Simulation tools for particle-based reaction-diffusion dynamics in continuous space

PubMed Central

2014-01-01

Particle-based reaction-diffusion algorithms facilitate the modeling of the diffusional motion of individual molecules and the reactions between them in cellular environments. A physically realistic model, depending on the system at hand and the questions asked, would require different levels of modeling detail such as particle diffusion, geometrical confinement, particle volume exclusion or particle-particle interaction potentials. Higher levels of detail usually correspond to increased number of parameters and higher computational cost. Certain systems however, require these investments to be modeled adequately. Here we present a review on the current field of particle-based reaction-diffusion software packages operating on continuous space. Four nested levels of modeling detail are identified that capture incrementing amount of detail. Their applicability to different biological questions is discussed, arching from straight diffusion simulations to sophisticated and expensive models that bridge towards coarse grained molecular dynamics. PMID:25737778

Development of interactive graphic user interfaces for modeling reaction-based biogeochemical processes in batch systems with BIOGEOCHEM

NASA Astrophysics Data System (ADS)

Chang, C.; Li, M.; Yeh, G.

2010-12-01

The BIOGEOCHEM numerical model (Yeh and Fang, 2002; Fang et al., 2003) was developed with FORTRAN for simulating reaction-based geochemical and biochemical processes with mixed equilibrium and kinetic reactions in batch systems. A complete suite of reactions including aqueous complexation, adsorption/desorption, ion-exchange, redox, precipitation/dissolution, acid-base reactions, and microbial mediated reactions were embodied in this unique modeling tool. Any reaction can be treated as fast/equilibrium or slow/kinetic reaction. An equilibrium reaction is modeled with an implicit finite rate governed by a mass action equilibrium equation or by a user-specified algebraic equation. A kinetic reaction is modeled with an explicit finite rate with an elementary rate, microbial mediated enzymatic kinetics, or a user-specified rate equation. None of the existing models has encompassed this wide array of scopes. To ease the input/output learning curve using the unique feature of BIOGEOCHEM, an interactive graphic user interface was developed with the Microsoft Visual Studio and .Net tools. Several user-friendly features, such as pop-up help windows, typo warning messages, and on-screen input hints, were implemented, which are robust. All input data can be real-time viewed and automated to conform with the input file format of BIOGEOCHEM. A post-processor for graphic visualizations of simulated results was also embedded for immediate demonstrations. By following data input windows step by step, errorless BIOGEOCHEM input files can be created even if users have little prior experiences in FORTRAN. With this user-friendly interface, the time effort to conduct simulations with BIOGEOCHEM can be greatly reduced.

Timescale analysis of rule-based biochemical reaction networks

PubMed Central

Klinke, David J.; Finley, Stacey D.

2012-01-01

The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150

A study of hydriding kinetics of metal hydrides using a physically based model

NASA Astrophysics Data System (ADS)

Voskuilen, Tyler G.

The reaction of hydrogen with metals to form metal hydrides has numerous potential energy storage and management applications. The metal hydrogen system has a high volumetric energy density and is often reversible with a high cycle life. The stored hydrogen can be used to produce energy through combustion, reaction in a fuel cell, or electrochemically in metal hydride batteries. The high enthalpy of the metal-hydrogen reaction can also be used for rapid heat removal or delivery. However, improving the often poor gravimetric performance of such systems through the use of lightweight metals usually comes at the cost of reduced reaction rates or the requirement of pressure and temperature conditions far from the desired operating conditions. In this work, a 700 bar Sievert system was developed at the Purdue Hydrogen Systems Laboratory to study the kinetic and thermodynamic behavior of high pressure hydrogen absorption under near-ambient temperatures. This system was used to determine the kinetic and thermodynamic properties of TiCrMn, an intermetallic metal hydride of interest due to its ambient temperature performance for vehicular applications. A commonly studied intermetallic hydride, LaNi5, was also characterized as a base case for the phase field model. The analysis of the data obtained from such a system necessitate the use of specialized techniques to decouple the measured reaction rates from experimental conditions. These techniques were also developed as a part of this work. Finally, a phase field model of metal hydride formation in mass-transport limited interstitial solute reactions based on the regular solution model was developed and compared with measured kinetics of LaNi5 and TiCrMn. This model aided in the identification of key reaction features and was used to verify the proposed technique for the analysis of gas-solid reaction rates determined volumetrically. Additionally, the phase field model provided detailed quantitative predictions of the effects of multidimensional phase growth and transitions between rate-limiting processes on the experimentally determined reaction rates. Unlike conventional solid state reaction analysis methods, this model relies fully on rate parameters based on the physical mechanisms occurring in the hydride reaction and can be extended to reactions in any dimension.

Model Experiment of Thermal Runaway Reactions Using the Aluminum-Hydrochloric Acid Reaction

ERIC Educational Resources Information Center

Kitabayashi, Suguru; Nakano, Masayoshi; Nishikawa, Kazuyuki; Koga, Nobuyoshi

2016-01-01

A laboratory exercise for the education of students about thermal runaway reactions based on the reaction between aluminum and hydrochloric acid as a model reaction is proposed. In the introductory part of the exercise, the induction period and subsequent thermal runaway behavior are evaluated via a simple observation of hydrogen gas evolution and…

Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms

DOE PAGES

Gao, Connie W.; Allen, Joshua W.; Green, William H.; ...

2016-02-24

Reaction Mechanism Generator (RMG) constructs kinetic models composed of elementary chemical reaction steps using a general understanding of how molecules react. Species thermochemistry is estimated through Benson group additivity and reaction rate coefficients are estimated using a database of known rate rules and reaction templates. At its core, RMG relies on two fundamental data structures: graphs and trees. Graphs are used to represent chemical structures, and trees are used to represent thermodynamic and kinetic data. Models are generated using a rate-based algorithm which excludes species from the model based on reaction fluxes. RMG can generate reaction mechanisms for species involvingmore » carbon, hydrogen, oxygen, sulfur, and nitrogen. It also has capabilities for estimating transport and solvation properties, and it automatically computes pressure-dependent rate coefficients and identifies chemically-activated reaction paths. RMG is an object-oriented program written in Python, which provides a stable, robust programming architecture for developing an extensible and modular code base with a large suite of unit tests. Computationally intensive functions are cythonized for speed improvements.« less

The Variance Reaction Time Model

ERIC Educational Resources Information Center

Sikstrom, Sverker

2004-01-01

The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…

Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling

NASA Astrophysics Data System (ADS)

Sutton, Jonathan E.; Guo, Wei; Katsoulakis, Markos A.; Vlachos, Dionisios G.

2016-04-01

Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.

Mixed quantum-classical simulation of the hydride transfer reaction catalyzed by dihydrofolate reductase based on a mapped system-harmonic bath model

NASA Astrophysics Data System (ADS)

Xu, Yang; Song, Kai; Shi, Qiang

2018-03-01

The hydride transfer reaction catalyzed by dihydrofolate reductase is studied using a recently developed mixed quantum-classical method to investigate the nuclear quantum effects on the reaction. Molecular dynamics simulation is first performed based on a two-state empirical valence bond potential to map the atomistic model to an effective double-well potential coupled to a harmonic bath. In the mixed quantum-classical simulation, the hydride degree of freedom is quantized, and the effective harmonic oscillator modes are treated classically. It is shown that the hydride transfer reaction rate using the mapped effective double-well/harmonic-bath model is dominated by the contribution from the ground vibrational state. Further comparison with the adiabatic reaction rate constant based on the Kramers theory confirms that the reaction is primarily vibrationally adiabatic, which agrees well with the high transmission coefficients found in previous theoretical studies. The calculated kinetic isotope effect is also consistent with the experimental and recent theoretical results.

A genetically optimized kinetic model for ethanol electro-oxidation on Pt-based binary catalysts used in direct ethanol fuel cells

NASA Astrophysics Data System (ADS)

Sánchez-Monreal, Juan; García-Salaberri, Pablo A.; Vera, Marcos

2017-09-01

A one-dimensional model is proposed for the anode of a liquid-feed direct ethanol fuel cell. The complex kinetics of the ethanol electro-oxidation reaction is described using a multi-step reaction mechanism that considers free and adsorbed intermediate species on Pt-based binary catalysts. The adsorbed species are modeled using coverage factors to account for the blockage of the active reaction sites on the catalyst surface. The reaction rates are described by Butler-Volmer equations that are coupled to a one-dimensional mass transport model, which incorporates the effect of ethanol and acetaldehyde crossover. The proposed kinetic model circumvents the acetaldehyde bottleneck effect observed in previous studies by incorporating CH3CHOHads among the adsorbed intermediates. A multi-objetive genetic algorithm is used to determine the reaction constants using anode polarization and product selectivity data obtained from the literature. By adjusting the reaction constants using the methodology developed here, different catalyst layers could be modeled and their selectivities could be successfully reproduced.

A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions.

PubMed

Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C; Brooks, Scott C; Pace, Molly N; Kim, Young-Jin; Jardine, Philip M; Watson, David B

2007-06-16

This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing N(E) equilibrium reactions and a set of reactive transport equations of M-N(E) kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.

Consistent post-reaction vibrational energy redistribution in DSMC simulations using TCE model

NASA Astrophysics Data System (ADS)

Borges Sebastião, Israel; Alexeenko, Alina

2016-10-01

The direct simulation Monte Carlo (DSMC) method has been widely applied to study shockwaves, hypersonic reentry flows, and other nonequilibrium flow phenomena. Although there is currently active research on high-fidelity models based on ab initio data, the total collision energy (TCE) and Larsen-Borgnakke (LB) models remain the most often used chemistry and relaxation models in DSMC simulations, respectively. The conventional implementation of the discrete LB model, however, may not satisfy detailed balance when recombination and exchange reactions play an important role in the flow energy balance. This issue can become even more critical in reacting mixtures involving polyatomic molecules, such as in combustion. In this work, this important shortcoming is addressed and an empirical approach to consistently specify the post-reaction vibrational states close to thermochemical equilibrium conditions is proposed within the TCE framework. Following Bird's quantum-kinetic (QK) methodology for populating post-reaction states, the new TCE-based approach involves two main steps. The state-specific TCE reaction probabilities for a forward reaction are first pre-computed from equilibrium 0-D simulations. These probabilities are then employed to populate the post-reaction vibrational states of the corresponding reverse reaction. The new approach is illustrated by application to exchange and recombination reactions relevant to H2-O2 combustion processes.

A mesoscopic reaction rate model for shock initiation of multi-component PBX explosives.

PubMed

Liu, Y R; Duan, Z P; Zhang, Z Y; Ou, Z C; Huang, F L

2016-11-05

The primary goal of this research is to develop a three-term mesoscopic reaction rate model that consists of a hot-spot ignition, a low-pressure slow burning and a high-pressure fast reaction terms for shock initiation of multi-component Plastic Bonded Explosives (PBX). Thereinto, based on the DZK hot-spot model for a single-component PBX explosive, the hot-spot ignition term as well as its reaction rate is obtained through a "mixing rule" of the explosive components; new expressions for both the low-pressure slow burning term and the high-pressure fast reaction term are also obtained by establishing the relationships between the reaction rate of the multi-component PBX explosive and that of its explosive components, based on the low-pressure slow burning term and the high-pressure fast reaction term of a mesoscopic reaction rate model. Furthermore, for verification, the new reaction rate model is incorporated into the DYNA2D code to simulate numerically the shock initiation process of the PBXC03 and the PBXC10 multi-component PBX explosives, and the numerical results of the pressure histories at different Lagrange locations in explosive are found to be in good agreements with previous experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

Electrophilic assistance to the cleavage of an RNA model phopshodiester via specific and general base-catalyzed mechanisms.

PubMed

Corona-Martínez, David Octavio; Gomez-Tagle, Paola; Yatsimirsky, Anatoly K

2012-10-19

Kinetics of transesterification of the RNA model substrate 2-hydroxypropyl 4-nitrophenyl phosphate promoted by Mg(2+) and Ca(2+), the most common biological metals acting as cofactors for nuclease enzymes and ribozymes, as well as by Co(NH(3))(6)(3+), Co(en)(3)(3+), Li(+), and Na(+) cations, often employed as mechanistic probes, was studied in 80% v/v (50 mol %) aqueous DMSO, a medium that allows one to discriminate easily specific base (OH(-)-catalyzed) and general base (buffer-catalyzed) reaction paths. All cations assist the specific base reaction, but only Mg(2+) and Na(+) assist the general base reaction. For Mg(2+)-assisted reactions, the solvent deuterium isotope effects are 1.23 and 0.25 for general base and specific base mechanisms, respectively. Rate constants for Mg(2+)-assisted general base reactions measured with different bases fit the Brønsted correlation with a slope of 0.38, significantly lower than the slope for the unassisted general base reaction (0.77). Transition state binding constants for catalysts in the specific base reaction (K(‡)(OH)) both in aqueous DMSO and pure water correlate with their binding constants to 4-nitrophenyl phosphate dianion (K(NPP)) used as a minimalist transition state model. It was found that K(‡)(OH) ≈ K(NPP) for "protic" catalysts (Co(NH(3))(6)(3+), Co(en)(3)(3+), guanidinium), but K(‡)(OH) ≫ K(NPP) for Mg(2+) and Ca(2+) acting as Lewis acids. It appears from results of this study that Mg(2+) is unique in its ability to assist efficiently the general base-catalyzed transesterification often occurring in active sites of nuclease enzymes and ribozymes.

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

PubMed

Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan

2018-05-30

Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.

Multi-criteria comparative evaluation of spallation reaction models

NASA Astrophysics Data System (ADS)

Andrianov, Andrey; Andrianova, Olga; Konobeev, Alexandr; Korovin, Yury; Kuptsov, Ilya

2017-09-01

This paper presents an approach to a comparative evaluation of the predictive ability of spallation reaction models based on widely used, well-proven multiple-criteria decision analysis methods (MAVT/MAUT, AHP, TOPSIS, PROMETHEE) and the results of such a comparison for 17 spallation reaction models in the presence of the interaction of high-energy protons with natPb.

Consequences of Base Time for Redundant Signals Experiments

PubMed Central

Townsend, James T.; Honey, Christopher

2007-01-01

We report analytical and computational investigations into the effects of base time on the diagnosticity of two popular theoretical tools in the redundant signals literature: (1) the race model inequality and (2) the capacity coefficient. We show analytically and without distributional assumptions that the presence of base time decreases the sensitivity of both of these measures to model violations. We further use simulations to investigate the statistical power model selection tools based on the race model inequality, both with and without base time. Base time decreases statistical power, and biases the race model test toward conservatism. The magnitude of this biasing effect increases as we increase the proportion of total reaction time variance contributed by base time. We marshal empirical evidence to suggest that the proportion of reaction time variance contributed by base time is relatively small, and that the effects of base time on the diagnosticity of our model-selection tools are therefore likely to be minor. However, uncertainty remains concerning the magnitude and even the definition of base time. Experimentalists should continue to be alert to situations in which base time may contribute a large proportion of the total reaction time variance. PMID:18670591

Modeling of Water-Breathing Propulsion Systems Utilizing the Aluminum-Seawater Reaction and Solid-Oxide Fuel Cells

DTIC Science & Technology

2011-01-01

ABSTRACT Title of Document: MODELING OF WATER-BREATHING PROPULSION SYSTEMS UTILIZING THE ALUMINUM-SEAWATER REACTION AND SOLID...Hybrid Aluminum Combustor (HAC): a novel underwater power system based on the exothermic reaction of aluminum with seawater. The system is modeled ...using a NASA-developed framework called Numerical Propulsion System Simulation (NPSS) by assembling thermodynamic models developed for each component

Microscopic approach based on a multiscale algebraic version of the resonating group model for radiative capture reactions

NASA Astrophysics Data System (ADS)

Solovyev, Alexander S.; Igashov, Sergey Yu.

2017-12-01

A microscopic approach to description of radiative capture reactions based on a multiscale algebraic version of the resonating group model is developed. The main idea of the approach is to expand wave functions of discrete spectrum and continuum for a nuclear system over different bases of the algebraic version of the resonating group model. These bases differ from each other by values of oscillator radius playing a role of scale parameter. This allows us in a unified way to calculate total and partial cross sections (astrophysical S factors) as well as branching ratio for the radiative capture reaction, to describe phase shifts for the colliding nuclei in the initial channel of the reaction, and at the same time to reproduce breakup thresholds of the final nucleus. The approach is applied to the theoretical study of the mirror 3H(α ,γ )7Li and 3He(α ,γ )7Be reactions, which are of great interest to nuclear astrophysics. The calculated results are compared with existing experimental data and with our previous calculations in the framework of the single-scale algebraic version of the resonating group model.

Kinetic analysis of reactions of Si-based epoxy resins by near-infrared spectroscopy, 13C NMR and soft-hard modelling.

PubMed

Garrido, Mariano; Larrechi, Maria Soledad; Rius, F Xavier; Mercado, Luis Adolfo; Galià, Marina

2007-02-05

Soft- and hard-modelling strategy was applied to near-infrared spectroscopy data obtained from monitoring the reaction between glycidyloxydimethylphenyl silane, a silicon-based epoxy monomer, and aniline. On the basis of the pure soft-modelling approach and previous chemical knowledge, a kinetic model for the reaction was proposed. Then, multivariate curve resolution-alternating least squares optimization was carried out under a hard constraint, that compels the concentration profiles to fulfil the proposed kinetic model at each iteration of the optimization process. In this way, the concentration profiles of each species and the corresponding kinetic rate constants of the reaction, unpublished until now, were obtained. The results obtained were contrasted with 13C NMR. The joint interval test of slope and intercept for detecting bias was not significant (alpha=5%).

