phenomenon. Revealing the underlying mechanisms, which are of biological and theoretical interest, will require empirical data, modelling and analysis techniques. Here, we contribute a geometric viewpoint, yielding a novel method of analysing movement. Snapshots of collective motion are portrayed as tangent vectors on configuration space, with length determined by the total kinetic energy. Using the geometry of fibre bundles and connections, this portrait is split into orthogonal components each tangential to a lower dimensional manifold derived from configuration space. The resulting decomposition, when interleaved with classical shape space construction, is categorized into a family of kinematic modes—including rigid translations, rigid rotations, inertia tensor transformations, expansions and compressions. Snapshots of empirical data from natural collectives can be allocated to these modes and weighted by fractions of total kinetic energy. Such quantitative measures can provide insight into the variation of the driving goals of a collective, as illustrated by applying these methods to a publicly available dataset of pigeon flocking. The geometric framework may also be profitably employed in the control of artificial systems of interacting agents such as robots. PMID:28484319
A Comprehensive Breath Plume Model for Disease Transmission via Expiratory Aerosols

PubMed Central

Halloran, Siobhan K.; Wexler, Anthony S.; Ristenpart, William D.

2012-01-01

The peak in influenza incidence during wintertime in temperate regions represents a longstanding, unresolved scientific question. One hypothesis is that the efficacy of airborne transmission via aerosols is increased at lower humidities and temperatures, conditions that prevail in wintertime. Recent work with a guinea pig model by Lowen et al. indicated that humidity and temperature do modulate airborne influenza virus transmission, and several investigators have interpreted the observed humidity dependence in terms of airborne virus survivability. This interpretation, however, neglects two key observations: the effect of ambient temperature on the viral growth kinetics within the animals, and the strong influence of the background airflow on transmission. Here we provide a comprehensive theoretical framework for assessing the probability of disease transmission via expiratory aerosols between test animals in laboratory conditions. The spread of aerosols emitted from an infected animal is modeled using dispersion theory for a homogeneous turbulent airflow. The concentration and size distribution of the evaporating droplets in the resulting “Gaussian breath plume” are calculated as functions of position, humidity, and temperature. The overall transmission probability is modeled with a combination of the time-dependent viral concentration in the infected animal and the probability of droplet inhalation by the exposed animal downstream. We demonstrate that the breath plume model is broadly consistent with the results of Lowen et al., without invoking airborne virus survivability. The results also suggest that, at least for guinea pigs, variation in viral kinetics within the infected animals is the dominant factor explaining the increased transmission probability observed at lower temperatures. PMID:22615902
Kinetic Model of Growth of Arthropoda Populations

NASA Astrophysics Data System (ADS)

Ershov, Yu. A.; Kuznetsov, M. A.

2018-05-01

Kinetic equations were derived for calculating the growth of crustacean populations ( Crustacea) based on the biological growth model suggested earlier using shrimp ( Caridea) populations as an example. The development cycle of successive stages for populations can be represented in the form of quasi-chemical equations. The kinetic equations that describe the development cycle of crustaceans allow quantitative prediction of the development of populations depending on conditions. In contrast to extrapolation-simulation models, in the developed kinetic model of biological growth the kinetic parameters are the experimental characteristics of population growth. Verification and parametric identification of the developed model on the basis of the experimental data showed agreement with experiment within the error of the measurement technique.
Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

PubMed

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.
Stochasticity in materials structure, properties, and processing—A review

NASA Astrophysics Data System (ADS)

Hull, Robert; Keblinski, Pawel; Lewis, Dan; Maniatty, Antoinette; Meunier, Vincent; Oberai, Assad A.; Picu, Catalin R.; Samuel, Johnson; Shephard, Mark S.; Tomozawa, Minoru; Vashishth, Deepak; Zhang, Shengbai

2018-03-01

We review the concept of stochasticity—i.e., unpredictable or uncontrolled fluctuations in structure, chemistry, or kinetic processes—in materials. We first define six broad classes of stochasticity: equilibrium (thermodynamic) fluctuations; structural/compositional fluctuations; kinetic fluctuations; frustration and degeneracy; imprecision in measurements; and stochasticity in modeling and simulation. In this review, we focus on the first four classes that are inherent to materials phenomena. We next develop a mathematical framework for describing materials stochasticity and then show how it can be broadly applied to these four materials-related stochastic classes. In subsequent sections, we describe structural and compositional fluctuations at small length scales that modify material properties and behavior at larger length scales; systems with engineered fluctuations, concentrating primarily on composite materials; systems in which stochasticity is developed through nucleation and kinetic phenomena; and configurations in which constraints in a given system prevent it from attaining its ground state and cause it to attain several, equally likely (degenerate) states. We next describe how stochasticity in these processes results in variations in physical properties and how these variations are then accentuated by—or amplify—stochasticity in processing and manufacturing procedures. In summary, the origins of materials stochasticity, the degree to which it can be predicted and/or controlled, and the possibility of using stochastic descriptions of materials structure, properties, and processing as a new degree of freedom in materials design are described.
A kinetic clutch governs uncoiling by type IB topoisomerases

NASA Astrophysics Data System (ADS)

Neuman, Keir

2013-03-01

Type IB topoisomerases (Top1B) are essential enzymes that relax excessive DNA supercoiling associated with replication and transcription and are important drug targets for cancer chemotherapy. The natural compound camptothecin (CPT) and the cancer chemotherapeutics derived from it, irinotecan and topotecan, are highly specific inhibitors of human nuclear Type IB topoisomerase (nTop1). We employed a magnetic-tweezers based single-molecule DNA supercoil relaxation assay to measure the torque dependence of human nuclear Top1 relaxation (nTop1) and inhibition by CPT. For comparison, we examined the human mitochondrial (Top1mt) topoisomerase and an N-terminal deletion mutant of nTop1 (Top68). Despite substantial sequence homology in their core domains, nTop1 and Top1mt exhibit dramatic differences in sensitivity to torque and CPT, with Top68 betraying intermediate characteristics. In particular, nTop1 displays nearly torque-independent religation probability, distinguishing it from other Top1B enzymes studied to date. Kinetic modeling reveals a hitherto unobserved torque-independent transition linking the DNA rotation and religation phases of the enzymatic cycle. The parameters of this transition determine the torque sensitivity of religation, and the efficiency of CPT binding. This ``kinetic clutch'' mechanism explains the molecular basis of CPT sensitivity and more generally provides a framework with which to interpret Top1B activity and inhibition.
Time-dependent observables in heavy ion collisions. Part II. In search of pressure isotropization in the φ 4 theory

NASA Astrophysics Data System (ADS)

Kovchegov, Yuri V.; Wu, Bin

2018-03-01

To understand the dynamics of thermalization in heavy ion collisions in the perturbative framework it is essential to first find corrections to the free-streaming classical gluon fields of the McLerran-Venugopalan model. The corrections that lead to deviations from free streaming (and that dominate at late proper time) would provide evidence for the onset of isotropization (and, possibly, thermalization) of the produced medium. To find such corrections we calculate the late-time two-point Green function and the energy-momentum tensor due to a single 2 → 2 scattering process involving two classical fields. To make the calculation tractable we employ the scalar φ 4 theory instead of QCD. We compare our exact diagrammatic results for these quantities to those in kinetic theory and find disagreement between the two. The disagreement is in the dependence on the proper time τ and, for the case of the two-point function, is also in the dependence on the space-time rapidity η: the exact diagrammatic calculation is, in fact, consistent with the free streaming scenario. Kinetic theory predicts a build-up of longitudinal pressure, which, however, is not observed in the exact calculation. We conclude that we find no evidence for the beginning of the transition from the free-streaming classical fields to the kinetic theory description of the produced matter after a single 2 → 2 rescattering.
Effect of static porosity fluctuations on reactive transport in a porous medium

NASA Astrophysics Data System (ADS)

L'Heureux, Ivan

2018-02-01

Reaction-diffusive transport phenomena in porous media are ubiquitous in engineering applications, biological and geochemical systems. The porosity field is usually random in space, but most models consider the porosity field as a well-defined deterministic function of space and time and ignore the porosity fluctuations. They use a reaction-diffusion equation written in terms of an average porosity and average concentration fields. In this contribution, we treat explicitly the effect of spatial porosity fluctuations on the dynamics of a concentration field for the case of a one-dimensional reaction-transport system with nonlinear kinetics. Three basic assumptions are considered. (i) The porosity fluctuations are assumed to have Gaussian properties and an arbitrary variance; (ii) we assume that the noise correlation length is small compared to the relevant macroscopic length scale; (iii) and we assume that the kinetics of the reactive term in the equations for the fluctuations is a self-consistently determined constant. Elimination of the fluctuating part of the concentration field from the dynamics leads to a renormalized equation involving the average concentration field. It is shown that the noise leads to a renormalized (generally smaller) diffusion coefficient and renormalized kinetics. Within the framework of the approximations used, numerical simulations are in agreement with our theory. We show that the porosity fluctuations may have a significant effect on the transport of a reactive species, even in the case of a homogeneous average porosity.
PyFolding: Open-Source Graphing, Simulation, and Analysis of the Biophysical Properties of Proteins.

PubMed

Lowe, Alan R; Perez-Riba, Albert; Itzhaki, Laura S; Main, Ewan R G

2018-02-06

For many years, curve-fitting software has been heavily utilized to fit simple models to various types of biophysical data. Although such software packages are easy to use for simple functions, they are often expensive and present substantial impediments to applying more complex models or for the analysis of large data sets. One field that is reliant on such data analysis is the thermodynamics and kinetics of protein folding. Over the past decade, increasingly sophisticated analytical models have been generated, but without simple tools to enable routine analysis. Consequently, users have needed to generate their own tools or otherwise find willing collaborators. Here we present PyFolding, a free, open-source, and extensible Python framework for graphing, analysis, and simulation of the biophysical properties of proteins. To demonstrate the utility of PyFolding, we have used it to analyze and model experimental protein folding and thermodynamic data. Examples include: 1) multiphase kinetic folding fitted to linked equations, 2) global fitting of multiple data sets, and 3) analysis of repeat protein thermodynamics with Ising model variants. Moreover, we demonstrate how PyFolding is easily extensible to novel functionality beyond applications in protein folding via the addition of new models. Example scripts to perform these and other operations are supplied with the software, and we encourage users to contribute notebooks and models to create a community resource. Finally, we show that PyFolding can be used in conjunction with Jupyter notebooks as an easy way to share methods and analysis for publication and among research teams. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Kinetically reduced local Navier-Stokes equations: an alternative approach to hydrodynamics.

PubMed

Karlin, Iliya V; Tomboulides, Ananias G; Frouzakis, Christos E; Ansumali, Santosh

2006-09-01

An alternative approach, the kinetically reduced local Navier-Stokes (KRLNS) equations for the grand potential and the momentum, is proposed for the simulation of low Mach number flows. The Taylor-Green vortex flow is considered in the KRLNS framework, and compared to the results of the direct numerical simulation of the incompressible Navier-Stokes equations. The excellent agreement between the KRLNS equations and the incompressible nonlocal Navier-Stokes equations for this nontrivial time-dependent flow indicates that the former is a viable alternative for computational fluid dynamics at low Mach numbers.

The amazing cases of motion with friction

NASA Astrophysics Data System (ADS)

Grech, Dariusz; Mazur, Zygmunt

2001-07-01

The paper describes the behaviour of a simple mechanical system, which should help students (or teachers) to understand and clarify the importance of relative motion of two surfaces when kinetic friction is present. We show that despite the simplicity of this system, the peculiar interplay between friction forces, tension forces and gravity leads to physical solutions exceeding in many cases most intuitive expectations. These are discussed in detail. The problem is intended to be solved in a theoretical framework as an example, which helps to understand better the physical background of kinetic friction phenomena.
Dynamic Morphologies and Stability of Droplet Interface Bilayers

NASA Astrophysics Data System (ADS)

Guiselin, Benjamin; Law, Jack O.; Chakrabarti, Buddhapriya; Kusumaatmaja, Halim

2018-06-01

We develop a theoretical framework for understanding dynamic morphologies and stability of droplet interface bilayers (DIBs), accounting for lipid kinetics in the monolayers and bilayer, and droplet evaporation due to imbalance between osmotic and Laplace pressures. Our theory quantitatively describes distinct pathways observed in experiments when DIBs become unstable. We find that when the timescale for lipid desorption is slow compared to droplet evaporation, the lipid bilayer will grow and the droplets approach a hemispherical shape. In contrast, when lipid desorption is fast, the bilayer area will shrink and the droplets eventually detach. Our model also suggests there is a critical size below which DIBs can become unstable, which may explain experimental difficulties in miniaturizing the DIB platform.
Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects.

PubMed

Colle, Ines J P; Lemmens, Lien; Knockaert, Griet; Van Loey, Ann; Hendrickx, Marc

2016-08-17

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.
Detonation initiation in a model of explosive: Comparative atomistic and hydrodynamics simulations

NASA Astrophysics Data System (ADS)

Murzov, S. A.; Sergeev, O. V.; Dyachkov, S. A.; Egorova, M. S.; Parshikov, A. N.; Zhakhovsky, V. V.