Interplay between inhibited transport and reaction in nanoporous materials

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

Ackerman, David Michael

2013-01-01

This work presents a detailed formulation of reaction and diffusion dynamics of molecules in confined pores such as mesoporous silica and zeolites. A general reaction-diffusion model and discrete Monte Carlo simulations are presented. Both transient and steady state behavior is covered. Failure of previous mean-field models for these systems is explained and discussed. A coarse-grained, generalized hydrodynamic model is developed that accurately captures the interplay between reaction and restricted transport in these systems. This method incorporates the non-uniform chemical diffusion behavior present in finite pores with multi-component diffusion. Two methods of calculating these diffusion values are developed: a random walkmore » based approach and a driven diffusion model based on an extension of Fick's law. The effects of reaction, diffusion, pore length, and catalytic site distribution are investigated. In addition to strictly single file motion, quasi-single file diffusion is incorporated into the model to match a range of experimental systems. The connection between these experimental systems and model parameters is made through Langevin dynamics modeling of particles in confined pores.« less

A method for integrating and ranking the evidence for biochemical pathways by mining reactions from text

PubMed Central

Miwa, Makoto; Ohta, Tomoko; Rak, Rafal; Rowley, Andrew; Kell, Douglas B.; Pyysalo, Sampo; Ananiadou, Sophia

2013-01-01

Motivation: To create, verify and maintain pathway models, curators must discover and assess knowledge distributed over the vast body of biological literature. Methods supporting these tasks must understand both the pathway model representations and the natural language in the literature. These methods should identify and order documents by relevance to any given pathway reaction. No existing system has addressed all aspects of this challenge. Method: We present novel methods for associating pathway model reactions with relevant publications. Our approach extracts the reactions directly from the models and then turns them into queries for three text mining-based MEDLINE literature search systems. These queries are executed, and the resulting documents are combined and ranked according to their relevance to the reactions of interest. We manually annotate document-reaction pairs with the relevance of the document to the reaction and use this annotation to study several ranking methods, using various heuristic and machine-learning approaches. Results: Our evaluation shows that the annotated document-reaction pairs can be used to create a rule-based document ranking system, and that machine learning can be used to rank documents by their relevance to pathway reactions. We find that a Support Vector Machine-based system outperforms several baselines and matches the performance of the rule-based system. The success of the query extraction and ranking methods are used to update our existing pathway search system, PathText. Availability: An online demonstration of PathText 2 and the annotated corpus are available for research purposes at http://www.nactem.ac.uk/pathtext2/. Contact: makoto.miwa@manchester.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23813008

Geochemical modeling of reactions and partitioning of trace metals and radionuclides during titration of contaminated acidic sediments.

PubMed

Zhang, Fan; Luo, Wensui; Parker, Jack C; Spalding, Brian P; Brooks, Scott C; Watson, David B; Jardine, Philip M; Gu, Baohua

2008-11-01

Many geochemical reactions that control aqueous metal concentrations are directly affected by solution pH. However, changes in solution pH are strongly buffered by various aqueous phase and solid phase precipitation/dissolution and adsorption/desorption reactions. The ability to predict acid-base behavior of the soil-solution system is thus critical to predict metal transport under variable pH conditions. This studywas undertaken to develop a practical generic geochemical modeling approach to predict aqueous and solid phase concentrations of metals and anions during conditions of acid or base additions. The method of Spalding and Spalding was utilized to model soil buffer capacity and pH-dependent cation exchange capacity by treating aquifer solids as a polyprotic acid. To simulate the dynamic and pH-dependent anion exchange capacity, the aquifer solids were simultaneously treated as a polyprotic base controlled by mineral precipitation/ dissolution reactions. An equilibrium reaction model that describes aqueous complexation, precipitation, sorption and soil buffering with pH-dependent ion exchange was developed using HydroGeoChem v5.0 (HGC5). Comparison of model results with experimental titration data of pH, Al, Ca, Mg, Sr, Mn, Ni, Co, and SO4(2-) for contaminated sediments indicated close agreement suggesting that the model could potentially be used to predictthe acid-base behavior of the sediment-solution system under variable pH conditions.

Ontology aided modeling of organic reaction mechanisms with flexible and fragment based XML markup procedures.

PubMed

Sankar, Punnaivanam; Aghila, Gnanasekaran

2007-01-01

The mechanism models for primary organic reactions encoding the structural fragments undergoing substitution, addition, elimination, and rearrangements are developed. In the proposed models, each and every structural component of mechanistic pathways is represented with flexible and fragment based markup technique in XML syntax. A significant feature of the system is the encoding of the electron movements along with the other components like charges, partial charges, half bonded species, lone pair electrons, free radicals, reaction arrows, etc. needed for a complete representation of reaction mechanism. The rendering of reaction schemes described with the proposed methodology is achieved with a concise XML extension language interoperating with the structure markup. The reaction scheme is visualized as 2D graphics in a browser by converting them into SVG documents enabling the desired layouts normally perceived by the chemists conventionally. An automatic representation of the complex patterns of the reaction mechanism is achieved by reusing the knowledge in chemical ontologies and developing artificial intelligence components in terms of axioms.

PhreeqcRM: A reaction module for transport simulators based on the geochemical model PHREEQC

USGS Publications Warehouse

Parkhurst, David L.; Wissmeier, Laurin

2015-01-01

PhreeqcRM is a geochemical reaction module designed specifically to perform equilibrium and kinetic reaction calculations for reactive transport simulators that use an operator-splitting approach. The basic function of the reaction module is to take component concentrations from the model cells of the transport simulator, run geochemical reactions, and return updated component concentrations to the transport simulator. If multicomponent diffusion is modeled (e.g., Nernst–Planck equation), then aqueous species concentrations can be used instead of component concentrations. The reaction capabilities are a complete implementation of the reaction capabilities of PHREEQC. In each cell, the reaction module maintains the composition of all of the reactants, which may include minerals, exchangers, surface complexers, gas phases, solid solutions, and user-defined kinetic reactants.PhreeqcRM assigns initial and boundary conditions for model cells based on standard PHREEQC input definitions (files or strings) of chemical compositions of solutions and reactants. Additional PhreeqcRM capabilities include methods to eliminate reaction calculations for inactive parts of a model domain, transfer concentrations and other model properties, and retrieve selected results. The module demonstrates good scalability for parallel processing by using multiprocessing with MPI (message passing interface) on distributed memory systems, and limited scalability using multithreading with OpenMP on shared memory systems. PhreeqcRM is written in C++, but interfaces allow methods to be called from C or Fortran. By using the PhreeqcRM reaction module, an existing multicomponent transport simulator can be extended to simulate a wide range of geochemical reactions. Results of the implementation of PhreeqcRM as the reaction engine for transport simulators PHAST and FEFLOW are shown by using an analytical solution and the reactive transport benchmark of MoMaS.

Iterated reaction graphs: simulating complex Maillard reaction pathways.

PubMed

Patel, S; Rabone, J; Russell, S; Tissen, J; Klaffke, W

2001-01-01

This study investigates a new method of simulating a complex chemical system including feedback loops and parallel reactions. The practical purpose of this approach is to model the actual reactions that take place in the Maillard process, a set of food browning reactions, in sufficient detail to be able to predict the volatile composition of the Maillard products. The developed framework, called iterated reaction graphs, consists of two main elements: a soup of molecules and a reaction base of Maillard reactions. An iterative process loops through the reaction base, taking reactants from and feeding products back to the soup. This produces a reaction graph, with molecules as nodes and reactions as arcs. The iterated reaction graph is updated and validated by comparing output with the main products found by classical gas-chromatographic/mass spectrometric analysis. To ensure a realistic output and convergence to desired volatiles only, the approach contains a number of novel elements: rate kinetics are treated as reaction probabilities; only a subset of the true chemistry is modeled; and the reactions are blocked into groups.

Automation of route identification and optimisation based on data-mining and chemical intuition.

PubMed

Lapkin, A A; Heer, P K; Jacob, P-M; Hutchby, M; Cunningham, W; Bull, S D; Davidson, M G

2017-09-21

Data-mining of Reaxys and network analysis of the combined literature and in-house reactions set were used to generate multiple possible reaction routes to convert a bio-waste feedstock, limonene, into a pharmaceutical API, paracetamol. The network analysis of data provides a rich knowledge-base for generation of the initial reaction screening and development programme. Based on the literature and the in-house data, an overall flowsheet for the conversion of limonene to paracetamol was proposed. Each individual reaction-separation step in the sequence was simulated as a combination of the continuous flow and batch steps. The linear model generation methodology allowed us to identify the reaction steps requiring further chemical optimisation. The generated model can be used for global optimisation and generation of environmental and other performance indicators, such as cost indicators. However, the identified further challenge is to automate model generation to evolve optimal multi-step chemical routes and optimal process configurations.

Simple model of inhibition of chain-branching combustion processes

NASA Astrophysics Data System (ADS)

Babushok, Valeri I.; Gubernov, Vladimir V.; Minaev, Sergei S.; Miroshnichenko, Taisia P.

2017-11-01

A simple kinetic model has been suggested to describe the inhibition and extinction of flame propagation in reaction systems with chain-branching reactions typical for hydrocarbon systems. The model is based on the generalised model of the combustion process with chain-branching reaction combined with the one-stage reaction describing the thermal mode of flame propagation with the addition of inhibition reaction steps. Inhibitor addition suppresses the radical overshoot in flame and leads to the change of reaction mode from the chain-branching reaction to a thermal mode of flame propagation. With the increase of inhibitor the transition of chain-branching mode of reaction to the reaction with straight-chains (non-branching chain reaction) is observed. The inhibition part of the model includes a block of three reactions to describe the influence of the inhibitor. The heat losses are incorporated into the model via Newton cooling. The flame extinction is the result of the decreased heat release of inhibited reaction processes and the suppression of radical overshoot with the further decrease of the reaction rate due to the temperature decrease and mixture dilution. A comparison of the results of modelling laminar premixed methane/air flames inhibited by potassium bicarbonate (gas phase model, detailed kinetic model) with the results obtained using the suggested simple model is presented. The calculations with the detailed kinetic model demonstrate the following modes of combustion process: (1) flame propagation with chain-branching reaction (with radical overshoot, inhibitor addition decreases the radical overshoot down to the equilibrium level); (2) saturation of chemical influence of inhibitor, and (3) transition to thermal mode of flame propagation (non-branching chain mode of reaction). The suggested simple kinetic model qualitatively reproduces the modes of flame propagation with the addition of the inhibitor observed using detailed kinetic models.

A reaction limited in vivo dissolution model for the study of drug absorption: Towards a new paradigm for the biopharmaceutic classification of drugs.

PubMed

Macheras, Panos; Iliadis, Athanassios; Melagraki, Georgia

2018-05-30

The aim of this work is to develop a gastrointestinal (GI) drug absorption model based on a reaction limited model of dissolution and consider its impact on the biopharmaceutic classification of drugs. Estimates for the fraction of dose absorbed as a function of dose, solubility, reaction/dissolution rate constant and the stoichiometry of drug-GI fluids reaction/dissolution were derived by numerical solution of the model equations. The undissolved drug dose and the reaction/dissolution rate constant drive the dissolution rate and determine the extent of absorption when high-constant drug permeability throughout the gastrointestinal tract is assumed. Dose is an important element of drug-GI fluids reaction/dissolution while solubility exclusively acts as an upper limit for drug concentrations in the lumen. The 3D plots of fraction of dose absorbed as a function of dose and reaction/dissolution rate constant for highly soluble and low soluble drugs for different "stoichiometries" (0.7, 1.0, 2.0) of the drug-reaction/dissolution with the GI fluids revealed that high extent of absorption was found assuming high drug- reaction/dissolution rate constant and high drug solubility. The model equations were used to simulate in vivo supersaturation and precipitation phenomena. The model developed provides the theoretical basis for the interpretation of the extent of drug's absorption on the basis of the parameters associated with the drug-GI fluids reaction/dissolution. A new paradigm emerges for the biopharmaceutic classification of drugs, namely, a model independent biopharmaceutic classification scheme of four drug categories based on either the fulfillment or not of the current dissolution criteria and the high or low % drug metabolism. Copyright © 2018. Published by Elsevier B.V.

An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models

PubMed Central

Chindelevitch, Leonid; Trigg, Jason; Regev, Aviv; Berger, Bonnie

2014-01-01

Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations. PMID:25291352

Tinnitus school: an educational approach to tinnitus management based on a stress-reaction tinnitus model.

PubMed

Alpini, Dario; Cesarani, Antonio; Hahn, Ales

2007-01-01

Stress is a significant factor influencing the clinical course of tinnitus. The auditory system is particularly sensitive to the effects of various stress factors (chemical, oxidative, emotional, etc.). Different stages of reaction (alarm, resistance, exhaustion) lead to different characteristics of tinnitus and to different therapeutic approaches. Individual characteristics of stress reaction may explain different aspects of tinnitus in various patients with different responses to treatment, despite similar audiological and etiological factors. A model based on individual reactions to stress factors (stress-reaction tinnitus model, or SRTM) could explain tinnitus as an alarm signal. In each patient, stressors have to be identified during the alarm phase to prevent an evolution toward the resistance and exhaustion phases. In the exhaustion phase, chronic tinnitus is due to the organization of a paradoxical auditory memory and a pathologically shifted attention to tinnitus. The aim of our study is to describe a therapeutic proposal based on the SRTM by taking an educational approach to management of chronic tinnitus. The educational aspect is emphasized; thus, we named our approach tinnitus school. Selection of appropriate patients and follow-up is based on psychometrics of tinnitus and stress questionnaires, including a tinnitus reaction questionnaire, a tinnitus cognitive questionnaire, and a 20-item perceived stress questionnaire. Tinnitus school is a three-phase program: counseling, training, and home training. Training is based on a tinnitus-fitted physiotherapeutic protocol.

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

Geochemical Modeling of Reactions and Partitioning of Trace Metals and Radionuclides during Titration of Contaminated Acidic Sediments

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

Zhang, Fan; Parker, Jack C.; Luo, Wensui

2008-01-01

Many geochemical reactions that control aqueous metal concentrations are directly affected by solution pH. However, changes in solution pH are strongly buffered by various aqueous phase and solid phase precipitation/dissolution and adsorption/desorption reactions. The ability to predict acid-base behavior of the soil-solution system is thus critical to predict metal transport under variable pH conditions. This study was undertaken to develop a practical generic geochemical modeling approach to predict aqueous and solid phase concentrations of metals and anions during conditions of acid or base additions. The method of Spalding and Spalding was utilized to model soil buffer capacity and pH-dependent cationmore » exchange capacity by treating aquifer solids as a polyprotic acid. To simulate the dynamic and pH-dependent anion exchange capacity, the aquifer solids were simultaneously treated as a polyprotic base controlled by mineral precipitation/dissolution reactions. An equilibrium reaction model that describes aqueous complexation, precipitation, sorption and soil buffering with pH-dependent ion exchange was developed using HydroGeoChem v5.0 (HGC5). Comparison of model results with experimental titration data of pH, Al, Ca, Mg, Sr, Mn, Ni, Co, and SO{sub 4}{sup 2-} for contaminated sediments indicated close agreement, suggesting that the model could potentially be used to predict the acid-base behavior of the sediment-solution system under variable pH conditions.« less

Multiscale Simulations of Reactive Transport

NASA Astrophysics Data System (ADS)

Tartakovsky, D. M.; Bakarji, J.

2014-12-01

Discrete, particle-based simulations offer distinct advantages when modeling solute transport and chemical reactions. For example, Brownian motion is often used to model diffusion in complex pore networks, and Gillespie-type algorithms allow one to handle multicomponent chemical reactions with uncertain reaction pathways. Yet such models can be computationally more intensive than their continuum-scale counterparts, e.g., advection-dispersion-reaction equations. Combining the discrete and continuum models has a potential to resolve the quantity of interest with a required degree of physicochemical granularity at acceptable computational cost. We present computational examples of such "hybrid models" and discuss the challenges associated with coupling these two levels of description.

A fully coupled 3D transport model in SPH for multi-species reaction-diffusion systems

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

Adami, Stefan; Hu, X. Y.; Adams, N. A.

2011-08-23

Abstract—In this paper we present a fully generalized transport model for multiple species in complex two and threedimensional geometries. Based on previous work [1] we have extended our interfacial reaction-diffusion model to handle arbitrary numbers of species allowing for coupled reaction models. Each species is tracked independently and we consider different physics of a species with respect to the bulk phases in contact. We use our SPH model to simulate the reaction-diffusion problem on a pore-scale level of a solid oxide fuel cell (SOFC) with special emphasize on the effect of surface diffusion.