2016-11-01

Here we extend consistent simulations to reactive materials by the example of AB model explosive. The kinetic model of chemical reactions observed in a molecular dynamics (MD) simulation of self-sustained detonation wave can be used in hydrodynamic simulation of detonation initiation. Kinetic coefficients are obtained by minimization of difference between profiles of species calculated from the kinetic model and observed in MD simulations of isochoric thermal decomposition with a help of downhill simplex method combined with random walk in multidimensional space of fitting kinetic model parameters.
Kinetic Description of the Impedance Probe

NASA Astrophysics Data System (ADS)

Oberrath, Jens; Lapke, Martin; Mussenbrock, Thomas; Brinkmann, Ralf

2011-10-01

Active plasma resonance spectroscopy is a well known diagnostic method. Many concepts of this method are theoretically investigated and realized as a diagnostic tool, one of which is the impedance probe (IP). The application of such a probe in plasmas with pressures of a few Pa raises the question whether kinetic effects have to be taken into account or not. To address this question a kinetic model is necessary. A general kinetic model for an electrostatic concept of active plasma spectroscopy was presented by R.P. Brinkmann and can be used to describe the multipole resonance probe (MRP). In principle the IP is interpretable as a special case of the MRP in lower order. Thus, we are able to describe the IP by the kinetic model of the MRP. Based on this model we derive a solution to investigate the influence of kinetic effects to the resonance behavior of the IP. Active plasma resonance spectroscopy is a well known diagnostic method. Many concepts of this method are theoretically investigated and realized as a diagnostic tool, one of which is the impedance probe (IP). The application of such a probe in plasmas with pressures of a few Pa raises the question whether kinetic effects have to be taken into account or not. To address this question a kinetic model is necessary. A general kinetic model for an electrostatic concept of active plasma spectroscopy was presented by R.P. Brinkmann and can be used to describe the multipole resonance probe (MRP). In principle the IP is interpretable as a special case of the MRP in lower order. Thus, we are able to describe the IP by the kinetic model of the MRP. Based on this model we derive a solution to investigate the influence of kinetic effects to the resonance behavior of the IP. The authors acknowledge the support by the Deutsche Forschungsgemeinschaft (DFG) via the Ruhr University Research School and the Federal Ministry of Education and Research in frame of the PluTO project.
Structure Elucidation of Mixed-Linker Zeolitic Imidazolate Frameworks by Solid-State (1)H CRAMPS NMR Spectroscopy and Computational Modeling.

PubMed

Jayachandrababu, Krishna C; Verploegh, Ross J; Leisen, Johannes; Nieuwendaal, Ryan C; Sholl, David S; Nair, Sankar

2016-06-15

Mixed-linker zeolitic imidazolate frameworks (ZIFs) are nanoporous materials that exhibit continuous and controllable tunability of properties like effective pore size, hydrophobicity, and organophilicity. The structure of mixed-linker ZIFs has been studied on macroscopic scales using gravimetric and spectroscopic techniques. However, it has so far not been possible to obtain information on unit-cell-level linker distribution, an understanding of which is key to predicting and controlling their adsorption and diffusion properties. We demonstrate the use of (1)H combined rotation and multiple pulse spectroscopy (CRAMPS) NMR spin exchange measurements in combination with computational modeling to elucidate potential structures of mixed-linker ZIFs, particularly the ZIF 8-90 series. All of the compositions studied have structures that have linkers mixed at a unit-cell-level as opposed to separated or highly clustered phases within the same crystal. Direct experimental observations of linker mixing were accomplished by measuring the proton spin exchange behavior between functional groups on the linkers. The data were then fitted to a kinetic spin exchange model using proton positions from candidate mixed-linker ZIF structures that were generated computationally using the short-range order (SRO) parameter as a measure of the ordering, clustering, or randomization of the linkers. The present method offers the advantages of sensitivity without requiring isotope enrichment, a straightforward NMR pulse sequence, and an analysis framework that allows one to relate spin diffusion behavior to proposed atomic positions. We find that structures close to equimolar composition of the two linkers show a greater tendency for linker clustering than what would be predicted based on random models. Using computational modeling we have also shown how the window-type distribution in experimentally synthesized mixed-linker ZIF-8-90 materials varies as a function of their composition. The structural information thus obtained can be further used for predicting, screening, or understanding the tunable adsorption and diffusion behavior of mixed-linker ZIFs, for which the knowledge of linker distributions in the framework is expected to be important.
A Self Consistent RF Discharge, Plasma Chemistry and Surface Model for Plasma Enhanced Chemical Vapor Deposition

DTIC Science & Technology

1988-06-30

consists of three submodels for the electron kinetics, plasma chemistry , and surface deposition kinetics for a-Si:H deposited from radio frequency...properties. Plasma enhanced, Chemical vapor deposition, amorphous silicon, Modeling, Electron kinetics, Plasma chemistry , Deposition kinetics, Rf discharge, Silane, Film properties, Silicon.
A note on the maintenance of the atmospheric kinetic energy

NASA Technical Reports Server (NTRS)

Chen, T.-C.; Lee, Y.-H.

1982-01-01

The winter simulations of the GLAS climate model and the NCAR community climate model are used to examine the maintenance of the atmospheric kinetic energy. It is found that the kinetic energy is generated in the lower latitudes south of the maximum westerlies, transported northward and then, destroyed in the midlatitudes north of the maximum westerlies. Therefore, the atmospheric kinetic energy is maintained by the counterbalance between the divergence (convergence) of kinetic energy flux and generation (destruction) of kinetic energy in lower (middle) latitudes.
Deriving in vivo biotransformation rate constants and metabolite parent concentration factor/stable metabolite factor from bioaccumulation and bioconcentration experiments: An illustration with worm accumulation data.

PubMed

Kuo, Dave Ta Fu; Chen, Ciara Chun

2016-12-01

Growing concern for the biological fate of organic contaminants and their metabolites and the urge to connect in vitro and in vivo toxicokinetics have prompted researchers to characterize the biotransformation behavior of organic contaminants in biota. The whole body biotransformation rate constant (k M ) is currently determined by the difference approach, which has significant methodological limitations. A new approach for determining k M from the kinetic observations of the parent contaminant and its intermediate metabolites is proposed. In this method, k M can be determined by fitting kinetic data of the parent contaminant and the metabolites to analytical equations that depict the bioaccumulation kinetics. The application of the proposed method is illustrated using worm bioaccumulation-biotransformation data collected from the literature. Furthermore, a metabolite parent concentration factor (MPCF) is also proposed to characterize the persistence of the metabolite in biota. Because both the proposed k M method and MPCF build on the existing theoretical framework for bioaccumulation, they can be readily incorporated into standard experimental bioaccumulation protocols or risk assessment procedures or frameworks. Possible limitations, implications, and future directions are elaborated. Environ Toxicol Chem 2016;35:2903-2909. © 2016 SETAC. © 2016 SETAC.
Kinetic analysis of overlapping multistep thermal decomposition comprising exothermic and endothermic processes: thermolysis of ammonium dinitramide.

PubMed

Muravyev, Nikita V; Koga, Nobuyoshi; Meerov, Dmitry B; Pivkina, Alla N

2017-01-25

This study focused on kinetic modeling of a specific type of multistep heterogeneous reaction comprising exothermic and endothermic reaction steps, as exemplified by the practical kinetic analysis of the experimental kinetic curves for the thermal decomposition of molten ammonium dinitramide (ADN). It is known that the thermal decomposition of ADN occurs as a consecutive two step mass-loss process comprising the decomposition of ADN and subsequent evaporation/decomposition of in situ generated ammonium nitrate. These reaction steps provide exothermic and endothermic contributions, respectively, to the overall thermal effect. The overall reaction process was deconvoluted into two reaction steps using simultaneously recorded thermogravimetry and differential scanning calorimetry (TG-DSC) curves by considering the different physical meanings of the kinetic data derived from TG and DSC by P value analysis. The kinetic data thus separated into exothermic and endothermic reaction steps were kinetically characterized using kinetic computation methods including isoconversional method, combined kinetic analysis, and master plot method. The overall kinetic behavior was reproduced as the sum of the kinetic equations for each reaction step considering the contributions to the rate data derived from TG and DSC. During reproduction of the kinetic behavior, the kinetic parameters and contributions of each reaction step were optimized using kinetic deconvolution analysis. As a result, the thermal decomposition of ADN was successfully modeled as partially overlapping exothermic and endothermic reaction steps. The logic of the kinetic modeling was critically examined, and the practical usefulness of phenomenological modeling for the thermal decomposition of ADN was illustrated to demonstrate the validity of the methodology and its applicability to similar complex reaction processes.
The influence of the "cage effect" on the mechanism of reversible bimolecular multistage chemical reactions in solutions.

PubMed

Doktorov, Alexander B

2015-08-21

Manifestations of the "cage effect" at the encounters of reactants are theoretically treated by the example of multistage reactions in liquid solutions including bimolecular exchange reactions as elementary stages. It is shown that consistent consideration of quasi-stationary kinetics of multistage reactions (possible only in the framework of the encounter theory) for reactions proceeding near reactants contact can be made on the basis of the concepts of a "cage complex." Though mathematically such a consideration is more complicated, it is more clear from the standpoint of chemical notions. It is established that the presence of the "cage effect" leads to some important effects not inherent in reactions in gases or those in solutions proceeding in the kinetic regime, such as the appearance of new transition channels of reactant transformation that cannot be caused by elementary event of chemical conversion for the given mechanism of reaction. This results in that, for example, rate constant values of multistage reaction defined by standard kinetic equations of formal chemical kinetics from experimentally measured kinetics can differ essentially from real values of these constants.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Doktorov, Alexander B., E-mail: doktorov@kinetics.nsc.ru

Manifestations of the “cage effect” at the encounters of reactants are theoretically treated by the example of multistage reactions in liquid solutions including bimolecular exchange reactions as elementary stages. It is shown that consistent consideration of quasi-stationary kinetics of multistage reactions (possible only in the framework of the encounter theory) for reactions proceeding near reactants contact can be made on the basis of the concepts of a “cage complex.” Though mathematically such a consideration is more complicated, it is more clear from the standpoint of chemical notions. It is established that the presence of the “cage effect” leads to somemore » important effects not inherent in reactions in gases or those in solutions proceeding in the kinetic regime, such as the appearance of new transition channels of reactant transformation that cannot be caused by elementary event of chemical conversion for the given mechanism of reaction. This results in that, for example, rate constant values of multistage reaction defined by standard kinetic equations of formal chemical kinetics from experimentally measured kinetics can differ essentially from real values of these constants.« less
Removal of Pertechnetate-Related Oxyanions from Solution Using Functionalized Hierarchical Porous Frameworks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banerjee, Debasis; Elsaidi, Sameh K.; Aguila, Briana

2016-10-20

Efficient and cost-effective removal of radioactive pertechnetate anions from nuclear waste is a key challenge to mitigate long-term nuclear waste storage issues. Traditional materials such as resins and layered double hydroxides (LDHs) were evaluated for their pertechnetate or perrhenate (the non-radioactive surrogate) removal capacity, but there is room for improvement in terms of capacity, selectivity and kinetics. A series of functionalized hierarchical porous frameworks were evaluated for their perrhenate removal capacity in the presence of other competing anions.
An efficient synthesis strategy for metal-organic frameworks: Dry-gel synthesis of MOF-74 framework with high yield and improved performance

DOE PAGES

Das, Atanu Kumar; Vemuri, Rama Sesha; Kutnyakov, Igor; ...

2016-06-16

Here, vapor-assisted dry-gel synthesis of MOF-74 structure, specifically NiMOF-74 from its synthetic precursors, was conducted with high yield and improved performance showing promise for gas (CO 2) and water adsorption applications. Unlike conventional synthesis, which takes 72 h, this kinetic study showed that NiMOF-74 forms within 12 h under dry-gel conditions with similar performance characteristics and exhibits the best performance characteristics after 48 h of heating.
On the derivation of a simple dynamic model of anaerobic digestion including the evolution of hydrogen.

PubMed

Giovannini, Giannina; Sbarciog, Mihaela; Steyer, Jean-Philippe; Chamy, Rolando; Vande Wouwer, Alain

2018-05-01

Hydrogen has been found to be an important intermediate during anaerobic digestion (AD) and a key variable for process monitoring as it gives valuable information about the stability of the reactor. However, simple dynamic models describing the evolution of hydrogen are not commonplace. In this work, such a dynamic model is derived using a systematic data driven-approach, which consists of a principal component analysis to deduce the dimension of the minimal reaction subspace explaining the data, followed by an identification of the kinetic parameters in the least-squares sense. The procedure requires the availability of informative data sets. When the available data does not fulfill this condition, the model can still be built from simulated data, obtained using a detailed model such as ADM1. This dynamic model could be exploited in monitoring and control applications after a re-identification of the parameters using actual process data. As an example, the model is used in the framework of a control strategy, and is also fitted to experimental data from raw industrial wine processing wastewater. Copyright © 2018 Elsevier Ltd. All rights reserved.
Multiscale modelling approaches for assessing cosmetic ingredients safety.

PubMed

Bois, Frédéric Y; Ochoa, Juan G Diaz; Gajewska, Monika; Kovarich, Simona; Mauch, Klaus; Paini, Alicia; Péry, Alexandre; Benito, Jose Vicente Sala; Teng, Sophie; Worth, Andrew

2017-12-01

The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Microbial Kinetic Model for the Degradation of Poorly Soluble Organic Materials

EPA Science Inventory

A novel mechanistic model is presented that describes the aerobic biodegradation kinetics of soybean biodiesel and petroleum diesel in batch experiments. The model was built on the assumptions that biodegradation takes place in the aqueous phase according to Monod kinetics, and ...
OH- Initiated Heterogeneous Oxidation of Saturated Organic Aerosols in the Presence of SO2: Uptake Kinetics and Product Identification.

NASA Astrophysics Data System (ADS)

Richards-Henderson, N. K.; Ward, M.; Goldstein, A. H.; Wilson, K. R.