Efficient reactive Brownian dynamics

DOE PAGES

Donev, Aleksandar; Yang, Chiao-Yu; Kim, Changho

2018-01-21

We develop a Split Reactive Brownian Dynamics (SRBD) algorithm for particle simulations of reaction-diffusion systems based on the Doi or volume reactivity model, in which pairs of particles react with a specified Poisson rate if they are closer than a chosen reactive distance. In our Doi model, we ensure that the microscopic reaction rules for various association and dissociation reactions are consistent with detailed balance (time reversibility) at thermodynamic equilibrium. The SRBD algorithm uses Strang splitting in time to separate reaction and diffusion and solves both the diffusion-only and reaction-only subproblems exactly, even at high packing densities. To efficiently processmore » reactions without uncontrolled approximations, SRBD employs an event-driven algorithm that processes reactions in a time-ordered sequence over the duration of the time step. A grid of cells with size larger than all of the reactive distances is used to schedule and process the reactions, but unlike traditional grid-based methods such as reaction-diffusion master equation algorithms, the results of SRBD are statistically independent of the size of the grid used to accelerate the processing of reactions. We use the SRBD algorithm to compute the effective macroscopic reaction rate for both reaction-limited and diffusion-limited irreversible association in three dimensions and compare to existing theoretical predictions at low and moderate densities. We also study long-time tails in the time correlation functions for reversible association at thermodynamic equilibrium and compare to recent theoretical predictions. Finally, we compare different particle and continuum methods on a model exhibiting a Turing-like instability and pattern formation. Our studies reinforce the common finding that microscopic mechanisms and correlations matter for diffusion-limited systems, making continuum and even mesoscopic modeling of such systems difficult or impossible. We also find that for models in which particles diffuse off lattice, such as the Doi model, reactions lead to a spurious enhancement of the effective diffusion coefficients.« less

Efficient reactive Brownian dynamics

NASA Astrophysics Data System (ADS)

Donev, Aleksandar; Yang, Chiao-Yu; Kim, Changho

2018-01-01

We develop a Split Reactive Brownian Dynamics (SRBD) algorithm for particle simulations of reaction-diffusion systems based on the Doi or volume reactivity model, in which pairs of particles react with a specified Poisson rate if they are closer than a chosen reactive distance. In our Doi model, we ensure that the microscopic reaction rules for various association and dissociation reactions are consistent with detailed balance (time reversibility) at thermodynamic equilibrium. The SRBD algorithm uses Strang splitting in time to separate reaction and diffusion and solves both the diffusion-only and reaction-only subproblems exactly, even at high packing densities. To efficiently process reactions without uncontrolled approximations, SRBD employs an event-driven algorithm that processes reactions in a time-ordered sequence over the duration of the time step. A grid of cells with size larger than all of the reactive distances is used to schedule and process the reactions, but unlike traditional grid-based methods such as reaction-diffusion master equation algorithms, the results of SRBD are statistically independent of the size of the grid used to accelerate the processing of reactions. We use the SRBD algorithm to compute the effective macroscopic reaction rate for both reaction-limited and diffusion-limited irreversible association in three dimensions and compare to existing theoretical predictions at low and moderate densities. We also study long-time tails in the time correlation functions for reversible association at thermodynamic equilibrium and compare to recent theoretical predictions. Finally, we compare different particle and continuum methods on a model exhibiting a Turing-like instability and pattern formation. Our studies reinforce the common finding that microscopic mechanisms and correlations matter for diffusion-limited systems, making continuum and even mesoscopic modeling of such systems difficult or impossible. We also find that for models in which particles diffuse off lattice, such as the Doi model, reactions lead to a spurious enhancement of the effective diffusion coefficients.

Efficient reactive Brownian dynamics

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

Donev, Aleksandar; Yang, Chiao-Yu; Kim, Changho

We develop a Split Reactive Brownian Dynamics (SRBD) algorithm for particle simulations of reaction-diffusion systems based on the Doi or volume reactivity model, in which pairs of particles react with a specified Poisson rate if they are closer than a chosen reactive distance. In our Doi model, we ensure that the microscopic reaction rules for various association and dissociation reactions are consistent with detailed balance (time reversibility) at thermodynamic equilibrium. The SRBD algorithm uses Strang splitting in time to separate reaction and diffusion and solves both the diffusion-only and reaction-only subproblems exactly, even at high packing densities. To efficiently processmore » reactions without uncontrolled approximations, SRBD employs an event-driven algorithm that processes reactions in a time-ordered sequence over the duration of the time step. A grid of cells with size larger than all of the reactive distances is used to schedule and process the reactions, but unlike traditional grid-based methods such as reaction-diffusion master equation algorithms, the results of SRBD are statistically independent of the size of the grid used to accelerate the processing of reactions. We use the SRBD algorithm to compute the effective macroscopic reaction rate for both reaction-limited and diffusion-limited irreversible association in three dimensions and compare to existing theoretical predictions at low and moderate densities. We also study long-time tails in the time correlation functions for reversible association at thermodynamic equilibrium and compare to recent theoretical predictions. Finally, we compare different particle and continuum methods on a model exhibiting a Turing-like instability and pattern formation. Our studies reinforce the common finding that microscopic mechanisms and correlations matter for diffusion-limited systems, making continuum and even mesoscopic modeling of such systems difficult or impossible. We also find that for models in which particles diffuse off lattice, such as the Doi model, reactions lead to a spurious enhancement of the effective diffusion coefficients.« less

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

NASA Astrophysics Data System (ADS)

Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

2013-09-01

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Tartakovsky, G.; Tartakovsky, A. M.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

2012-12-01

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

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

Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.

2013-09-07

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated withmore » microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).« less

Rule-based spatial modeling with diffusing, geometrically constrained molecules.

PubMed

Gruenert, Gerd; Ibrahim, Bashar; Lenser, Thorsten; Lohel, Maiko; Hinze, Thomas; Dittrich, Peter

2010-06-07

We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

Rule-based spatial modeling with diffusing, geometrically constrained molecules

PubMed Central

2010-01-01

Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly. PMID:20529264

Rule-based modeling with Virtual Cell

PubMed Central

Schaff, James C.; Vasilescu, Dan; Moraru, Ion I.; Loew, Leslie M.; Blinov, Michael L.

2016-01-01

Summary: Rule-based modeling is invaluable when the number of possible species and reactions in a model become too large to allow convenient manual specification. The popular rule-based software tools BioNetGen and NFSim provide powerful modeling and simulation capabilities at the cost of learning a complex scripting language which is used to specify these models. Here, we introduce a modeling tool that combines new graphical rule-based model specification with existing simulation engines in a seamless way within the familiar Virtual Cell (VCell) modeling environment. A mathematical model can be built integrating explicit reaction networks with reaction rules. In addition to offering a large choice of ODE and stochastic solvers, a model can be simulated using a network free approach through the NFSim simulation engine. Availability and implementation: Available as VCell (versions 6.0 and later) at the Virtual Cell web site (http://vcell.org/). The application installs and runs on all major platforms and does not require registration for use on the user’s computer. Tutorials are available at the Virtual Cell website and Help is provided within the software. Source code is available at Sourceforge. Contact: vcell_support@uchc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27497444

Neutron-induced reactions on AlF3 studied using the optical model

NASA Astrophysics Data System (ADS)

Ma, Chun-Wang; Lv, Cui-Juan; Zhang, Guo-Qiang; Wang, Hong-Wei; Zuo, Jia-Xu

2015-08-01

Neutron-induced reactions on 27Al and 19F nuclei are investigated using the optical model implemented in the TALYS 1.4 toolkit. Incident neutron energies in a wide range from 0.1 keV to 30 MeV are calculated. The cross sections for the main channels (n, np), (n, p), (n, α), (n, 2n), and (n, γ) and the total reaction cross section (n, tot) of the reactions are obtained. When the default parameters in TALYS 1.4 are adopted, the calculated results agree with the measured results. Based on the calculated results for the n + 27Al and n + 19F reactions, the results of the n + 27Al19F reactions are predicted. These results are useful both for the design of thorium-based molten salt reactors and for neutron activation analysis techniques.

Mechanism of multinucleon transfer reaction based on the GRAZING model and DNS model

NASA Astrophysics Data System (ADS)

Wen, Pei-wei; Li, Cheng; Zhu, Long; Lin, Cheng-jian; Zhang, Feng-shou

2017-11-01

Multinucleon transfer (MNT) reactions have been studied by either the GRAZING model or dinuclear system (DNS) model before. MNT reactions in the grazing regime have been described quite well by the GRAZING model. The DNS model is able to deal with MNT reactions, which happen in the closer overlapped regime after contact of two colliding nuclei. Since MNT reactions can happen in both areas and cannot be distinguished in view of experimental work, it is beneficial to compare these two models to clarify mechanism of MNT reactions. In this study, the mechanism of the MNT reaction has been studied by comparing the GRAZING model and DNS model for the first time. Reaction systems 136Xe+208Pb at {E}{{c}.{{m}}.}=450 MeV and 64Ni+238U at {E}{{c}.{{m}}.}=307 MeV are taken as examples in this paper. It is found that the gradients of transfer cross sections with respect to the impact parameter of the GRAZING model and DNS model are mainly concentrated on two different areas, which represents two kinds of transfer mechanisms. The theoretical framework of these two models are exclusive according to whether capture happens, which guarantees that the theoretical results calculated by these two models have no overlap and can be added up. Results indicate that the description of experimental MNT reaction cross sections can be significantly improved if calculations of the GRAZING model and DNS model are both considered.

On the Development of a New Nonequilibrium Chemistry Model for Mars Entry

NASA Technical Reports Server (NTRS)

Jaffe, R. L.; Schwenke, D. W.; Chaban, G. M.; Prabhu, D. K.; Johnston, C. O.; Panesi, M.

2017-01-01

This paper represents a summary of results to date of an on-going effort at NASA Ames Research Center to develop a physics-based non-equilibrium model for hypersonic entry into the Martian atmosphere. Our approach is to first compute potential energy surfaces based on accurate solutions of the electronic Schroedinger equation and then use quasiclassical trajectory calculations to obtain reaction cross sections and rate coefficients based on these potentials. We have presented new rate coefficients for N2 dissociation and CO dissociation and exchange reactions. These results illustrate shortcomings with some of the rate coefficients in Parks original T-Tv model for Mars entries and with some of the 30-45 year old shock tube data. We observe that the shock tube experiments of CO + O dissociation did not adequately account for the exchange reaction that leads to formation of C + O2. This reaction is actually the primary channel for CO removal in the shock layer at temperatures below 10,000 K, because the reaction enthalpy for exchange is considerably lower than the comparable value for dissociation.

Neural network modeling of the kinetics of SO2 removal by fly ash-based sorbent.

PubMed

Raymond-Ooi, E H; Lee, K T; Mohamed, A R; Chu, K H

2006-01-01

The mechanistic modeling of the sulfation reaction between fly ash-based sorbent and SO2 is a challenging task due to a variety reasons including the complexity of the reaction itself and the inability to measure some of the key parameters of the reaction. In this work, the possibility of modeling the sulfation reaction kinetics using a purely data-driven neural network was investigated. Experiments on SO2 removal by a sorbent prepared from coal fly ash/CaO/CaSO4 were conducted using a fixed bed reactor to generate a database to train and validate the neural network model. Extensive SO2 removal data points were obtained by varying three process variables, namely, SO2 inlet concentration (500-2000 mg/L), reaction temperature (60-80 degreesC), and relative humidity (50-70%), as a function of reaction time (0-60 min). Modeling results show that the neural network can provide excellent fits to the SO2 removal data after considerable training and can be successfully used to predict the extent of SO2 removal as a function of time even when the process variables are outside the training domain. From a modeling standpoint, the suitably trained and validated neural network with excellent interpolation and extrapolation properties could have immediate practical benefits in the absence of a theoretical model.

Formal modeling of a system of chemical reactions under uncertainty.

PubMed

Ghosh, Krishnendu; Schlipf, John

2014-10-01

We describe a novel formalism representing a system of chemical reactions, with imprecise rates of reactions and concentrations of chemicals, and describe a model reduction method, pruning, based on the chemical properties. We present two algorithms, midpoint approximation and interval approximation, for construction of efficient model abstractions with uncertainty in data. We evaluate computational feasibility by posing queries in computation tree logic (CTL) on a prototype of extracellular-signal-regulated kinase (ERK) pathway.

Self-optimisation and model-based design of experiments for developing a C-H activation flow process.

PubMed

Echtermeyer, Alexander; Amar, Yehia; Zakrzewski, Jacek; Lapkin, Alexei

2017-01-01

A recently described C(sp 3 )-H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE) and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

Invariant characteristics of self-organization modes in Belousov reaction modeling

NASA Astrophysics Data System (ADS)

Glyzin, S. D.; Goryunov, V. E.; Kolesov, A. Yu

2018-01-01

We consider the problem of mathematical modeling of oxidation-reduction oscillatory chemical reactions based on the mechanism of Belousov reaction. The process of the main components interaction in such reaction can be interpreted by a phenomenologically similar to it “predator-prey” model. Thereby, we consider a parabolic boundary value problem consisting of three Volterra-type equations, which is a mathematical model of this reaction. We carry out a local study of the neighborhood of the system’s non-trivial equilibrium state and construct the normal form of the considering system. Finally, we do a numerical analysis of the coexisting chaotic oscillatory modes of the boundary value problem in a flat area, which have different nature and occur as the diffusion coefficient decreases.

The Fixed-Links Model in Combination with the Polynomial Function as a Tool for Investigating Choice Reaction Time Data

ERIC Educational Resources Information Center

Schweizer, Karl

2006-01-01

A model with fixed relations between manifest and latent variables is presented for investigating choice reaction time data. The numbers for fixation originate from the polynomial function. Two options are considered: the component-based (1 latent variable for each component of the polynomial function) and composite-based options (1 latent…

MODELING CHLORINE RESIDUALS IN DRINKING-WATER DISTRIBUTION SYSTEMS

EPA Science Inventory

A mass-transfer-based model is developed for predicting chlorine decay in drinking-water distribution networks. The model considers first-order reactions of chlorine to occur both in the bulk flow and at the pipe wall. The overall rate of the wall reaction is a function of the ...

MODELING CHLORINE RESIDUALS IN DRINKING-WATER DISTRIBUTION SYSTEMS

EPA Science Inventory

A mass transfer-based model is developed for predicting chlorine decay in drinking water distribution networks. he model considers first order reactions of chlorine to occur both in the bulk flow and at the pipe wall. he overall rate of the wall reaction is a function of the rate...

The photochemical formation and gas-particle partitioning of oxidation products of decamethyl cyclopentasiloxane and decamethyl tetrasiloxane in the atmosphere

NASA Astrophysics Data System (ADS)

Chandramouli, Bharadwaj; Kamens, Richard M.

Decamethyl cyclopentasiloxane (D 5) and decamethyl tetrasiloxane (MD 2M) were injected into a smog chamber containing fine Arizona road dust particles (95% surface area <2.6 μM) and an urban smog atmosphere in the daytime. A photochemical reaction - gas-particle partitioning reaction scheme, was implemented to simulate the formation and gas-particle partitioning of hydroxyl oxidation products of D 5 and MD 2M. This scheme incorporated the reactions of D 5 and MD 2M into an existing urban smog chemical mechanism carbon bond IV and partitioned the products between gas and particle phase by treating gas-particle partitioning as a kinetic process and specifying an uptake and off-gassing rate. A photochemical model PKSS was used to simulate this set of reactions. A Langmuirian partitioning model was used to convert the measured and estimated mass-based partitioning coefficients ( KP) to a molar or volume-based form. The model simulations indicated that >99% of all product silanol formed in the gas-phase partition immediately to particle phase and the experimental data agreed with model predictions. One product, D 4TOH was observed and confirmed for the D 5 reaction and this system was modeled successfully. Experimental data was inadequate for MD 2M reaction products and it is likely that more than one product formed. The model set up a framework into which more reaction and partitioning steps can be easily added.

Computational methods for diffusion-influenced biochemical reactions.

PubMed

Dobrzynski, Maciej; Rodríguez, Jordi Vidal; Kaandorp, Jaap A; Blom, Joke G

2007-08-01

We compare stochastic computational methods accounting for space and discrete nature of reactants in biochemical systems. Implementations based on Brownian dynamics (BD) and the reaction-diffusion master equation are applied to a simplified gene expression model and to a signal transduction pathway in Escherichia coli. In the regime where the number of molecules is small and reactions are diffusion-limited predicted fluctuations in the product number vary between the methods, while the average is the same. Computational approaches at the level of the reaction-diffusion master equation compute the same fluctuations as the reference result obtained from the particle-based method if the size of the sub-volumes is comparable to the diameter of reactants. Using numerical simulations of reversible binding of a pair of molecules we argue that the disagreement in predicted fluctuations is due to different modeling of inter-arrival times between reaction events. Simulations for a more complex biological study show that the different approaches lead to different results due to modeling issues. Finally, we present the physical assumptions behind the mesoscopic models for the reaction-diffusion systems. Input files for the simulations and the source code of GMP can be found under the following address: http://www.cwi.nl/projects/sic/bioinformatics2007/

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration.

PubMed

Chen, Yunjin; Pock, Thomas

2017-06-01

Image restoration is a long-standing problem in low-level computer vision with many interesting applications. We describe a flexible learning framework based on the concept of nonlinear reaction diffusion models for various image restoration problems. By embodying recent improvements in nonlinear diffusion models, we propose a dynamic nonlinear reaction diffusion model with time-dependent parameters (i.e., linear filters and influence functions). In contrast to previous nonlinear diffusion models, all the parameters, including the filters and the influence functions, are simultaneously learned from training data through a loss based approach. We call this approach TNRD-Trainable Nonlinear Reaction Diffusion. The TNRD approach is applicable for a variety of image restoration tasks by incorporating appropriate reaction force. We demonstrate its capabilities with three representative applications, Gaussian image denoising, single image super resolution and JPEG deblocking. Experiments show that our trained nonlinear diffusion models largely benefit from the training of the parameters and finally lead to the best reported performance on common test datasets for the tested applications. Our trained models preserve the structural simplicity of diffusion models and take only a small number of diffusion steps, thus are highly efficient. Moreover, they are also well-suited for parallel computation on GPUs, which makes the inference procedure extremely fast.

Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

PubMed Central

Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas; Hebbelmann, Inga; Rolletschek, Hardy; Schwender, Jorg

2014-01-01

The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) model and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis (13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). Using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content. PMID:25566296

Development of a Detailed Surface Chemistry Framework in DSMC

NASA Technical Reports Server (NTRS)

Swaminathan-Gopalan, K.; Borner, A.; Stephani, K. A.

2017-01-01

Many of the current direct simulation Monte Carlo (DSMC) codes still employ only simple surface catalysis models. These include only basic mechanisms such as dissociation, recombination, and exchange reactions, without any provision for adsorption and finite rate kinetics. Incorporating finite rate chemistry at the surface is increasingly becoming a necessity for various applications such as high speed re-entry flows over thermal protection systems (TPS), micro-electro-mechanical systems (MEMS), surface catalysis, etc. In the recent years, relatively few works have examined finite-rate surface reaction modeling using the DSMC method.In this work, a generalized finite-rate surface chemistry framework incorporating a comprehensive list of reaction mechanisms is developed and implemented into the DSMC solver SPARTA. The various mechanisms include adsorption, desorption, Langmuir-Hinshelwood (LH), Eley-Rideal (ER), Collision Induced (CI), condensation, sublimation, etc. The approach is to stochastically model the various competing reactions occurring on a set of active sites. Both gas-surface (e.g., ER, CI) and pure-surface (e.g., LH, desorption) reaction mechanisms are incorporated. The reaction mechanisms could also be catalytic or surface altering based on the participation of the bulk-phase species (e.g., bulk carbon atoms). Marschall and MacLean developed a general formulation in which multiple phases and surface sites are used and we adopt a similar convention in the current work. Microscopic parameters of reaction probabilities (for gas-surface reactions) and frequencies (for pure-surface reactions) that are require for DSMC are computed from the surface properties and macroscopic parameters such as rate constants, sticking coefficients, etc. The energy and angular distributions of the products are decided based on the reaction type and input parameters. Thus, the user has the capability to model various surface reactions via user-specified reaction rate constants, surface properties and parameters.

The effect of noise-induced variance on parameter recovery from reaction times.

PubMed

Vadillo, Miguel A; Garaizar, Pablo

2016-03-31

Technical noise can compromise the precision and accuracy of the reaction times collected in psychological experiments, especially in the case of Internet-based studies. Although this noise seems to have only a small impact on traditional statistical analyses, its effects on model fit to reaction-time distributions remains unexplored. Across four simulations we study the impact of technical noise on parameter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Model. Our results suggest that the impact of noise-induced variance tends to be limited to specific parameters and conditions. Although we encourage researchers to adopt all measures to reduce the impact of noise on reaction-time experiments, we conclude that the typical amount of noise-induced variance found in these experiments does not pose substantial problems for statistical analyses based on model fitting.

Effects of Material Degradation on the Structural Integrity of Composite Materials: Experimental Investigation and Modeling of High Temperature Degradation Mechanisms

NASA Technical Reports Server (NTRS)

Cunningham, Ronan A.; McManus, Hugh L.

1996-01-01

It has previously been demonstrated that simple coupled reaction-diffusion models can approximate the aging behavior of PMR-15 resin subjected to different oxidative environments. Based on empirically observed phenomena, a model coupling chemical reactions, both thermal and oxidative, with diffusion of oxygen into the material bulk should allow simulation of the aging process. Through preliminary modeling techniques such as this it has become apparent that accurate analytical models cannot be created until the phenomena which cause the aging of these materials are quantified. An experimental program is currently underway to quantify all of the reaction/diffusion related mechanisms involved. The following contains a summary of the experimental data which has been collected through thermogravimetric analyses of neat PMR-15 resin, along with analytical predictions from models based on the empirical data. Thermogravimetric analyses were carried out in a number of different environments - nitrogen, air and oxygen. The nitrogen provides data for the purely thermal degradation mechanisms while those in air provide data for the coupled oxidative-thermal process. The intent here is to effectively subtract the nitrogen atmosphere data (assumed to represent only thermal reactions) from the air and oxygen atmosphere data to back-figure the purely oxidative reactions. Once purely oxidative (concentration dependent) reactions have been quantified it should then be possible to quantify the diffusion of oxygen into the material bulk.

Integrating Geochemical Reactions with a Particle-Tracking Approach to Simulate Nitrogen Transport and Transformation in Aquifers

NASA Astrophysics Data System (ADS)

Cui, Z.; Welty, C.; Maxwell, R. M.

2011-12-01

Lagrangian, particle-tracking models are commonly used to simulate solute advection and dispersion in aquifers. They are computationally efficient and suffer from much less numerical dispersion than grid-based techniques, especially in heterogeneous and advectively-dominated systems. Although particle-tracking models are capable of simulating geochemical reactions, these reactions are often simplified to first-order decay and/or linear, first-order kinetics. Nitrogen transport and transformation in aquifers involves both biodegradation and higher-order geochemical reactions. In order to take advantage of the particle-tracking approach, we have enhanced an existing particle-tracking code SLIM-FAST, to simulate nitrogen transport and transformation in aquifers. The approach we are taking is a hybrid one: the reactive multispecies transport process is operator split into two steps: (1) the physical movement of the particles including the attachment/detachment to solid surfaces, which is modeled by a Lagrangian random-walk algorithm; and (2) multispecies reactions including biodegradation are modeled by coupling multiple Monod equations with other geochemical reactions. The coupled reaction system is solved by an ordinary differential equation solver. In order to solve the coupled system of equations, after step 1, the particles are converted to grid-based concentrations based on the mass and position of the particles, and after step 2 the newly calculated concentration values are mapped back to particles. The enhanced particle-tracking code is capable of simulating subsurface nitrogen transport and transformation in a three-dimensional domain with variably saturated conditions. Potential application of the enhanced code is to simulate subsurface nitrogen loading to the Chesapeake Bay and its tributaries. Implementation details, verification results of the enhanced code with one-dimensional analytical solutions and other existing numerical models will be presented in addition to a discussion of implementation challenges.

Assessment and Requirements of Nuclear Reaction Databases for GCR Transport in the Atmosphere and Structures

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Wilson, J. W.; Shinn, J. L.; Tripathi, R. K.

1998-01-01

The transport properties of galactic cosmic rays (GCR) in the atmosphere, material structures, and human body (self-shielding) am of interest in risk assessment for supersonic and subsonic aircraft and for space travel in low-Earth orbit and on interplanetary missions. Nuclear reactions, such as knockout and fragmentation, present large modifications of particle type and energies of the galactic cosmic rays in penetrating materials. We make an assessment of the current nuclear reaction models and improvements in these model for developing required transport code data bases. A new fragmentation data base (QMSFRG) based on microscopic models is compared to the NUCFRG2 model and implications for shield assessment made using the HZETRN radiation transport code. For deep penetration problems, the build-up of light particles, such as nucleons, light clusters and mesons from nuclear reactions in conjunction with the absorption of the heavy ions, leads to the dominance of the charge Z = 0, 1, and 2 hadrons in the exposures at large penetration depths. Light particles are produced through nuclear or cluster knockout and in evaporation events with characteristically distinct spectra which play unique roles in the build-up of secondary radiation's in shielding. We describe models of light particle production in nucleon and heavy ion induced reactions and make an assessment of the importance of light particle multiplicity and spectral parameters in these exposures.

Kinetic modeling of non-ideal explosives with CHEETAH

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

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

1998-08-06

We report an implementation of the Wood-Kirkwood kinetic detonation model based on multi-species equations of state and multiple reaction rate laws. Finite rate laws are used for the slowest chemical reactions. Other reactions are given infinite rates and are kept in constant thermodynamic equilibrium. We model a wide range of ideal and non-ideal composite energetic materials. We find that we can replicate experimental detonation velocities to within a few per cent, while obtaining good agreement with estimated reaction zone lengths. The detonation velocity as a function of charge radius is also correctly reproduced.

Automatized Assessment of Protective Group Reactivity: A Step Toward Big Reaction Data Analysis.

PubMed

Lin, Arkadii I; Madzhidov, Timur I; Klimchuk, Olga; Nugmanov, Ramil I; Antipin, Igor S; Varnek, Alexandre

2016-11-28

We report a new method to assess protective groups (PGs) reactivity as a function of reaction conditions (catalyst, solvent) using raw reaction data. It is based on an intuitive similarity principle for chemical reactions: similar reactions proceed under similar conditions. Technically, reaction similarity can be assessed using the Condensed Graph of Reaction (CGR) approach representing an ensemble of reactants and products as a single molecular graph, i.e., as a pseudomolecule for which molecular descriptors or fingerprints can be calculated. CGR-based in-house tools were used to process data for 142,111 catalytic hydrogenation reactions extracted from the Reaxys database. Our results reveal some contradictions with famous Greene's Reactivity Charts based on manual expert analysis. Models developed in this study show high accuracy (ca. 90%) for predicting optimal experimental conditions of protective group deprotection.

SurfKin: an ab initio kinetic code for modeling surface reactions.

PubMed

Le, Thong Nguyen-Minh; Liu, Bin; Huynh, Lam K

2014-10-05

In this article, we describe a C/C++ program called SurfKin (Surface Kinetics) to construct microkinetic mechanisms for modeling gas-surface reactions. Thermodynamic properties of reaction species are estimated based on density functional theory calculations and statistical mechanics. Rate constants for elementary steps (including adsorption, desorption, and chemical reactions on surfaces) are calculated using the classical collision theory and transition state theory. Methane decomposition and water-gas shift reaction on Ni(111) surface were chosen as test cases to validate the code implementations. The good agreement with literature data suggests this is a powerful tool to facilitate the analysis of complex reactions on surfaces, and thus it helps to effectively construct detailed microkinetic mechanisms for such surface reactions. SurfKin also opens a possibility for designing nanoscale model catalysts. Copyright © 2014 Wiley Periodicals, Inc.

ReaDDy - A Software for Particle-Based Reaction-Diffusion Dynamics in Crowded Cellular Environments

PubMed Central

Schöneberg, Johannes; Noé, Frank

2013-01-01

We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics. PMID:24040218

Solute transport with multiple equilibrium-controlled or kinetically controlled chemical reactions

USGS Publications Warehouse

Friedly, John C.; Rubin, Jacob

1992-01-01

A new approach is applied to the problem of modeling solute transport accompanied by many chemical reactions. The approach, based on concepts of the concentration space and its stoichiometric subspaces, uses elements of the subspaces as primary dependent variables. It is shown that the resulting model equations are compact in form, isolate the chemical reaction expressions from flow expressions, and can be used for either equilibrium or kinetically controlled reactions. The implications of the results on numerical algorithms for solving the equations are discussed. The application of the theory is illustrated throughout with examples involving a simple but broadly representative set of reactions previously considered in the literature. Numerical results are presented for four interconnected reactions: a homogeneous complexation reaction, two sorption reactions, and a dissolution/precipitation reaction. Three cases are considered: (1) four kinetically controlled reactions, (2) four equilibrium-controlled reactions, and (3) a system with two kinetically controlled reactions and two equilibrium-controlled reactions.

Vicher: A Virtual Reality Based Educational Module for Chemical Reaction Engineering.

ERIC Educational Resources Information Center

Bell, John T.; Fogler, H. Scott

1996-01-01

A virtual reality application for undergraduate chemical kinetics and reactor design education, Vicher (Virtual Chemical Reaction Model) was originally designed to simulate a portion of a modern chemical plant. Vicher now consists of two programs: Vicher I that models catalyst deactivation and Vicher II that models nonisothermal effects in…

Force modeling for incisions into various tissues with MRF haptic master

NASA Astrophysics Data System (ADS)

Kim, Pyunghwa; Kim, Soomin; Park, Young-Dai; Choi, Seung-Bok

2016-03-01

This study proposes a new model to predict the reaction force that occurs in incisions during robot-assisted minimally invasive surgery. The reaction force is fed back to the manipulator by a magneto-rheological fluid (MRF) haptic master, which is featured by a bi-directional clutch actuator. The reaction force feedback provides similar sensations to laparotomy that cannot be provided by a conventional master for surgery. This advantage shortens the training period for robot-assisted minimally invasive surgery and can improve the accuracy of operations. The reaction force modeling of incisions can be utilized in a surgical simulator that provides a virtual reaction force. In this work, in order to model the reaction force during incisions, the energy aspect of the incision process is adopted and analyzed. Each mode of the incision process is classified by the tendency of the energy change, and modeled for realistic real-time application. The reaction force model uses actual reaction force information with three types of actual tissues: hard tissue, medium tissue, and soft tissue. This modeled force is realized by the MRF haptic master through an algorithm based on the position and velocity of a scalpel using two different control methods: an open-loop algorithm and a closed-loop algorithm. The reaction forces obtained from the proposed model are compared with a desired force in time domain.

How accurate is automated gap filling of metabolic models?

PubMed

Karp, Peter D; Weaver, Daniel; Latendresse, Mario

2018-06-19

Reaction gap filling is a computational technique for proposing the addition of reactions to genome-scale metabolic models to permit those models to run correctly. Gap filling completes what are otherwise incomplete models that lack fully connected metabolic networks. The models are incomplete because they are derived from annotated genomes in which not all enzymes have been identified. Here we compare the results of applying an automated likelihood-based gap filler within the Pathway Tools software with the results of manually gap filling the same metabolic model. Both gap-filling exercises were applied to the same genome-derived qualitative metabolic reconstruction for Bifidobacterium longum subsp. longum JCM 1217, and to the same modeling conditions - anaerobic growth under four nutrients producing 53 biomass metabolites. The solution computed by the gap-filling program GenDev contained 12 reactions, but closer examination showed that solution was not minimal; two of the twelve reactions can be removed to yield a set of ten reactions that enable model growth. The manually curated solution contained 13 reactions, eight of which were shared with the 12-reaction computed solution. Thus, GenDev achieved recall of 61.5% and precision of 66.6%. These results suggest that although computational gap fillers are populating metabolic models with significant numbers of correct reactions, automatically gap-filled metabolic models also contain significant numbers of incorrect reactions. Our conclusion is that manual curation of gap-filler results is needed to obtain high-accuracy models. Many of the differences between the manual and automatic solutions resulted from using expert biological knowledge to direct the choice of reactions within the curated solution, such as reactions specific to the anaerobic lifestyle of B. longum.

Transport—Reaction process in the reaction of flue gas desulfurization

NASA Astrophysics Data System (ADS)

Yan, Yan; Peng, Xiaofeng; Lee, Duu Jong

2000-12-01

A theoretical investigation was conducted to study the transport-reaction process in the spray-drying flue gas desulfurization. A transport-reaction model of single particle was proposed, which considered the water evaporation from the surface of droplet and the reaction at the same time. Based on this model, the reaction rate and the absorbent utilization can be calculated. The most appropriate particle radius and the initial absorbent concentration can be deduced through comparing the wet lifetime with the residence time, the result shows in the case that the partial pressure of vapor in the bulk flue gas is 2000Pa, the optimum initial radius and absorbent concentration are 210 310 µ m and 23% respectively. The model can supply the optimum parameters for semi-dry FGD system designed.

Upper atmosphere research: Reaction rate and optical measurements

NASA Technical Reports Server (NTRS)

Stief, L. J.; Allen, J. E., Jr.; Nava, D. F.; Payne, W. A., Jr.

1990-01-01

The objective is to provide photochemical, kinetic, and spectroscopic information necessary for photochemical models of the Earth's upper atmosphere and to examine reactions or reactants not presently in the models to either confirm the correctness of their exclusion or provide evidence to justify future inclusion in the models. New initiatives are being taken in technique development (many of them laser based) and in the application of established techniques to address gaps in the photochemical/kinetic data base, as well as to provide increasingly reliable information.

Minimum reaction network necessary to describe Ar/CF4 plasma etch

NASA Astrophysics Data System (ADS)

Helpert, Sofia; Chopra, Meghali; Bonnecaze, Roger T.

2018-03-01

Predicting the etch and deposition profiles created using plasma processes is challenging due to the complexity of plasma discharges and plasma-surface interactions. Volume-averaged global models allow for efficient prediction of important processing parameters and provide a means to quickly determine the effect of a variety of process inputs on the plasma discharge. However, global models are limited based on simplifying assumptions to describe the chemical reaction network. Here a database of 128 reactions is compiled and their corresponding rate constants collected from 24 sources for an Ar/CF4 plasma using the platform RODEo (Recipe Optimization for Deposition and Etching). Six different reaction sets were tested which employed anywhere from 12 to all 128 reactions to evaluate the impact of the reaction database on particle species densities and electron temperature. Because many the reactions used in our database had conflicting rate constants as reported in literature, we also present a method to deal with those uncertainties when constructing the model which includes weighting each reaction rate and filtering outliers. By analyzing the link between a reaction's rate constant and its impact on the predicted plasma densities and electron temperatures, we determine the conditions at which a reaction is deemed necessary to the plasma model. The results of this study provide a foundation for determining which minimal set of reactions must be included in the reaction set of the plasma model.