2014-12-01

Gas-phase oxidation mechanisms for organic gases are often used as a starting point to understand heterogeneous oxidation. The reaction of a simple alkane hydrocarbon by OH proceeds through hydrogen abstraction and under ambient conditions leads to peroxy radical (RO2) formation. RO2 can further react to form: (1) smaller molecular weight products (i.e. fragmentation) via alkoxy radical formation and dissociation and/or (2) higher molecular weight products with oxygenated functional groups (i.e. functionalization). The ability to perturb these two pathways (functionalization vs. fragmentation) is critical for understanding the detailed reaction mechanism that control atmospheric aging chemistry of particles. At high temperatures the presence of sulfur dioxide (SO2) during organic-OH gas-phase oxidation enhances the fragmentation pathway leading to increased alkoxy formation. It is unknown if a comparative affect occurs at room temperature during a heterogeneous reaction. We used the heterogeneous reaction of OH radicals with sub-micron squalane particles in the presence and absence of SO2 as a model system to explore changes in individual mechanistic pathways. Detailed kinetic measurements were made in a flow tube reactor using a vacuum ultraviolet (VUV) photoionization aerosol mass spectrometer and oxidation products are identified from samples collected on quartz filters using thermal desorption two-dimensional chromatographic separation and ionization by either VUV (10.5 eV) or electron impact (70 eV), with detection by high resolution time of flight mass spectrometry (GCxGC-VUV/EI-HRTOFMS). In the presence of SO2 the yields of alcohols were enhanced compared to without SO2, suggesting that the alkoxy formation pathway was dominant. The results from this work will provide an experimentally-confirmed kinetic framework that could be used to model atmospheric aging mechanisms.
Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions.

PubMed

Götz, Markus; Wortmann, Philipp; Schmid, Sonja; Hugel, Thorsten

2018-01-30

Single-molecule Förster resonance energy transfer (smFRET) has become a widely used biophysical technique to study the dynamics of biomolecules. For many molecular machines in a cell proteins have to act together with interaction partners in a functional cycle to fulfill their task. The extension of two-color to multi-color smFRET makes it possible to simultaneously probe more than one interaction or conformational change. This not only adds a new dimension to smFRET experiments but it also offers the unique possibility to directly study the sequence of events and to detect correlated interactions when using an immobilized sample and a total internal reflection fluorescence microscope (TIRFM). Therefore, multi-color smFRET is a versatile tool for studying biomolecular complexes in a quantitative manner and in a previously unachievable detail. Here, we demonstrate how to overcome the special challenges of multi-color smFRET experiments on proteins. We present detailed protocols for obtaining the data and for extracting kinetic information. This includes trace selection criteria, state separation, and the recovery of state trajectories from the noisy data using a 3D ensemble Hidden Markov Model (HMM). Compared to other methods, the kinetic information is not recovered from dwell time histograms but directly from the HMM. The maximum likelihood framework allows us to critically evaluate the kinetic model and to provide meaningful uncertainties for the rates. By applying our method to the heat shock protein 90 (Hsp90), we are able to disentangle the nucleotide binding and the global conformational changes of the protein. This allows us to directly observe the cooperativity between the two nucleotide binding pockets of the Hsp90 dimer.
Kinetics of Cd(ii) adsorption and desorption on ferrihydrite: experiments and modeling.

PubMed

Liang, Yuzhen; Tian, Lei; Lu, Yang; Peng, Lanfang; Wang, Pei; Lin, Jingyi; Cheng, Tao; Dang, Zhi; Shi, Zhenqing

2018-05-15

The kinetics of Cd(ii) adsorption/desorption on ferrihydrite is an important process affecting the fate, transport, and bioavailability of Cd(ii) in the environment, which was rarely systematically studied and understood at quantitative levels. In this work, a combination of stirred-flow kinetic experiments, batch adsorption equilibrium experiments, high-resolution transmission electron microscopy (HR-TEM), and mechanistic kinetic modeling were used to study the kinetic behaviors of Cd(ii) adsorption/desorption on ferrihydrite. HR-TEM images showed the open, loose, and sponge-like structure of ferrihydrite. The batch adsorption equilibrium experiments revealed that higher pH and initial metal concentration increased Cd(ii) adsorption on ferrihydrite. The stirred-flow kinetic results demonstrated the increased adsorption rate and capacity as a result of the increased pH, influent concentration, and ferrihydrite concentration. The mechanistic kinetic model successfully described the kinetic behaviors of Cd(ii) during the adsorption and desorption stages under various chemistry conditions. The model calculations showed that the adsorption rate coefficients varied as a function of solution chemistry, and the relative contributions of the weak and strong ferrihydrite sites for Cd(ii) binding varied with time at different pH and initial metal concentrations. Our model is able to quantitatively assess the contributions of each individual ferrihydrite binding site to the overall Cd(ii) adsorption/desorption kinetics. This study provided insights into the dynamic behavior of Cd(ii) and a predictive modeling tool for Cd(ii) adsorption/desorption kinetics when ferrihydrite is present, which may be helpful for the risk assessment and management of Cd contaminated sites.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism

PubMed Central

2017-01-01

Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J) and the modal matrix (M-1) arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions. PMID:29267329
Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and non-linear methods.

PubMed

Ho, Yuh-Shan

2006-01-01

A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.
A Non-Incompressible Non-Boussinesq (NINB) framework for studying atmospheric turbulence

NASA Astrophysics Data System (ADS)

Yan, C.; Archer, C. L.; Xie, S.; Ghaisas, N.

2015-12-01

The incompressible assumption is widely used for studying the turbulent atmospheric boundary layer (ABL) and is generally accepted when the Mach number < ~0.3 (velocity < ~100 m/s). Since the tips of modern wind turbine blades can reach and exceed this threshold, neglecting air compressibility will introduce errors. In addition, if air incompressibility does not hold, then the Boussinesq approximation, by which air density is treated as a constant except in the gravity term of the Navier-Stokes equation, is also invalidated. Here, we propose a new theoretical framework, called NINB for Non-Incompressible Non-Boussinesq, in which air is not considered incompressible and air density is treated as a non-turbulent 4D variable. First, the NINB mass, momentum, and energy conservation equations are developed using Reynolds averaging. Second, numerical simulations of the NINB equations, coupled with a k-epsilon turbulence model, are performed with the finite-volume method. Wind turbines are modeled with the actuator-line model using SOWFA (Software for Offshore/onshore Wind Farm Applications). Third, NINB results are compared with the traditional incompressible buoyant simulations performed by SOWFA with the same set up. The results show differences between NINB and traditional simulations in the neutral atmosphere with a wind turbine. The largest differences in wind speed (up to 1 m/s), turbulent kinetic energy (~10%), dissipation rate (~5%), and shear stress (~10%) occur near the turbine tip region. The power generation differences are 5-15% (depending on setup). These preliminary results suggest that compressibility effects are non-negligible around wind turbines and should be taken into account when forecasting wind power. Since only a few extra terms are introduced, the NINB framework may be an alternative to the traditional incompressible Boussinesq framework for studying the turbulent ABL in general (i.e., without turbines) in the absence of shock waves.
An NMR Kinetics Experiment.