A mathematical model for foreign body reactions in 2D.

PubMed

Su, Jianzhong; Gonzales, Humberto Perez; Todorov, Michail; Kojouharov, Hristo; Tang, Liping

2011-02-01

The foreign body reactions are commonly referred to the network of immune and inflammatory reactions of human or animals to foreign objects placed in tissues. They are basic biological processes, and are also highly relevant to bioengineering applications in implants, as fibrotic tissue formations surrounding medical implants have been found to substantially reduce the effectiveness of devices. Despite of intensive research on determining the mechanisms governing such complex responses, few mechanistic mathematical models have been developed to study such foreign body reactions. This study focuses on a kinetics-based predictive tool in order to analyze outcomes of multiple interactive complex reactions of various cells/proteins and biochemical processes and to understand transient behavior during the entire period (up to several months). A computational model in two spatial dimensions is constructed to investigate the time dynamics as well as spatial variation of foreign body reaction kinetics. The simulation results have been consistent with experimental data and the model can facilitate quantitative insights for study of foreign body reaction process in general.

Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

PubMed

Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

2017-01-01

Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

Efficient rejection-based simulation of biochemical reactions with stochastic noise and delays

NASA Astrophysics Data System (ADS)

Thanh, Vo Hong; Priami, Corrado; Zunino, Roberto

2014-10-01

We propose a new exact stochastic rejection-based simulation algorithm for biochemical reactions and extend it to systems with delays. Our algorithm accelerates the simulation by pre-computing reaction propensity bounds to select the next reaction to perform. Exploiting such bounds, we are able to avoid recomputing propensities every time a (delayed) reaction is initiated or finished, as is typically necessary in standard approaches. Propensity updates in our approach are still performed, but only infrequently and limited for a small number of reactions, saving computation time and without sacrificing exactness. We evaluate the performance improvement of our algorithm by experimenting with concrete biological models.

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

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

Li, Minjing; Qian, Wei-jun; Gao, Yuqian

The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes asmore » time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates« less

A multi-species reactive transport model to estimate biogeochemical rates based on single-well push-pull test data

NASA Astrophysics Data System (ADS)

Phanikumar, Mantha S.; McGuire, Jennifer T.

2010-08-01

Push-pull tests are a popular technique to investigate various aquifer properties and microbial reaction kinetics in situ. Most previous studies have interpreted push-pull test data using approximate analytical solutions to estimate (generally first-order) reaction rate coefficients. Though useful, these analytical solutions may not be able to describe important complexities in rate data. This paper reports the development of a multi-species, radial coordinate numerical model (PPTEST) that includes the effects of sorption, reaction lag time and arbitrary reaction order kinetics to estimate rates in the presence of mixing interfaces such as those created between injected "push" water and native aquifer water. The model has the ability to describe an arbitrary number of species and user-defined reaction rate expressions including Monod/Michelis-Menten kinetics. The FORTRAN code uses a finite-difference numerical model based on the advection-dispersion-reaction equation and was developed to describe the radial flow and transport during a push-pull test. The accuracy of the numerical solutions was assessed by comparing numerical results with analytical solutions and field data available in the literature. The model described the observed breakthrough data for tracers (chloride and iodide-131) and reactive components (sulfate and strontium-85) well and was found to be useful for testing hypotheses related to the complex set of processes operating near mixing interfaces.

A coupled mechanical-chemical model for reflecting the influence of stress on oxidation reactions in thermal barrier coating

NASA Astrophysics Data System (ADS)

Chen, Lin; Yueming, Li

2018-06-01

In this paper, a coupled mechanical-chemical model is established based on the thermodynamic framework, in which the contribution of chemical expansion to free energy is introduced. The stress-dependent chemical potential equilibrium at the gas-solid interface and the stress gradient-dependent diffusion equation as well as a so-called generalized force which is conjugate to the oxidation rate are derived from the proposed model, which could reflect the influence of stresses on the oxidation reaction. Based on the proposed coupled mechanical-chemical model, a user element subroutine is developed in ABAQUS. The numerical simulation of the high temperature oxidation in the thermal barrier coating is carried out to verify the accuracy of the proposed model, and then the influence of stresses on the oxidation reaction is investigated. In thermally grown oxide, the considerable stresses would be induced by permanent volumetric swelling during the oxidation. The stresses play an important role in the chemical potential equilibrium at the gas-solid interface and strongly affect the oxidation reaction. The gradient of the stresses, however, only occurs in the extremely thin oxidation front layer, which plays a very limited role in the oxidation reaction. The generalized force could be divided into the stress-dependent and the stress-independent parts. Comparing with the stress-independent part, the stress-dependent part is smaller, which has little influence on oxidation reaction.

Assessing College Students' Understanding of Acid Base Chemistry Concepts

ERIC Educational Resources Information Center

Wan, Yanjun Jean

2014-01-01

Typically most college curricula include three acid base models: Arrhenius', Bronsted-Lowry's, and Lewis'. Although Lewis' acid base model is generally thought to be the most sophisticated among these three models, and can be further applied in reaction mechanisms, most general chemistry curricula either do not include Lewis' acid base model, or…

Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

PubMed Central

Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

2015-01-01

There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes. PMID:25806041

Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

DOE PAGES

Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; ...

2015-03-10

There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions andmore » possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.« less

The role of Fenton reaction in ROS-induced toxicity underlying atherosclerosis - modeled and analyzed using a Petri net-based approach.

PubMed

Formanowicz, Dorota; Radom, Marcin; Rybarczyk, Agnieszka; Formanowicz, Piotr

2018-03-01

The superoxide-driven Fenton reaction plays an important role in the transformation of poorly reactive radicals into highly reactive ones. These highly reactive species (ROS), especially hydroxyl radicals can lead to many disturbances contributing to the endothelial dysfunction being a starting point for atherosclerosis. Although, iron has been identified as a possible culprit influencing formation of ROS, its significance in this process is still debatable. To better understand this phenomenon, the influence of blockade of Fenton reaction in a proposed Petri net-based model of the selected aspects of the iron ROS-induced toxicity in atherosclerosis has been evaluated. As a result of the blockade of iron ions formation in the model, even up to 70% of the paths leading to the progression of atherosclerosis in this model has been blocked. In addition, after adding to the model, the blockade of the lipids peroxidation paths, progression of atherosclerotic plaque has been not observed. This allowed to conclude that the superoxide-driven Fenton reaction plays a significant role in the atherosclerosis. Copyright © 2018 Elsevier B.V. All rights reserved.

PEaCH4 v.2.0: A modelling platform to predict early diagenetic processes in marine sediments with a focus on biogenic methane - Case study: Offshore Namibia

NASA Astrophysics Data System (ADS)

Arning, Esther T.; Häußler, Steffen; van Berk, Wolfgang; Schulz, Hans-Martin

2016-07-01

The modelling of early diagenetic processes in marine sediments is of interest in marine science, and in the oil and gas industry, here, especially with respect to methane occurrence and gas hydrate formation as resources. Early diagenesis in marine sediments evolves from a complex web of intertwining (bio)geochemical reactions. It comprises microbially catalysed reactions and inorganic mineral-water-gas interactions. A model that will describe and consider all of these reactions has to be complex. However, it should be user-friendly, as well as to be applicable for a broad community and not only for experts in the field of marine chemistry. The presented modelling platform PeaCH4 v.2.0 combines both aspects, and is Microsoft Excel©-based. The modelling tool is PHREEQC (version 2), a computer programme for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations. The conceptual PEaCH4 model is based on the conversion of sediment-bound degradable organic matter. PEaCH4 v.2.0 was developed to quantify and predict early diagenetic processes in marine sediments with the focus on biogenic methane formation and its phase behaviour, and allows carbon mass balancing. In regard to the irreversible degradation of organic matter, it comprises a "reaction model" and a "kinetic model" to predict methane formation. Both approaches differ in their calculations and outputs as the "kinetic model" considers the modelling time to integrate temperature dependent biogenic methane formation in its calculations, whereas the "reaction model" simply relies on default organic matter degradation. With regard to the inorganic mineral-water-gas interactions, which are triggered by irreversible degradation of organic matter, PEaCH4 v.2.0 is based on chemical equilibrium thermodynamics, appropriate mass-action laws, and their temperature dependent equilibrium constants. The programme is exemplarily presented with the example of upwelling sediments off Namibia, ODP Leg 175, Site 1082. The application demonstrates that the modelling platform PEaCH4 v.2.0 provides a user-friendly, but complex scientific tool that delivers retraceable information about early diagenetic processes and products in marine sediments.

Birth-jump processes and application to forest fire spotting.

PubMed

Hillen, T; Greese, B; Martin, J; de Vries, G

2015-01-01

Birth-jump models are designed to describe population models for which growth and spatial spread cannot be decoupled. A birth-jump model is a nonlinear integro-differential equation. We present two different derivations of this equation, one based on a random walk approach and the other based on a two-compartmental reaction-diffusion model. In the case that the redistribution kernels are highly concentrated, we show that the integro-differential equation can be approximated by a reaction-diffusion equation, in which the proliferation rate contributes to both the diffusion term and the reaction term. We completely solve the corresponding critical domain size problem and the minimal wave speed problem. Birth-jump models can be applied in many areas in mathematical biology. We highlight an application of our results in the context of forest fire spread through spotting. We show that spotting increases the invasion speed of a forest fire front.

Confining Domains Lead to Reaction Bursts: Reaction Kinetics in the Plasma Membrane

PubMed Central

Kalay, Ziya; Fujiwara, Takahiro K.; Kusumi, Akihiro

2012-01-01

Confinement of molecules in specific small volumes and areas within a cell is likely to be a general strategy that is developed during evolution for regulating the interactions and functions of biomolecules. The cellular plasma membrane, which is the outermost membrane that surrounds the entire cell, was considered to be a continuous two-dimensional liquid, but it is becoming clear that it consists of numerous nano-meso-scale domains with various lifetimes, such as raft domains and cytoskeleton-induced compartments, and membrane molecules are dynamically trapped in these domains. In this article, we give a theoretical account on the effects of molecular confinement on reversible bimolecular reactions in a partitioned surface such as the plasma membrane. By performing simulations based on a lattice-based model of diffusion and reaction, we found that in the presence of membrane partitioning, bimolecular reactions that occur in each compartment proceed in bursts during which the reaction rate is sharply and briefly increased even though the asymptotic reaction rate remains the same. We characterized the time between reaction bursts and the burst amplitude as a function of the model parameters, and discussed the biological significance of the reaction bursts in the presence of strong inhibitor activity. PMID:22479350

Predictive Finite Rate Model for Oxygen-Carbon Interactions at High Temperature

NASA Astrophysics Data System (ADS)

Poovathingal, Savio

An oxidation model for carbon surfaces is developed to predict ablation rates for carbon heat shields used in hypersonic vehicles. Unlike existing empirical models, the approach used here was to probe gas-surface interactions individually and then based on an understanding of the relevant fundamental processes, build a predictive model that would be accurate over a wide range of pressures and temperatures, and even microstructures. Initially, molecular dynamics was used to understand the oxidation processes on the surface. The molecular dynamics simulations were compared to molecular beam experiments and good qualitative agreement was observed. The simulations reproduced cylindrical pitting observed in the experiments where oxidation was rapid and primarily occurred around a defect. However, the studies were limited to small systems at low temperatures and could simulate time scales only of the order of nanoseconds. Molecular beam experiments at high surface temperature indicated that a majority of surface reaction products were produced through thermal mechanisms. Since the reactions were thermal, they occurred over long time scales which were computationally prohibitive for molecular dynamics to simulate. The experiments provided detailed dynamical data on the scattering of O, O2, CO, and CO2 and it was found that the data from molecular beam experiments could be used directly to build a model. The data was initially used to deduce surface reaction probabilities at 800 K. The reaction probabilities were then incorporated into the direct simulation Monte Carlo (DSMC) method. Simulations were performed where the microstructure was resolved and dissociated oxygen convected and diffused towards it. For a gas-surface temperature of 800 K, it was found that despite CO being the dominant surface reaction product, a gas-phase reaction forms significant CO2 within the microstructure region. It was also found that surface area did not play any role in concentration of reaction products because the reaction probabilities were in the diffusion dominant regime. The molecular beam data at different surface temperatures was then used to build a finite rate model. Each reaction mechanism and all rate parameters of the new model were determined individually based on the molecular beam data. Despite the experiments being performed at near vacuum conditions, the finite rate model developed using the data could be used at pressures and temperatures relevant to hypersonic conditions. The new model was implemented in a computational fluid dynamics (CFD) solver and flow over a hypersonic vehicle was simulated. The new model predicted similar overall mass loss rates compared to existing models, however, the individual species production rates were completely different. The most notable difference was that the new model (based on molecular beam data) predicts CO as the oxidation reaction product with virtually no CO2 production, whereas existing models predict the exact opposite trend. CO being the dominant oxidation product is consistent with recent high enthalpy wind tunnel experiments. The discovery that measurements taken in molecular beam facilities are able to determine individual reaction mechanisms, including dependence on surface coverage, opens up an entirely new way of constructing ablation models.

Modeling and simulation of pressure waves generated by nano-thermite reactions

NASA Astrophysics Data System (ADS)

Martirosyan, Karen S.; Zyskin, Maxim; Jenkins, Charles M.; (Yuki) Horie, Yasuyuki

2012-11-01

This paper reports the modeling of pressure waves from the explosive reaction of nano-thermites consisting of mixtures of nanosized aluminum and oxidizer granules. Such nanostructured thermites have higher energy density (up to 26 kJ/cm3) and can generate a transient pressure pulse four times larger than that from trinitrotoluene (TNT) based on volume equivalence. A plausible explanation for the high pressure generation is that the reaction times are much shorter than the time for a shock wave to propagate away from the reagents region so that all the reaction energy is dumped into the gaseous products almost instantaneously and thereby a strong shock wave is generated. The goal of the modeling is to characterize the gas dynamic behavior for thermite reactions in a cylindrical reaction chamber and to model the experimentally measured pressure histories. To simplify the details of the initial stage of the explosive reaction, it is assumed that the reaction generates a one dimensional shock wave into an air-filled cylinder and propagates down the tube in a self-similar mode. Experimental data for Al/Bi2O3 mixtures were used to validate the model with attention focused on the ratio of specific heats and the drag coefficient. Model predictions are in good agreement with the measured pressure histories.

Versatile fusion source integrator AFSI for fast ion and neutron studies in fusion devices

NASA Astrophysics Data System (ADS)

Sirén, Paula; Varje, Jari; Äkäslompolo, Simppa; Asunta, Otto; Giroud, Carine; Kurki-Suonio, Taina; Weisen, Henri; JET Contributors, The

2018-01-01

ASCOT Fusion Source Integrator AFSI, an efficient tool for calculating fusion reaction rates and characterizing the fusion products, based on arbitrary reactant distributions, has been developed and is reported in this paper. Calculation of reactor-relevant D-D, D-T and D-3He fusion reactions has been implemented based on the Bosch-Hale fusion cross sections. The reactions can be calculated between arbitrary particle populations, including Maxwellian thermal particles and minority energetic particles. Reaction rate profiles, energy spectra and full 4D phase space distributions can be calculated for the non-isotropic reaction products. The code is especially suitable for integrated modelling in self-consistent plasma physics simulations as well as in the Serpent neutronics calculation chain. Validation of the model has been performed for neutron measurements at the JET tokamak and the code has been applied to predictive simulations in ITER.

Simulation of unsteady flows by the DSMC macroscopic chemistry method

NASA Astrophysics Data System (ADS)

Goldsworthy, Mark; Macrossan, Michael; Abdel-jawad, Madhat

2009-03-01

In the Direct Simulation Monte-Carlo (DSMC) method, a combination of statistical and deterministic procedures applied to a finite number of 'simulator' particles are used to model rarefied gas-kinetic processes. In the macroscopic chemistry method (MCM) for DSMC, chemical reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell, not just those selected for collisions, is used to determine a reaction rate coefficient for that cell. Unlike collision-based methods, MCM can be used with any viscosity or non-reacting collision models and any non-reacting energy exchange models. It can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies. MCM has been previously validated for steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation. Close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature, density and species mole fractions, as well as for the accumulated number of net reactions per cell.

Predictive modeling of surimi cake shelf life at different storage temperatures

NASA Astrophysics Data System (ADS)

Wang, Yatong; Hou, Yanhua; Wang, Quanfu; Cui, Bingqing; Zhang, Xiangyu; Li, Xuepeng; Li, Yujin; Liu, Yuanping

2017-04-01

The Arrhenius model of the shelf life prediction which based on the TBARS index was established in this study. The results showed that the significant changed of AV, POV, COV and TBARS with temperature increased, and the reaction rate constants k was obtained by the first order reaction kinetics model. Then the secondary model fitting was based on the Arrhenius equation. There was the optimal fitting accuracy of TBARS in the first and the secondary model fitting (R2≥0.95). The verification test indicated that the relative error between the shelf life model prediction value and actual value was within ±10%, suggesting the model could predict the shelf life of surimi cake.