ERIC Educational Resources Information Center

Kaufman, Don; And Others

1982-01-01

Outlines advantages of and provides background information, procedures, and typical student data for an experiment determining rate of hydration of p-methyoxyphenylacetylene (III), followed by nuclear magnetic resonance spectroscopy. Reaction rate can be adjusted to meet time framework of a particular laboratory by altering concentration of…
Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rai, Raj K.; Berg, Larry K.; Pekour, Mikhail

The assumption of sub-grid scale (SGS) horizontal homogeneity within a model grid cell, which forms the basis of SGS turbulence closures used by mesoscale models, becomes increasingly tenuous as grid spacing is reduced to a few kilometers or less, such as in many emerging high-resolution applications. Herein, we use the turbulence kinetic energy (TKE) budget equation to study the spatio-temporal variability in two types of terrain—complex (Columbia Basin Wind Energy Study [CBWES] site, north-eastern Oregon) and flat (ScaledWind Farm Technologies [SWiFT] site, west Texas) using the Weather Research and Forecasting (WRF) model. In each case six-nested domains (three domains eachmore » for mesoscale and large-eddy simulation [LES]) are used to downscale the horizontal grid spacing from 10 km to 10 m using the WRF model framework. The model output was used to calculate the values of the TKE budget terms in vertical and horizontal planes as well as the averages of grid cells contained in the four quadrants (a quarter area) of the LES domain. The budget terms calculated along the planes and the mean profile of budget terms show larger spatial variability at CBWES site than at the SWiFT site. The contribution of the horizontal derivative of the shear production term to the total production shear was found to be 45% and 15% of the total shear, at the CBWES and SWiFT sites, respectively, indicating that the horizontal derivatives applied in the budget equation should not be ignored in mesoscale model parameterizations, especially for cases with complex terrain with <10 km scale.« less
Bayesian Quantification of Contrast-Enhanced Ultrasound Images With Adaptive Inclusion of an Irreversible Component.

PubMed

Rizzo, Gaia; Tonietto, Matteo; Castellaro, Marco; Raffeiner, Bernd; Coran, Alessandro; Fiocco, Ugo; Stramare, Roberto; Grisan, Enrico

2017-04-01

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity and it can be particularly useful in early detection and grading of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. However, in some cases the heterogeneity of the kinetics can be such that even the Gamma model does not properly describe the curve, with a high number of outliers. In this work we apply to CEUS data the single compartment recirculation model (SCR) which takes explicitly into account the trapping of the microbubbles contrast agent by adding to the single Gamma-variate model its integral. The SCR model, originally proposed for dynamic-susceptibility magnetic resonance imaging, is solved here at pixel level within a Bayesian framework using Variational Bayes (VB). We also include the automatic relevant determination (ARD) algorithm to automatically infer the model complexity (SCR vs. Gamma model) from the data. We demonstrate that the inclusion of trapping best describes the CEUS patterns in 50% of the pixels, with the other 50% best fitted by a single Gamma. Such results highlight the necessity of the use ARD, to automatically exclude the irreversible component where not supported by the data. VB with ARD returns precise estimates in the majority of the kinetics (88% of total percentage of pixels) in a limited computational time (on average, 3.6 min per subject). Moreover, the impact of the additional trapping component has been evaluated for the differentiation of rheumatoid and non-rheumatoid patients, by means of a support vector machine classifier with backward feature selection. The results show that the trapping parameter is always present in the selected feature set, and improves the classification.
Biological reduction of chlorinated solvents: Batch-scale geochemical modeling

NASA Astrophysics Data System (ADS)

Kouznetsova, Irina; Mao, Xiaomin; Robinson, Clare; Barry, D. A.; Gerhard, Jason I.; McCarty, Perry L.

2010-09-01

Simulation of biodegradation of chlorinated solvents in dense non-aqueous phase liquid (DNAPL) source zones requires a model that accounts for the complexity of processes involved and that is consistent with available laboratory studies. This paper describes such a comprehensive modeling framework that includes microbially mediated degradation processes, microbial population growth and decay, geochemical reactions, as well as interphase mass transfer processes such as DNAPL dissolution, gas formation and mineral precipitation/dissolution. All these processes can be in equilibrium or kinetically controlled. A batch modeling example was presented where the degradation of trichloroethene (TCE) and its byproducts and concomitant reactions (e.g., electron donor fermentation, sulfate reduction, pH buffering by calcite dissolution) were simulated. Local and global sensitivity analysis techniques were applied to delineate the dominant model parameters and processes. Sensitivity analysis indicated that accurate values for parameters related to dichloroethene (DCE) and vinyl chloride (VC) degradation (i.e., DCE and VC maximum utilization rates, yield due to DCE utilization, decay rate for DCE/VC dechlorinators) are important for prediction of the overall dechlorination time. These parameters influence the maximum growth rate of the DCE and VC dechlorinating microorganisms and, thus, the time required for a small initial population to reach a sufficient concentration to significantly affect the overall rate of dechlorination. Self-inhibition of chlorinated ethenes at high concentrations and natural buffering provided by the sediment were also shown to significantly influence the dechlorination time. Furthermore, the analysis indicated that the rates of the competing, nonchlorinated electron-accepting processes relative to the dechlorination kinetics also affect the overall dechlorination time. Results demonstrated that the model developed is a flexible research tool that is able to provide valuable insight into the fundamental processes and their complex interactions during bioremediation of chlorinated ethenes in DNAPL source zones.
Kinetics, bioavailability, and metabolism of RRR-alpha-tocopherol in humans supports lower requirement for vitamin E

USDA-ARS?s Scientific Manuscript database

Kinetic models enable nutrient needs and kinetic behaviors to be quantified and provide mechanistic insights into metabolism. Therefore, we modeled and quantified the kinetics, bioavailability and metabolism of RRR-alpha-tocopherol in 12 healthy adults. Six men and six women, aged 27 ± 6 y, each i...
An advanced kinetic theory for morphing continuum with inner structures

NASA Astrophysics Data System (ADS)

Chen, James

2017-12-01

Advanced kinetic theory with the Boltzmann-Curtiss equation provides a promising tool for polyatomic gas flows, especially for fluid flows containing inner structures, such as turbulence, polyatomic gas flows and others. Although a Hamiltonian-based distribution function was proposed for diatomic gas flow, a general distribution function for the generalized Boltzmann-Curtiss equations and polyatomic gas flow is still out of reach. With assistance from Boltzmann's entropy principle, a generalized Boltzmann-Curtiss distribution for polyatomic gas flow is introduced. The corresponding governing equations at equilibrium state are derived and compared with Eringen's morphing (micropolar) continuum theory derived under the framework of rational continuum thermomechanics. Although rational continuum thermomechanics has the advantages of mathematical rigor and simplicity, the presented statistical kinetic theory approach provides a clear physical picture for what the governing equations represent.
Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, James C.

2016-10-01

Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.
An improved kinetics approach to describe the physical stability of amorphous solid dispersions.