Model validation of simple-graph representations of metabolism

PubMed Central

Holme, Petter

2009-01-01

The large-scale properties of chemical reaction systems, such as metabolism, can be studied with graph-based methods. To do this, one needs to reduce the information, lists of chemical reactions, available in databases. Even for the simplest type of graph representation, this reduction can be done in several ways. We investigate different simple network representations by testing how well they encode information about one biologically important network structure—network modularity (the propensity for edges to be clustered into dense groups that are sparsely connected between each other). To achieve this goal, we design a model of reaction systems where network modularity can be controlled and measure how well the reduction to simple graphs captures the modular structure of the model reaction system. We find that the network types that best capture the modular structure of the reaction system are substrate–product networks (where substrates are linked to products of a reaction) and substance networks (with edges between all substances participating in a reaction). Furthermore, we argue that the proposed model for reaction systems with tunable clustering is a general framework for studies of how reaction systems are affected by modularity. To this end, we investigate statistical properties of the model and find, among other things, that it recreates correlations between degree and mass of the molecules. PMID:19158012

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

Bandyopadhyay, S.; Chowdhury, R.; Biswas, G.K.

A mathematical model based on the mechanistic approach to the reaction kinetics of pyrolysis reactions and the realistic analysis of the interaction between simultaneous heat and mass transfer along with the chemical reaction has been developed for the design of smoothly running pyrolyzers. The model of a fixed-bed pyrolysis reactor has been proposed on the basis of the dimensionless parameters with respect to time and radial position. The variation of physical parameters like bed voidage, heat capacity, diffusivity, density, thermal conductivity, etc., on temperature and conversion has been taken into account. A deactivation model has also been incorporated to explainmore » the behavior of pyrolysis reactions at temperatures above 673 K. The simulated results of the model have been explained by comparing them with the experimental results.« less

Mimoza: web-based semantic zooming and navigation in metabolic networks.

PubMed

Zhukova, Anna; Sherman, David J

2015-02-26

The complexity of genome-scale metabolic models makes them quite difficult for human users to read, since they contain thousands of reactions that must be included for accurate computer simulation. Interestingly, hidden similarities between groups of reactions can be discovered, and generalized to reveal higher-level patterns. The web-based navigation system Mimoza allows a human expert to explore metabolic network models in a semantically zoomable manner: The most general view represents the compartments of the model; the next view shows the generalized versions of reactions and metabolites in each compartment; and the most detailed view represents the initial network with the generalization-based layout (where similar metabolites and reactions are placed next to each other). It allows a human expert to grasp the general structure of the network and analyze it in a top-down manner Mimoza can be installed standalone, or used on-line at http://mimoza.bordeaux.inria.fr/ , or installed in a Galaxy server for use in workflows. Mimoza views can be embedded in web pages, or downloaded as COMBINE archives.

Role of core excitation in (d ,p ) transfer reactions

NASA Astrophysics Data System (ADS)

Deltuva, A.; Ross, A.; Norvaišas, E.; Nunes, F. M.

2016-10-01

Background: Recent work found that core excitations can be important in extracting structure information from (d ,p ) reactions. Purpose: Our objective is to systematically explore the role of core excitation in (d ,p ) reactions and to understand the origin of the dynamical effects. Method: Based on the particle-rotor model of n +10Be , we generate a number of models with a range of separation energies (Sn=0.1 -5.0 MeV), while maintaining a significant core excited component. We then apply the latest extension of the momentum-space-based Faddeev method, including dynamical core excitation in the reaction mechanism to all orders, to the 10Be(d ,p )11Be -like reactions, and study the excitation effects for beam energies Ed=15 -90 MeV. Results: We study the resulting angular distributions and the differences between the spectroscopic factor that would be extracted from the cross sections, when including dynamical core excitation in the reaction, and that of the original structure model. We also explore how different partial waves affect the final cross section. Conclusions: Our results show a strong beam-energy dependence of the extracted spectroscopic factors that become smaller for intermediate beam energies. This dependence increases for loosely bound systems.

On the Green's function of the partially diffusion-controlled reversible ABCD reaction for radiation chemistry codes

NASA Astrophysics Data System (ADS)

Plante, Ianik; Devroye, Luc

2015-09-01

Several computer codes simulating chemical reactions in particles systems are based on the Green's functions of the diffusion equation (GFDE). Indeed, many types of chemical systems have been simulated using the exact GFDE, which has also become the gold standard for validating other theoretical models. In this work, a simulation algorithm is presented to sample the interparticle distance for partially diffusion-controlled reversible ABCD reaction. This algorithm is considered exact for 2-particles systems, is faster than conventional look-up tables and uses only a few kilobytes of memory. The simulation results obtained with this method are compared with those obtained with the independent reaction times (IRT) method. This work is part of our effort in developing models to understand the role of chemical reactions in the radiation effects on cells and tissues and may eventually be included in event-based models of space radiation risks. However, as many reactions are of this type in biological systems, this algorithm might play a pivotal role in future simulation programs not only in radiation chemistry, but also in the simulation of biochemical networks in time and space as well.

DFT-based prediction of reactivity of short-chain alcohol dehydrogenase

NASA Astrophysics Data System (ADS)

Stawoska, I.; Dudzik, A.; Wasylewski, M.; Jemioła-Rzemińska, M.; Skoczowski, A.; Strzałka, K.; Szaleniec, M.

2017-06-01

The reaction mechanism of ketone reduction by short chain dehydrogenase/reductase, ( S)-1-phenylethanol dehydrogenase from Aromatoleum aromaticum, was studied with DFT methods using cluster model approach. The characteristics of the hydride transfer process were investigated based on reaction of acetophenone and its eight structural analogues. The results confirmed previously suggested concomitant transfer of hydride from NADH to carbonyl C atom of the substrate with proton transfer from Tyr to carbonyl O atom. However, additional coupled motion of the next proton in the proton-relay system, between O2' ribose hydroxyl and Tyr154 was observed. The protonation of Lys158 seems not to affect the pKa of Tyr154, as the stable tyrosyl anion was observed only for a neutral Lys158 in the high pH model. The calculated reaction energies and reaction barriers were calibrated by calorimetric and kinetic methods. This allowed an excellent prediction of the reaction enthalpies (R2 = 0.93) and a good prediction of the reaction kinetics (R2 = 0.89). The observed relations were validated in prediction of log K eq obtained for real whole-cell reactor systems that modelled industrial synthesis of S-alcohols.

Attitude Model of a Reaction Wheel/Fixed Thruster Based Satellite Using Telemetry Data

DTIC Science & Technology

2005-03-01

xii ATTITUDE MODEL OF A REACTION WHEEL/ FIXED THRUSTER BASED SATELLITE USING TELEMETRY DATA I. Introduction As technology advances and spacecraft ...Earth’s horizon to determine spacecraft attitude . Sun sensors use the Sun to determine spacecraft attitude and are currently the attitude determination...wheels and the rate of rotation of the gimbal. Gravity gradient stabilization is a passive attitude control technique that is designed to use the

α -unbound levels in 34Ar from 36Ar(p ,t )34Ar reaction measurements and implications for the astrophysical 30S(α ,p )33Cl reaction rate

NASA Astrophysics Data System (ADS)

Long, A. M.; Adachi, T.; Beard, M.; Berg, G. P. A.; Couder, M.; deBoer, R. J.; Dozono, M.; Görres, J.; Fujita, H.; Fujita, Y.; Hatanaka, K.; Ishikawa, D.; Kubo, T.; Matsubara, H.; Namiki, Y.; O'Brien, S.; Ohkuma, Y.; Okamura, H.; Ong, H. J.; Patel, D.; Sakemi, Y.; Shimbara, Y.; Suzuki, S.; Talwar, R.; Tamii, A.; Volya, A.; Wakasa, T.; Watanabe, R.; Wiescher, M.; Yamada, R.; Zenihiro, J.

2018-05-01

The 30S(α ,p )33Cl reaction has been identified in several type-1 x-ray burst (XRB) sensitivity studies as a significant reaction within the α p process, possibly influencing not only the abundances of burst ashes but also the bolometric shape of double-peaked light curves coming from certain XRB systems. Given the dearth of experimental data on the 30S(α ,p ) 33Cl reaction at burst temperatures, we have performed high energy-resolution forward-angle 36Ar(p ,t )34Ar measurements in order to identify levels in 34Ar that could appear as resonances in the 30S(α ,p )33Cl reaction. Energies of levels identified in this work, along with model-based assumptions for spin assignments and spectroscopic factors, were then used to determine a rate for the 30S(α ,p )33Cl reaction based on a narrow-resonance formalism. The rates determined in this work are then compared with two standard Hauser-Feshbach model predictions over a range of XRB temperatures.

Simulations of an accelerator-based shielding experiment using the particle and heavy-ion transport code system PHITS.

PubMed

Sato, T; Sihver, L; Iwase, H; Nakashima, H; Niita, K

2005-01-01

In order to estimate the biological effects of HZE particles, an accurate knowledge of the physics of interaction of HZE particles is necessary. Since the heavy ion transport problem is a complex one, there is a need for both experimental and theoretical studies to develop accurate transport models. RIST and JAERI (Japan), GSI (Germany) and Chalmers (Sweden) are therefore currently developing and bench marking the General-Purpose Particle and Heavy-Ion Transport code System (PHITS), which is based on the NMTC and MCNP for nucleon/meson and neutron transport respectively, and the JAM hadron cascade model. PHITS uses JAERI Quantum Molecular Dynamics (JQMD) and the Generalized Evaporation Model (GEM) for calculations of fission and evaporation processes, a model developed at NASA Langley for calculation of total reaction cross sections, and the SPAR model for stopping power calculations. The future development of PHITS includes better parameterization in the JQMD model used for the nucleus-nucleus reactions, and improvement of the models used for calculating total reaction cross sections, and addition of routines for calculating elastic scattering of heavy ions, and inclusion of radioactivity and burn up processes. As a part of an extensive bench marking of PHITS, we have compared energy spectra of secondary neutrons created by reactions of HZE particles with different targets, with thicknesses ranging from <1 to 200 cm. We have also compared simulated and measured spatial, fluence and depth-dose distributions from different high energy heavy ion reactions. In this paper, we report simulations of an accelerator-based shielding experiment, in which a beam of 1 GeV/n Fe-ions has passed through thin slabs of polyethylene, Al, and Pb at an acceptance angle up to 4 degrees. c2005 Published by Elsevier Ltd on behalf of COSPAR.

Ethylene Decomposition Initiated by Ultraviolet Radiation from Low Pressure Mercury Lamps: Kinetics Model Prediction and Experimental Verification.

NASA Astrophysics Data System (ADS)

Jozwiak, Zbigniew Boguslaw

1995-01-01

Ethylene is an important auto-catalytic plant growth hormone. Removal of ethylene from the atmosphere surrounding ethylene-sensitive horticultural products may be very beneficial, allowing an extended period of storage and preventing or delaying the induction of disorders. Various ethylene removal techniques have been studied and put into practice. One technique is based on using low pressure mercury ultraviolet lamps as a source of photochemical energy to initiate chemical reactions that destroy ethylene. Although previous research showed that ethylene disappeared in experiments with mercury ultraviolet lamps, the reactions were not described and the actual cause of ethylene disappearance remained unknown. Proposed causes for this disappearance were the direct action of ultraviolet rays on ethylene, reaction of ethylene with ozone (which is formed when air or gas containing molecular oxygen is exposed to radiation emitted by this type of lamp), or reactions with atomic oxygen leading to formation of ozone. The objective of the present study was to determine the set of physical and chemical actions leading to the disappearance of ethylene from artificial storage atmosphere under conditions of ultraviolet irradiation. The goal was achieved by developing a static chemical model based on the physical properties of a commercially available ultraviolet lamp, the photochemistry of gases, and the kinetics of chemical reactions. The model was used to perform computer simulations predicting time dependent concentrations of chemical species included in the model. Development of the model was accompanied by the design of a reaction chamber used for experimental verification. The model provided a good prediction of the general behavior of the species involved in the chemistry under consideration; however the model predicted lower than measured rate of ethylene disappearance. Some reasons for the model -experiment disagreement are radiation intensity averaging, the experimental technique, mass transfer in the chamber, and incompleteness of the set of chemical reactions included in the model. The work is concluded with guidelines for development of a more complex mathematical model that includes elements of mass transfer inside the reaction chamber, and uses a three dimensional approach to distribute radiation from the low pressure mercury ultraviolet tube.

Simulating Metabolism with Statistical Thermodynamics

PubMed Central

Cannon, William R.

2014-01-01

New methods are needed for large scale modeling of metabolism that predict metabolite levels and characterize the thermodynamics of individual reactions and pathways. Current approaches use either kinetic simulations, which are difficult to extend to large networks of reactions because of the need for rate constants, or flux-based methods, which have a large number of feasible solutions because they are unconstrained by the law of mass action. This report presents an alternative modeling approach based on statistical thermodynamics. The principles of this approach are demonstrated using a simple set of coupled reactions, and then the system is characterized with respect to the changes in energy, entropy, free energy, and entropy production. Finally, the physical and biochemical insights that this approach can provide for metabolism are demonstrated by application to the tricarboxylic acid (TCA) cycle of Escherichia coli. The reaction and pathway thermodynamics are evaluated and predictions are made regarding changes in concentration of TCA cycle intermediates due to 10- and 100-fold changes in the ratio of NAD+:NADH concentrations. Finally, the assumptions and caveats regarding the use of statistical thermodynamics to model non-equilibrium reactions are discussed. PMID:25089525

Simulating metabolism with statistical thermodynamics.

PubMed

Cannon, William R

2014-01-01

New methods are needed for large scale modeling of metabolism that predict metabolite levels and characterize the thermodynamics of individual reactions and pathways. Current approaches use either kinetic simulations, which are difficult to extend to large networks of reactions because of the need for rate constants, or flux-based methods, which have a large number of feasible solutions because they are unconstrained by the law of mass action. This report presents an alternative modeling approach based on statistical thermodynamics. The principles of this approach are demonstrated using a simple set of coupled reactions, and then the system is characterized with respect to the changes in energy, entropy, free energy, and entropy production. Finally, the physical and biochemical insights that this approach can provide for metabolism are demonstrated by application to the tricarboxylic acid (TCA) cycle of Escherichia coli. The reaction and pathway thermodynamics are evaluated and predictions are made regarding changes in concentration of TCA cycle intermediates due to 10- and 100-fold changes in the ratio of NAD+:NADH concentrations. Finally, the assumptions and caveats regarding the use of statistical thermodynamics to model non-equilibrium reactions are discussed.

Efficient rejection-based simulation of biochemical reactions with stochastic noise and delays

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

Thanh, Vo Hong, E-mail: vo@cosbi.eu; Priami, Corrado, E-mail: priami@cosbi.eu; Department of Mathematics, University of Trento

2014-10-07

We propose a new exact stochastic rejection-based simulation algorithm for biochemical reactions and extend it to systems with delays. Our algorithm accelerates the simulation by pre-computing reaction propensity bounds to select the next reaction to perform. Exploiting such bounds, we are able to avoid recomputing propensities every time a (delayed) reaction is initiated or finished, as is typically necessary in standard approaches. Propensity updates in our approach are still performed, but only infrequently and limited for a small number of reactions, saving computation time and without sacrificing exactness. We evaluate the performance improvement of our algorithm by experimenting with concretemore » biological models.« less

Approaching mathematical model of the immune network based DNA Strand Displacement system.

PubMed

Mardian, Rizki; Sekiyama, Kosuke; Fukuda, Toshio

2013-12-01

One biggest obstacle in molecular programming is that there is still no direct method to compile any existed mathematical model into biochemical reaction in order to solve a computational problem. In this paper, the implementation of DNA Strand Displacement system based on nature-inspired computation is observed. By using the Immune Network Theory and Chemical Reaction Network, the compilation of DNA-based operation is defined and the formulation of its mathematical model is derived. Furthermore, the implementation on this system is compared with the conventional implementation by using silicon-based programming. From the obtained results, we can see a positive correlation between both. One possible application from this DNA-based model is for a decision making scheme of intelligent computer or molecular robot. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Intra-individual reaction time variability and all-cause mortality over 17 years: a community-based cohort study.

PubMed

Batterham, Philip J; Bunce, David; Mackinnon, Andrew J; Christensen, Helen

2014-01-01

very few studies have examined the association between intra-individual reaction time variability and subsequent mortality. Furthermore, the ability of simple measures of variability to predict mortality has not been compared with more complex measures. a prospective cohort study of 896 community-based Australian adults aged 70+ were interviewed up to four times from 1990 to 2002, with vital status assessed until June 2007. From this cohort, 770-790 participants were included in Cox proportional hazards regression models of survival. Vital status and time in study were used to conduct survival analyses. The mean reaction time and three measures of intra-individual reaction time variability were calculated separately across 20 trials of simple and choice reaction time tasks. Models were adjusted for a range of demographic, physical health and mental health measures. greater intra-individual simple reaction time variability, as assessed by the raw standard deviation (raw SD), coefficient of variation (CV) or the intra-individual standard deviation (ISD), was strongly associated with an increased hazard of all-cause mortality in adjusted Cox regression models. The mean reaction time had no significant association with mortality. intra-individual variability in simple reaction time appears to have a robust association with mortality over 17 years. Health professionals such as neuropsychologists may benefit in their detection of neuropathology by supplementing neuropsychiatric testing with the straightforward process of testing simple reaction time and calculating raw SD or CV.