PubMed

Yang, Jiao; Grey, Kristin; Doney, John

2010-01-15

The recrystallization of amorphous solid dispersions may lead to a loss in the dissolution rate, and consequently reduce bioavailability. The purpose of this work is to understand factors governing the recrystallization of amorphous drug-polymer solid dispersions, and develop a kinetics model capable of accurately predicting their physical stability. Recrystallization kinetics was measured using differential scanning calorimetry for initially amorphous efavirenz-polyvinylpyrrolidone solid dispersions stored at controlled temperature and relative humidity. The experimental measurements were fitted by a new kinetic model to estimate the recrystallization rate constant and microscopic geometry of crystal growth. The new kinetics model was used to illustrate the governing factors of amorphous solid dispersions stability. Temperature was found to affect efavirenz recrystallization in an Arrhenius manner, while recrystallization rate constant was shown to increase linearly with relative humidity. Polymer content tremendously inhibited the recrystallization process by increasing the crystallization activation energy and decreasing the equilibrium crystallinity. The new kinetic model was validated by the good agreement between model fits and experiment measurements. A small increase in polyvinylpyrrolidone resulted in substantial stability enhancements of efavirenz amorphous solid dispersion. The new established kinetics model provided more accurate predictions than the Avrami equation.
Assessment of kinetic models on Fe adsorption in groundwater using high-quality limestone

NASA Astrophysics Data System (ADS)

Akbar, N. A.; Kamil, N. A. F. Mohd; Zin, N. S. Md; Adlan, M. N.; Aziz, H. A.

2018-04-01

During the groundwater pumping process, dissolved Fe2+ is oxidized into Fe3+ and produce rust-coloured iron mineral. Adsorption kinetic models are used to evaluate the performance of limestone adsorbent and describe the mechanism of adsorption and the diffusion processes of Fe adsorption in groundwater. This work presents the best kinetic model of Fe adsorption, which was chosen based on a higher value of coefficient correlation, R2. A batch adsorption experiment was conducted for various contact times ranging from 0 to 135 minutes. From the results of the batch study, three kinetic models were analyzed for Fe removal onto limestone sorbent, including the pseudo-first order (PFO), pseudo-second order (PSO) and intra-particle diffusion (IPD) models. Results show that the adsorption kinetic models follow the sequence: PSO > PFO > IPD, where the values of R2 are 0.997 > 0.919 > 0.918. A high value of R2 (0.997) reveals better fitted experimental data. Furthermore, the value of qe cal in the PSO kinetic model is very near to qe exp rather than that in other models. This finding therefore suggests that the PSO kinetic model has the good fitted with the experimental data which involved chemisorption process of divalent Fe removal in groundwater solution. Thus, limestone adsorbent media found to be an alternative and effective treatment of Fe removal from groundwater.
Anti-SEMA3A Antibody: A Novel Therapeutic Agent to Suppress GBM Tumor Growth.

PubMed

Lee, Jaehyun; Shin, Yong Jae; Lee, Kyoungmin; Cho, Hee Jin; Sa, Jason K; Lee, Sang-Yun; Kim, Seok-Hyung; Lee, Jeongwu; Yoon, Yeup; Nam, Do-Hyun

2017-11-10

Glioblastoma (GBM) is classified as one of the most aggressive and lethal brain tumor. Great strides have been made in understanding the genomic and molecular underpinnings of GBM, which translated into development of new therapeutic approaches to combat such deadly disease. However, there are only few therapeutic agents that can effectively inhibit GBM invasion in a clinical framework. In an effort to address such challenges, we have generated anti-SEMA3A monoclonal antibody as a potential therapeutic antibody against GBM progression. We employed public glioma datasets, Repository of Molecular Brain Neoplasia Data and The Cancer Genome Atlas, to analyze SEMA3A mRNA expression in human GBM specimens. We also evaluated for protein expression level of SEMA3A via tissue microarray (TMA) analysis. Cell migration and proliferation kinetics were assessed in various GBM patient-derived cells (PDCs) and U87-MG cell-line for SEMA3A antibody efficacy. GBM patient-derived xenograft (PDX) models were generated to evaluate tumor inhibitory effect of anti-SEMA3A antibody in vivo. By combining bioinformatics and TMA analysis, we discovered that SEMA3A is highly expressed in human GBM specimens compared to non-neoplastic tissues. We developed three different anti-SEMA3A antibodies, in fully human IgG form, through screening phage-displayed synthetic antibody library using a classical panning method. Neutralization of SEMA3A significantly reduced migration and proliferation capabilities of PDCs and U87-MG cell-line in vitro. In PDX models, treatment with anti-SEMA3A antibody exhibited notable tumor inhibitory effect through down-regulation of cellular proliferative kinetics and tumor-associated macrophages recruitment. In present study, we demonstrated tumor inhibitory effect of SEMA3A antibody in GBM progression and present its potential relevance as a therapeutic agent in a clinical framework.
Thermal isomerization of azobenzenes: on the performance of Eyring transition state theory.

PubMed

Rietze, Clemens; Titov, Evgenii; Lindner, Steven; Saalfrank, Peter

2017-08-09

The thermal [Formula: see text] (back-)isomerization of azobenzenes is a prototypical reaction occurring in molecular switches. It has been studied for decades, yet its kinetics is not fully understood. In this paper, quantum chemical calculations are performed to model the kinetics of an experimental benchmark system, where a modified azobenzene (AzoBiPyB) is embedded in a metal-organic framework (MOF). The molecule can be switched thermally from cis to trans, under solvent-free conditions. We critically test the validity of Eyring transition state theory for this reaction. As previously found for other azobenzenes (albeit in solution), good agreement between theory and experiment emerges for activation energies and activation free energies, already at a comparatively simple level of theory, B3LYP/6-31G * including dispersion corrections. However, theoretical Arrhenius prefactors and activation entropies are in qualitiative disagreement with experiment. Several factors are discussed that may have an influence on activation entropies, among them dynamical and geometric constraints (imposed by the MOF). For a simpler model-[Formula: see text] isomerization in azobenzene-a systematic test of quantum chemical methods from both density functional theory and wavefunction theory is carried out in the context of Eyring theory. Also, the effect of anharmonicities on activation entropies is discussed for this model system. Our work highlights capabilities and shortcomings of Eyring transition state theory and quantum chemical methods, when applied for the [Formula: see text] (back-)isomerization of azobenzenes under solvent-free conditions.
Systems-level computational modeling demonstrates fuel selection switching in high capacity running and low capacity running rats

PubMed Central

Qi, Nathan R.

2018-01-01

High capacity and low capacity running rats, HCR and LCR respectively, have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise. HCR rats can maintain fatty acid (FA) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization. We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density. To test this hypothesis and to investigate mechanisms of fuel selection, we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats. Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis, the TCA cycle, and mitochondrial FA transport and oxidation. The model can effectively match the observed relative rates of oxidation of glucose versus FA, as a function of ATP demand. In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats, it was determined that the whole-body metabolic phenotype of LCR, compared to the HCR, could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity. Finally, we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes. PMID:29474500
Toxicokinetics/toxicodynamics links bioavailability for assessing arsenic uptake and toxicity in three aquaculture species.