Numerical modeling of particle generation from ozone reactions with human-worn clothing in indoor environments

NASA Astrophysics Data System (ADS)

Rai, Aakash C.; Lin, Chao-Hsin; Chen, Qingyan

2015-02-01

Ozone-terpene reactions are important sources of indoor ultrafine particles (UFPs), a potential health hazard for human beings. Humans themselves act as possible sites for ozone-initiated particle generation through reactions with squalene (a terpene) that is present in their skin, hair, and clothing. This investigation developed a numerical model to probe particle generation from ozone reactions with clothing worn by humans. The model was based on particle generation measured in an environmental chamber as well as physical formulations of particle nucleation, condensational growth, and deposition. In five out of the six test cases, the model was able to predict particle size distributions reasonably well. The failure in the remaining case demonstrated the fundamental limitations of nucleation models. The model that was developed was used to predict particle generation under various building and airliner cabin conditions. These predictions indicate that ozone reactions with human-worn clothing could be an important source of UFPs in densely occupied classrooms and airliner cabins. Those reactions could account for about 40% of the total UFPs measured on a Boeing 737-700 flight. The model predictions at this stage are indicative and should be improved further.

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.

Simulation of dual carbon-bromine stable isotope fractionation during 1,2-dibromoethane degradation.

PubMed

Jin, Biao; Nijenhuis, Ivonne; Rolle, Massimo

2018-06-01

We performed a model-based investigation to simultaneously predict the evolution of concentration, as well as stable carbon and bromine isotope fractionation during 1,2-dibromoethane (EDB, ethylene dibromide) transformation in a closed system. The modelling approach considers bond-cleavage mechanisms during different reactions and allows evaluating dual carbon-bromine isotopic signals for chemical and biotic reactions, including aerobic and anaerobic biological transformation, dibromoelimination by Zn(0) and alkaline hydrolysis. The proposed model allowed us to accurately simulate the evolution of concentrations and isotope data observed in a previous laboratory study and to successfully identify different reaction pathways. Furthermore, we illustrated the model capabilities in degradation scenarios involving complex reaction systems. Specifically, we examined (i) the case of sequential multistep transformation of EDB and the isotopic evolution of the parent compound, the intermediate and the reaction product and (ii) the case of parallel competing abiotic pathways of EDB transformation in alkaline solution.

The kinetics of thermal generation of flavour.

PubMed

Parker, Jane K

2013-01-01

Control and optimisation of flavour is the ultimate challenge for the food and flavour industry. The major route to flavour formation during thermal processing is the Maillard reaction, which is a complex cascade of interdependent reactions initiated by the reaction between a reducing sugar and an amino compound. The complexity of the reaction means that researchers turn to kinetic modelling in order to understand the control points of the reaction and to manipulate the flavour profile. Studies of the kinetics of flavour formation have developed over the past 30 years from single- response empirical models of binary aqueous systems to sophisticated multi-response models in food matrices, based on the underlying chemistry, with the power to predict the formation of some key aroma compounds. This paper discusses in detail the development of kinetic models of thermal generation of flavour and looks at the challenges involved in predicting flavour. Copyright © 2012 Society of Chemical Industry.

Efficiency of reactant site sampling in network-free simulation of rule-based models for biochemical systems

PubMed Central

Yang, Jin; Hlavacek, William S.

2011-01-01

Rule-based models, which are typically formulated to represent cell signaling systems, can now be simulated via various network-free simulation methods. In a network-free method, reaction rates are calculated for rules that characterize molecular interactions, and these rule rates, which each correspond to the cumulative rate of all reactions implied by a rule, are used to perform a stochastic simulation of reaction kinetics. Network-free methods, which can be viewed as generalizations of Gillespie’s method, are so named because these methods do not require that a list of individual reactions implied by a set of rules be explicitly generated, which is a requirement of other methods for simulating rule-based models. This requirement is impractical for rule sets that imply large reaction networks (i.e., long lists of individual reactions), as reaction network generation is expensive. Here, we compare the network-free simulation methods implemented in RuleMonkey and NFsim, general-purpose software tools for simulating rule-based models encoded in the BioNetGen language. The method implemented in NFsim uses rejection sampling to correct overestimates of rule rates, which introduces null events (i.e., time steps that do not change the state of the system being simulated). The method implemented in RuleMonkey uses iterative updates to track rule rates exactly, which avoids null events. To ensure a fair comparison of the two methods, we developed implementations of the rejection and rejection-free methods specific to a particular class of kinetic models for multivalent ligand-receptor interactions. These implementations were written with the intention of making them as much alike as possible, minimizing the contribution of irrelevant coding differences to efficiency differences. Simulation results show that performance of the rejection method is equal to or better than that of the rejection-free method over wide parameter ranges. However, when parameter values are such that ligand-induced aggregation of receptors yields a large connected receptor cluster, the rejection-free method is more efficient. PMID:21832806

Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

PubMed

Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

2011-03-25

The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The modeling system is designed in such a way that constraint-based models targeting different microorganisms or competing organism communities can be easily plugged into the system. Constraint-based modeling is very costly given the size of a genome-scale reaction network. To save computation time, a binary tree is traversed to examine the concentration and solution pool generated during the simulation in order to decide whether the constraint-based model should be called. We also show preliminary results from the integrated model including a comparison of the direct and indirect coupling approaches and evaluated the ability of the approach to simulate field experiment. Published by Elsevier B.V.

Application of global kinetic models to HMX beta-delta transition and cookoff processes.

PubMed

Wemhoff, Aaron P; Burnham, Alan K; Nichols, Albert L

2007-03-08

The reduction of the number of reactions in kinetic models for both the HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) beta-delta phase transition and thermal cookoff provides an attractive alternative to traditional multi-stage kinetic models due to reduced calibration effort requirements. In this study, we use the LLNL code ALE3D to provide calibrated kinetic parameters for a two-reaction bidirectional beta-delta HMX phase transition model based on Sandia instrumented thermal ignition (SITI) and scaled thermal explosion (STEX) temperature history curves, and a Prout-Tompkins cookoff model based on one-dimensional time to explosion (ODTX) data. Results show that the two-reaction bidirectional beta-delta transition model presented here agrees as well with STEX and SITI temperature history curves as a reversible four-reaction Arrhenius model yet requires an order of magnitude less computational effort. In addition, a single-reaction Prout-Tompkins model calibrated to ODTX data provides better agreement with ODTX data than a traditional multistep Arrhenius model and can contain up to 90% fewer chemistry-limited time steps for low-temperature ODTX simulations. Manual calibration methods for the Prout-Tompkins kinetics provide much better agreement with ODTX experimental data than parameters derived from differential scanning calorimetry (DSC) measurements at atmospheric pressure. The predicted surface temperature at explosion for STEX cookoff simulations is a weak function of the cookoff model used, and a reduction of up to 15% of chemistry-limited time steps can be achieved by neglecting the beta-delta transition for this type of simulation. Finally, the inclusion of the beta-delta transition model in the overall kinetics model can affect the predicted time to explosion by 1% for the traditional multistep Arrhenius approach, and up to 11% using a Prout-Tompkins cookoff model.

ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-10-22

Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of ReactionPredictor are available via the chemoinformatics portal http://cdb.ics.uci.edu/.

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

NASA Astrophysics Data System (ADS)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

Reaction of positronium with doped ions in silica-based glasses in the size determination of subnanometer structural open spaces

NASA Astrophysics Data System (ADS)

Inoue, K.; Kataoka, H.; Nagai, Y.; Hasegawa, M.; Kobayashi, Y.

2013-10-01

Positron annihilation spectroscopy is employed to estimate the size of subnanometer-scale open spaces in insulating materials. In most cases, the size is estimated from the lifetime of long-lived ortho-positronium (o-Ps) by pickoff annihilation using a simplified model. However, reactions of Ps with surrounding electrons other than the pickoff reaction, such as spin conversion or chemical reaction, could give a substantially underestimated size using the simplified model. In the present paper, we report that the size of the open spaces can be evaluated correctly by the angular correlation of positron annihilation radiation (ACAR) with a magnetic field using the spin-polarization effect on Ps formation, even if such reactions of Ps occur in the material. This method is applied to the subnanometer-scale structural open spaces of silica-based glass doped with Fe. We demonstrate the influence of the Ps reaction on size-estimation of the open spaces from the o-Ps lifetime. Furthermore, the type of reaction, whether spin conversion or chemical, is distinguished from the magnetic field dependence of the Ps self-annihilation component intensity in the ACAR spectra. The Ps reaction in silica-based glass doped with Fe is a chemical reaction (most likely oxidation) rather than spin conversion, with Fe ions. The chemical quenching rate with Fe ions is determined from the dependence of the o-Ps lifetime on the Fe content.

A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4.

PubMed

Dai, Zi-Ru; Ai, Chun-Zhi; Ge, Guang-Bo; He, Yu-Qi; Wu, Jing-Jing; Wang, Jia-Yue; Man, Hui-Zi; Jia, Yan; Yang, Ling

2015-06-30

Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s) on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s) and the site(s) of modification. The newly established model was applied to predict the metabolic site(s) of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s) of CYP3A4 on steroids with high predictive accuracy.

A New Publicly Available Chemical Query Language, CSRML, to support Chemotype Representations for Application to Data-Mining and Modeling

EPA Science Inventory

A new XML-based query language, CSRML, has been developed for representing chemical substructures, molecules, reaction rules, and reactions. CSRML queries are capable of integrating additional forms of information beyond the simple substructure (e.g., SMARTS) or reaction transfor...

Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling.

PubMed

Schaefer, C; Jansen, A P J

2013-02-07

We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature.

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

PubMed Central

Stover, Lori J.; Nair, Niketh S.; Faeder, James R.

2014-01-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This “network-free” approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of “partial network expansion” into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. PMID:24699269

Exact hybrid particle/population simulation of rule-based models of biochemical systems.

PubMed

Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R

2014-04-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility.

Neutrino-induced meson productions off nucleon at forward limit in nucleon resonance region

NASA Astrophysics Data System (ADS)

Nakamura, S. X.; Kamano, H.; Lee, T.-S. H.; Sato, T.

2015-05-01

We study forward neutrino-induced meson production off the nucleon in the resonance region. Our calculation is based on a dynamical coupled-channels (DCC) model that reasonably describes π(γ)N → πN, ηN, KΛ, KΣ data in the resonance region. We apply the PCAC hypothesis to the DCC model to relate the πN reaction amplitude to the forward neutrino reaction amplitude. In this way, we give a prediction for νN → πN, ππN, ηN, KΛ, KΣ reaction cross sections. The predicted νN → ππN, ηN, KΛ, KΣ cross sections are, for the first time, based on a model extensively tested by data. We compare our results with those from the Rein-Sehgal model that has been very often used in the existing Monte Carlo simulators for neutrino experiments. We find a significant difference between them.

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

Wemhoff, A P; Burnham, A K; Nichols III, A L

The reduction of the number of reactions in kinetic models for both the HMX beta-delta phase transition and thermal cookoff provides an attractive alternative to traditional multi-stage kinetic models due to reduced calibration effort requirements. In this study, we use the LLNL code ALE3D to provide calibrated kinetic parameters for a two-reaction bidirectional beta-delta HMX phase transition model based on Sandia Instrumented Thermal Ignition (SITI) and Scaled Thermal Explosion (STEX) temperature history curves, and a Prout-Tompkins cookoff model based on One-Dimensional Time to Explosion (ODTX) data. Results show that the two-reaction bidirectional beta-delta transition model presented here agrees as wellmore » with STEX and SITI temperature history curves as a reversible four-reaction Arrhenius model, yet requires an order of magnitude less computational effort. In addition, a single-reaction Prout-Tompkins model calibrated to ODTX data provides better agreement with ODTX data than a traditional multi-step Arrhenius model, and can contain up to 90% less chemistry-limited time steps for low-temperature ODTX simulations. Manual calibration methods for the Prout-Tompkins kinetics provide much better agreement with ODTX experimental data than parameters derived from Differential Scanning Calorimetry (DSC) measurements at atmospheric pressure. The predicted surface temperature at explosion for STEX cookoff simulations is a weak function of the cookoff model used, and a reduction of up to 15% of chemistry-limited time steps can be achieved by neglecting the beta-delta transition for this type of simulation. Finally, the inclusion of the beta-delta transition model in the overall kinetics model can affect the predicted time to explosion by 1% for the traditional multi-step Arrhenius approach, while up to 11% using a Prout-Tompkins cookoff model.« less

To address surface reaction network complexity using scaling relations machine learning and DFT calculations

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

Ulissi, Zachary W.; Medford, Andrew J.; Bligaard, Thomas

Surface reaction networks involving hydrocarbons exhibit enormous complexity with thousands of species and reactions for all but the very simplest of chemistries. We present a framework for optimization under uncertainty for heterogeneous catalysis reaction networks using surrogate models that are trained on the fly. The surrogate model is constructed by teaching a Gaussian process adsorption energies based on group additivity fingerprints, combined with transition-state scaling relations and a simple classifier for determining the rate-limiting step. The surrogate model is iteratively used to predict the most important reaction step to be calculated explicitly with computationally demanding electronic structure theory. Applying thesemore » methods to the reaction of syngas on rhodium(111), we identify the most likely reaction mechanism. Lastly, propagating uncertainty throughout this process yields the likelihood that the final mechanism is complete given measurements on only a subset of the entire network and uncertainty in the underlying density functional theory calculations.« less

To address surface reaction network complexity using scaling relations machine learning and DFT calculations

DOE PAGES

Ulissi, Zachary W.; Medford, Andrew J.; Bligaard, Thomas; ...

2017-03-06

Surface reaction networks involving hydrocarbons exhibit enormous complexity with thousands of species and reactions for all but the very simplest of chemistries. We present a framework for optimization under uncertainty for heterogeneous catalysis reaction networks using surrogate models that are trained on the fly. The surrogate model is constructed by teaching a Gaussian process adsorption energies based on group additivity fingerprints, combined with transition-state scaling relations and a simple classifier for determining the rate-limiting step. The surrogate model is iteratively used to predict the most important reaction step to be calculated explicitly with computationally demanding electronic structure theory. Applying thesemore » methods to the reaction of syngas on rhodium(111), we identify the most likely reaction mechanism. Lastly, propagating uncertainty throughout this process yields the likelihood that the final mechanism is complete given measurements on only a subset of the entire network and uncertainty in the underlying density functional theory calculations.« less

Implementation of a vibrationally linked chemical reaction model for DSMC

NASA Technical Reports Server (NTRS)

Carlson, A. B.; Bird, Graeme A.

1994-01-01

A new procedure closely linking dissociation and exchange reactions in air to the vibrational levels of the diatomic molecules has been implemented in both one- and two-dimensional versions of Direct Simulation Monte Carlo (DSMC) programs. The previous modeling of chemical reactions with DSMC was based on the continuum reaction rates for the various possible reactions. The new method is more closely related to the actual physics of dissociation and is more appropriate to the particle nature of DSMC. Two cases are presented: the relaxation to equilibrium of undissociated air initially at 10,000 K, and the axisymmetric calculation of shuttle forebody heating during reentry at 92.35 km and 7500 m/s. Although reaction rates are not used in determining the dissociations or exchange reactions, the new method produces rates which agree astonishingly well with the published rates derived from experiment. The results for gas properties and surface properties also agree well with the results produced by earlier DSMC models, equilibrium air calculations, and experiment.

Reduced Order Models for Reactions of Energetic Materials

NASA Astrophysics Data System (ADS)

Kober, Edward

The formulation of reduced order models for the reaction chemistry of energetic materials under high pressures is needed for the development of mesoscale models in the areas of initiation, deflagration and detonation. Phenomenologically, 4-8 step models have been formulated from the analysis of cook-off data by analyzing the temperature rise of heated samples. Reactive molecular dynamics simulations have been used to simulate many of these processes, but reducing the results of those simulations to simple models has not been achieved. Typically, these efforts have focused on identifying molecular species and detailing specific chemical reactions. An alternative approach is presented here that is based on identifying the coordination geometries of each atom in the simulation and tracking classes of reactions by correlated changes in these geometries. Here, every atom and type of reaction is documented for every time step; no information is lost from unsuccessful molecular identification. Principal Component Analysis methods can then be used to map out the effective chemical reaction steps. For HMX and TATB decompositions simulated with ReaxFF, 90% of the data can be explained by 4-6 steps, generating models similar to those from the cook-off analysis. By performing these simulations at a variety of temperatures and pressures, both the activation and reaction energies and volumes can then be extracted.

Investigation of nutrient feeding strategies in a countercurrent mixed-acid multi-staged fermentation: development of segregated-nitrogen model.