PubMed

Chen, Wei-Yu; Liao, Chung-Min

2012-11-01

The purpose of this study was to link toxicokinetics/toxicodynamics (TK/TD) and bioavailability-based metal uptake kinetics to assess arsenic (As) uptake and bioaccumulation in three common farmed species of tilapia (Oreochromis mossambicus), milkfish (Chanos chanos), and freshwater clam (Corbicula fluminea). We developed a mechanistic framework by linking damage assessment model (DAM) and bioavailability-based Michaelis-Menten model for describing TK/TD and As uptake mechanisms. The proposed model was verified with published acute toxicity data. The estimated TK/TD parameters were used to simulate the relationship between bioavailable As uptake and susceptibility probability. The As toxicity was also evaluated based on a constructed elimination-recovery scheme. Absorption rate constants were estimated to be 0.025, 0.016, and 0.175 mL g(-1) h(-1) and As uptake rate constant estimates were 22.875, 63.125, and 788.318 ng g(-1) h(-1) for tilapia, milkfish, and freshwater clam, respectively. Here we showed that a potential trade-off between capacities of As elimination and damage recovery was found among three farmed species. Moreover, the susceptibility probability can also be estimated by the elimination-recovery relations. This study suggested that bioavailability-based uptake kinetics and TK/TD-based DAM could be integrated for assessing metal uptake and toxicity in aquatic organisms. This study is useful to quantitatively assess the complex environmental behavior of metal uptake and implicate to risk assessment of metals in aquaculture systems.
Stochastic tools hidden behind the empirical dielectric relaxation laws

NASA Astrophysics Data System (ADS)

Stanislavsky, Aleksander; Weron, Karina

2017-03-01

The paper is devoted to recent advances in stochastic modeling of anomalous kinetic processes observed in dielectric materials which are prominent examples of disordered (complex) systems. Theoretical studies of dynamical properties of ‘structures with variations’ (Goldenfield and Kadanoff 1999 Science 284 87-9) require application of such mathematical tools—by means of which their random nature can be analyzed and, independently of the details distinguishing various systems (dipolar materials, glasses, semiconductors, liquid crystals, polymers, etc), the empirical universal kinetic patterns can be derived. We begin with a brief survey of the historical background of the dielectric relaxation study. After a short outline of the theoretical ideas providing the random tools applicable to modeling of relaxation phenomena, we present probabilistic implications for the study of the relaxation-rate distribution models. In the framework of the probability distribution of relaxation rates we consider description of complex systems, in which relaxing entities form random clusters interacting with each other and single entities. Then we focus on stochastic mechanisms of the relaxation phenomenon. We discuss the diffusion approach and its usefulness for understanding of anomalous dynamics of relaxing systems. We also discuss extensions of the diffusive approach to systems under tempered random processes. Useful relationships among different stochastic approaches to the anomalous dynamics of complex systems allow us to get a fresh look at this subject. The paper closes with a final discussion on achievements of stochastic tools describing the anomalous time evolution of complex systems.
Brownian cluster dynamics with short range patchy interactions: Its application to polymers and step-growth polymerization

NASA Astrophysics Data System (ADS)

Prabhu, A.; Babu, S. B.; Dolado, J. S.; Gimel, J.-C.

2014-07-01

We present a novel simulation technique derived from Brownian cluster dynamics used so far to study the isotropic colloidal aggregation. It now implements the classical Kern-Frenkel potential to describe patchy interactions between particles. This technique gives access to static properties, dynamics and kinetics of the system, even far from the equilibrium. Particle thermal motions are modeled using billions of independent small random translations and rotations, constrained by the excluded volume and the connectivity. This algorithm, applied to a single polymer chain leads to correct static and dynamic properties, in the framework where hydrodynamic interactions are ignored. By varying patch angles, various local chain flexibilities can be obtained. We have used this new algorithm to model step-growth polymerization under various solvent qualities. The polymerization reaction is modeled by an irreversible aggregation between patches while an isotropic finite square-well potential is superimposed to mimic the solvent quality. In bad solvent conditions, a competition between a phase separation (due to the isotropic interaction) and polymerization (due to patches) occurs. Surprisingly, an arrested network with a very peculiar structure appears. It is made of strands and nodes. Strands gather few stretched chains that dip into entangled globular nodes. These nodes act as reticulation points between the strands. The system is kinetically driven and we observe a trapped arrested structure. That demonstrates one of the strengths of this new simulation technique. It can give valuable insights about mechanisms that could be involved in the formation of stranded gels.
Benchmark studies of the gyro-Landau-fluid code and gyro-kinetic codes on kinetic ballooning modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, T. F.; Lawrence Livermore National Laboratory, Livermore, California 94550; Xu, X. Q.

2016-03-15

A Gyro-Landau-Fluid (GLF) 3 + 1 model has been recently implemented in BOUT++ framework, which contains full Finite-Larmor-Radius effects, Landau damping, and toroidal resonance [Ma et al., Phys. Plasmas 22, 055903 (2015)]. A linear global beta scan has been conducted using the JET-like circular equilibria (cbm18 series), showing that the unstable modes are kinetic ballooning modes (KBMs). In this work, we use the GYRO code, which is a gyrokinetic continuum code widely used for simulation of the plasma microturbulence, to benchmark with GLF 3 + 1 code on KBMs. To verify our code on the KBM case, we first perform the beta scan basedmore » on “Cyclone base case parameter set.” We find that the growth rate is almost the same for two codes, and the KBM mode is further destabilized as beta increases. For JET-like global circular equilibria, as the modes localize in peak pressure gradient region, a linear local beta scan using the same set of equilibria has been performed at this position for comparison. With the drift kinetic electron module in the GYRO code by including small electron-electron collision to damp electron modes, GYRO generated mode structures and parity suggest that they are kinetic ballooning modes, and the growth rate is comparable to the GLF results. However, a radial scan of the pedestal for a particular set of cbm18 equilibria, using GYRO code, shows different trends for the low-n and high-n modes. The low-n modes show that the linear growth rate peaks at peak pressure gradient position as GLF results. However, for high-n modes, the growth rate of the most unstable mode shifts outward to the bottom of pedestal and the real frequency of what was originally the KBMs in ion diamagnetic drift direction steadily approaches and crosses over to the electron diamagnetic drift direction.« less
Parameter Balancing in Kinetic Models of Cell Metabolism†

PubMed Central

2010-01-01

Kinetic modeling of metabolic pathways has become a major field of systems biology. It combines structural information about metabolic pathways with quantitative enzymatic rate laws. Some of the kinetic constants needed for a model could be collected from ever-growing literature and public web resources, but they are often incomplete, incompatible, or simply not available. We address this lack of information by parameter balancing, a method to complete given sets of kinetic constants. Based on Bayesian parameter estimation, it exploits the thermodynamic dependencies among different biochemical quantities to guess realistic model parameters from available kinetic data. Our algorithm accounts for varying measurement conditions in the input data (pH value and temperature). It can process kinetic constants and state-dependent quantities such as metabolite concentrations or chemical potentials, and uses prior distributions and data augmentation to keep the estimated quantities within plausible ranges. An online service and free software for parameter balancing with models provided in SBML format (Systems Biology Markup Language) is accessible at www.semanticsbml.org. We demonstrate its practical use with a small model of the phosphofructokinase reaction and discuss its possible applications and limitations. In the future, parameter balancing could become an important routine step in the kinetic modeling of large metabolic networks. PMID:21038890

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