PubMed

Smith, Aaron D; Holtzapple, Mark T

2010-12-01

The MixAlco process is a biorefinery based on the production of carboxylic acids via mixed-culture fermentation. Nitrogen is essential for microbial growth and metabolism, and may exist in soluble (e.g., ammonia) or insoluble forms (e.g., cells). Understanding the dynamics of nitrogen flow in a countercurrent fermentation is necessary to develop control strategies to maximize performance. To estimate nitrogen concentration profiles in a four-stage fermentation train, a mass balance-based segregated-nitrogen model was developed, which uses separate balances for solid- and liquid-phase nitrogen with nitrogen reaction flux between phases assumed to be zero. Comparison of predictions with measured nitrogen profiles from five trains, each with a different nutrient contacting pattern, shows the segregated-nitrogen model captures basic behavior and is a reasonable tool for estimating nitrogen profiles. The segregated-nitrogen model may be used to (1) estimate optimal nitrogen loading patterns, (2) develop a reaction-based model, (3) understand influence of model inputs (e.g., operating parameters, feedstock properties, nutrient loading pattern) on the steady-state nitrogen profile, and (4) determine the direction of the nitrogen reaction flux between liquid and solid phases. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

PubMed

Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

2017-05-01

To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in amore » stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

DEPENDENCE OF X-RAY BURST MODELS ON NUCLEAR REACTION RATES

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

Cyburt, R. H.; Keek, L.; Schatz, H.

2016-10-20

X-ray bursts are thermonuclear flashes on the surface of accreting neutron stars, and reliable burst models are needed to interpret observations in terms of properties of the neutron star and the binary system. We investigate the dependence of X-ray burst models on uncertainties in (p, γ ), ( α , γ ), and ( α , p) nuclear reaction rates using fully self-consistent burst models that account for the feedbacks between changes in nuclear energy generation and changes in astrophysical conditions. A two-step approach first identified sensitive nuclear reaction rates in a single-zone model with ignition conditions chosen to matchmore » calculations with a state-of-the-art 1D multi-zone model based on the Kepler stellar evolution code. All relevant reaction rates on neutron-deficient isotopes up to mass 106 were individually varied by a factor of 100 up and down. Calculations of the 84 changes in reaction rate with the highest impact were then repeated in the 1D multi-zone model. We find a number of uncertain reaction rates that affect predictions of light curves and burst ashes significantly. The results provide insights into the nuclear processes that shape observables from X-ray bursts, and guidance for future nuclear physics work to reduce nuclear uncertainties in X-ray burst models.« less

Probabilistic, sediment-geochemical parameterisation of the groundwater compartment of the Netherlands for spatially distributed, reactive transport modelling

NASA Astrophysics Data System (ADS)

Janssen, Gijs; Gunnink, Jan; van Vliet, Marielle; Goldberg, Tanya; Griffioen, Jasper

2017-04-01

Pollution of groundwater aquifers with contaminants as nitrate is a common problem. Reactive transport models are useful to predict the fate of such contaminants and to characterise the efficiency of mitigating or preventive measures. Parameterisation of a groundwater transport model on reaction capacity is a necessary step during building the model. Two Dutch, national programs are combined to establish a methodology for building a probabilistic model on reaction capacity of the groundwater compartment at the national scale: the Geological Survey program and the NHI Netherlands Hydrological Instrument program. Reaction capacity is considered as a series of geochemical characteristics that control acid/base condition, redox condition and sorption capacity. Five primary reaction capacity variables are characterised: 1. pyrite, 2. non-pyrite, reactive iron (oxides, siderite and glauconite), 3. clay fraction, 4. organic matter and 5. Ca-carbonate. Important reaction capacity variables that are determined by more than one solid compound are also deduced: 1. potential reduction capacity (PRC) by pyrite and organic matter, 2. cation-exchange capacity (CEC) by organic matter and clay content, 3. carbonate buffering upon pyrite oxidation (CPBO) by carbonate and pyrite. Statistical properties of these variables are established based on c. 16,000 sediment geochemical analyses. The first tens of meters are characterised based on 25 regions using combinations of lithological class and geological formation as strata. Because of both less data and more geochemical uniformity, the deeper subsurface is characterised in a similar way based on 3 regions. The statistical data is used as input in an algoritm that probabilistically calculates the reaction capacity per grid cell. First, the cumulative frequency distribution (cfd) functions are calculated from the statistical data for the geochemical strata. Second, all voxel cells are classified into the geochemical strata. Third, the cfd functions are used to put random reaction capacity variables into the hydrological voxel model. Here, the distribution can be conditioned on two variables. Two important variables are clay content and depth. The first is valid because more dense data is available for clay content than for geochemical variables as pyrite and probabilistic, lithological models are also built at TNO Geological Survey. The second is important to account for locally different depths at which the redox cline between NO3-rich and Fe(II)-rich groundwater occurs within the first tens of meters of the subsurface. An extensive data-set of groundwater quality analyses is used to derive criteria for depth variability of the redox cline. The result is a unique algoritm in order to obtain heterogeneous geochemical reaction capacity models of the entire groundwater compartment of the Netherlands.

How are the Concepts and Theories of Acid Base Reactions Presented? Chemistry in Textbooks and as Presented by Teachers

NASA Astrophysics Data System (ADS)

Furió-Más, Carlos; Calatayud, María Luisa; Guisasola, Jenaro; Furió-Gómez, Cristina

2005-09-01

This paper investigates the views of science and scientific activity that can be found in chemistry textbooks and heard from teachers when acid base reactions are introduced to grade 12 and university chemistry students. First, the main macroscopic and microscopic conceptual models are developed. Second, we attempt to show how the existence of views of science in textbooks and of chemistry teachers contributes to an impoverished image of chemistry. A varied design has been elaborated to analyse some epistemological deficiencies in teaching acid base reactions. Textbooks have been analysed and teachers have been interviewed. The results obtained show that the teaching process does not emphasize the macroscopic presentation of acids and bases. Macroscopic and microscopic conceptual models involved in the explanation of acid base processes are mixed in textbooks and by teachers. Furthermore, the non-problematic introduction of concepts, such as the hydrolysis concept, and the linear, cumulative view of acid base theories (Arrhenius and Brönsted) were detected.

An electromechanical based deformable model for soft tissue simulation.

PubMed

Zhong, Yongmin; Shirinzadeh, Bijan; Smith, Julian; Gu, Chengfan

2009-11-01

Soft tissue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues. Soft tissue deformation is formulated as a reaction-diffusion process coupled with a mechanical load. The mechanical load applied to a soft tissue to cause a deformation is incorporated into the reaction-diffusion system, and consequently distributed among mass points of the soft tissue. Reaction-diffusion of mechanical load and non-rigid mechanics of motion are combined to govern the simulation dynamics of soft tissue deformation. An improved reaction-diffusion model is developed to describe the distribution of the mechanical load in soft tissues. A three-layer artificial cellular neural network is constructed to solve the reaction-diffusion model for real-time simulation of soft tissue deformation. A gradient based method is established to derive internal forces from the distribution of the mechanical load. Integration with a haptic device has also been achieved to simulate soft tissue deformation with haptic feedback. The proposed methodology does not only predict the typical behaviours of living tissues, but it also accepts both local and large-range deformations. It also accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients.

Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

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

Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas

The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) modelmore » and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis ( 13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content.« less

Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

DOE PAGES

Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas; ...

2014-12-19

The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) modelmore » and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis ( 13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content.« less

Role of core excitation in ( d , p ) transfer reactions

DOE PAGES

Deltuva, A.; Ross, A.; Norvaišas, E.; ...

2016-10-24

In our recent work we found that core excitations can be important in extracting structure information from (d,p) reactions. Our objective is to systematically explore the role of core excitation in (d,p) reactions and to understand the origin of the dynamical effects. Based on the particle-rotor model of n+Be 10, we generate a number of models with a range of separation energies (S n=0.1–5.0 MeV), while maintaining a significant core excited component. We then apply the latest extension of the momentum-space-based Faddeev method, including dynamical core excitation in the reaction mechanism to all orders, to the Be 10(d,p)Be 11-like reactions,more » and study the excitation effects for beam energies E d=15–90 MeV. We study the resulting angular distributions and the differences between the spectroscopic factor that would be extracted from the cross sections, when including dynamical core excitation in the reaction, and that of the original structure model. We also explore how different partial waves affect the final cross section. Our results show a strong beam-energy dependence of the extracted spectroscopic factors that become smaller for intermediate beam energies. Finally, this dependence increases for loosely bound systems.« less

Influence of reaction-induced fracturing on serpentinisation rate

NASA Astrophysics Data System (ADS)

Malvoisin, B.; Brantut, N.; Kaczmarek, M. A.

2017-12-01

The alteration of mantle rocks at mid-ocean ridges (i.e. serpentinisation) can lead to a solid volume increase responsible for stress build-up and cracking during reaction (reaction-induced fracturing). This mechanism has been proposed to play a key role for maintaining fluid pathways during reaction. However, its impact on the reaction rate is not yet quantified. We propose here a micromechanical model to quantify the influence of the crystallisation pressure generated during serpentine precipitation on crack propagation in olivine. This model is then coupled to a simple geometrical model to calculate the generation of reactive surface area during grain splitting, and thus bulk reaction rate. The model is able to reproduce experimental kinetic data as well as the mesh texture observed in natural samples. The model results are compared to olivine grain size distribution in serpentinised peridotites from the Marum ophiolite and the Papuan ultramafic belt (Papuan New Guinea). The observations and the model both indicate a decrease of the mean grain size by one order of magnitude as the reaction progresses from 5 to 40 %. Based on this good agreement, we use our model to predict that cracking reduces the characteristic time of serpentinisation by one order of magnitude, down to values comprised between 10 and 1,000 yr. The peak serpentinisation is also shifted 4 km above the previous predictions due to effective pressure increase with depth.

Reacting Chemistry Based Burn Model for Explosive Hydrocodes

NASA Astrophysics Data System (ADS)

Schwaab, Matthew; Greendyke, Robert; Steward, Bryan

2017-06-01

Currently, in hydrocodes designed to simulate explosive material undergoing shock-induced ignition, the state of the art is to use one of numerous reaction burn rate models. These burn models are designed to estimate the bulk chemical reaction rate. Unfortunately, these models are largely based on empirical data and must be recalibrated for every new material being simulated. We propose that the use of an equilibrium Arrhenius rate reacting chemistry model in place of these empirically derived burn models will improve the accuracy for these computational codes. Such models have been successfully used in codes simulating the flow physics around hypersonic vehicles. A reacting chemistry model of this form was developed for the cyclic nitramine RDX by the Naval Research Laboratory (NRL). Initial implementation of this chemistry based burn model has been conducted on the Air Force Research Laboratory's MPEXS multi-phase continuum hydrocode. In its present form, the burn rate is based on the destruction rate of RDX from NRL's chemistry model. Early results using the chemistry based burn model show promise in capturing deflagration to detonation features more accurately in continuum hydrocodes than previously achieved using empirically derived burn models.

Spallation reactions: A successful interplay between modeling and applications

NASA Astrophysics Data System (ADS)

David, J.-C.

2015-06-01

The spallation reactions are a type of nuclear reaction which occur in space by interaction of the cosmic rays with interstellar bodies. The first spallation reactions induced with an accelerator took place in 1947 at the Berkeley cyclotron (University of California) with 200MeV deuterons and 400MeV alpha beams. They highlighted the multiple emission of neutrons and charged particles and the production of a large number of residual nuclei far different from the target nuclei. In the same year, R. Serber described the reaction in two steps: a first and fast one with high-energy particle emission leading to an excited remnant nucleus, and a second one, much slower, the de-excitation of the remnant. In 2010 IAEA organized a workshop to present the results of the most widely used spallation codes within a benchmark of spallation models. If one of the goals was to understand the deficiencies, if any, in each code, one remarkable outcome points out the overall high-quality level of some models and so the great improvements achieved since Serber. Particle transport codes can then rely on such spallation models to treat the reactions between a light particle and an atomic nucleus with energies spanning from few tens of MeV up to some GeV. An overview of the spallation reactions modeling is presented in order to point out the incomparable contribution of models based on basic physics to numerous applications where such reactions occur. Validations or benchmarks, which are necessary steps in the improvement process, are also addressed, as well as the potential future domains of development. Spallation reactions modeling is a representative case of continuous studies aiming at understanding a reaction mechanism and which end up in a powerful tool.

Quantum chemical modeling of enzymatic reactions: the case of 4-oxalocrotonate tautomerase.

PubMed

Sevastik, Robin; Himo, Fahmi

2007-12-01

The reaction mechanism of 4-oxalocrotonate tautomerase (4-OT) is studied using the density functional theory method B3LYP. This enzyme catalyzes the isomerisation of unconjugated alpha-keto acids to their conjugated isomers. Two different quantum chemical models of the active site are devised and the potential energy curves for the reaction are computed. The calculations support the proposed reaction mechanism in which Pro-1 acts as a base to shuttle a proton from the C3 to the C5 position of the substrate. The first step (proton transfer from C3 to proline) is shown to be the rate-limiting step. The energy of the charge-separated intermediate (protonated proline-deprotonated substrate) is calculated to be quite low, in accordance with measured pKa values. The results of the two models are used to evaluate the methodology employed in modeling enzyme active sites using quantum chemical cluster models.

Calculation and analysis of cross-sections for p+184W reactions up to 200 MeV

NASA Astrophysics Data System (ADS)

Sun, Jian-Ping; Zhang, Zheng-Jun; Han, Yin-Lu

2015-08-01

A set of optimal proton optical potential parameters for p+ 184W reactions are obtained at incident proton energy up to 250 MeV. Based on these parameters, the reaction cross-sections, elastic scattering angular distributions, energy spectra and double differential cross sections of proton-induced reactions on 184W are calculated and analyzed by using theoretical models which integrate the optical model, distorted Born wave approximation theory, intra-nuclear cascade model, exciton model, Hauser-Feshbach theory and evaporation model. The calculated results are compared with existing experimental data and good agreement is achieved. Supported by National Basic Research Program of China, Technology Research of Accelerator Driven Sub-critical System for Nuclear Waste Transmutation (2007CB209903) and Strategic Priority Research Program of Chinese Academy of Sciences, Thorium Molten Salt Reactor Nuclear Energy System (XDA02010100)

Aromatic sulfonation with sulfur trioxide: mechanism and kinetic model.

PubMed

Moors, Samuel L C; Deraet, Xavier; Van Assche, Guy; Geerlings, Paul; De Proft, Frank

2017-01-01

Electrophilic aromatic sulfonation of benzene with sulfur trioxide is studied with ab initio molecular dynamics simulations in gas phase, and in explicit noncomplexing (CCl 3 F) and complexing (CH 3 NO 2 ) solvent models. We investigate different possible reaction pathways, the number of SO 3 molecules participating in the reaction, and the influence of the solvent. Our simulations confirm the existence of a low-energy concerted pathway with formation of a cyclic transition state with two SO 3 molecules. Based on the simulation results, we propose a sequence of elementary reaction steps and a kinetic model compatible with experimental data. Furthermore, a new alternative reaction pathway is proposed in complexing solvent, involving two SO 3 and one CH 3 NO 2 .

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

NASA Astrophysics Data System (ADS)

Kim, Changho; Nonaka, Andy; Bell, John B.; Garcia, Alejandro L.; Donev, Aleksandar

2017-03-01

We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules, to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. By comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

DOE PAGES

Kim, Changho; Nonaka, Andy; Bell, John B.; ...

2017-03-24

Here, we develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules,more » to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. Furthermore, by comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.« less

Exclusive data-based modeling of neutron-nuclear reactions below 20 MeV

NASA Astrophysics Data System (ADS)

Savin, Dmitry; Kosov, Mikhail

2017-09-01

We are developing CHIPS-TPT physics library for exclusive simulation of neutron-nuclear reactions below 20 MeV. Exclusive modeling reproduces each separate scattering and thus requires conservation of energy, momentum and quantum numbers in each reaction. Inclusive modeling reproduces only selected values while averaging over the others and imposes no such constraints. Therefore the exclusive modeling allows to simulate additional quantities like secondary particle correlations and gamma-lines broadening and avoid artificial fluctuations. CHIPS-TPT is based on the formerly included in Geant4 CHIPS library, which follows the exclusive approach, and extends it to incident neutrons with the energy below 20 MeV. The NeutronHP model for neutrons below 20 MeV included in Geant4 follows the inclusive approach like the well known MCNP code. Unfortunately, the available data in this energy region is mostly presented in ENDF-6 format and semi-inclusive. Imposing additional constraints on secondary particles complicates modeling but also allows to detect inconsistencies in the input data and to avoid errors that may remain unnoticed in inclusive modeling.

Turing patterns and a stochastic individual-based model for predator-prey systems

NASA Astrophysics Data System (ADS)

Nagano, Seido

2012-02-01

Reaction-diffusion theory has played a very important role in the study of pattern formations in biology. However, a group of individuals is described by a single state variable representing population density in reaction-diffusion models and interaction between individuals can be included only phenomenologically. Recently, we have seamlessly combined individual-based models with elements of reaction-diffusion theory. To include animal migration in the scheme, we have adopted a relationship between the diffusion and the random numbers generated according to a two-dimensional bivariate normal distribution. Thus, we have observed the transition of population patterns from an extinction mode, a stable mode, or an oscillatory mode to the chaotic mode as the population growth rate increases. We show our phase diagram of predator-prey systems and discuss the microscopic mechanism for the stable lattice formation in detail.

Shock tube and chemical kinetic modeling study of the oxidation of 2,5-dimethylfuran.

PubMed

Sirjean, Baptiste; Fournet, René; Glaude, Pierre-Alexandre; Battin-Leclerc, Frédérique; Wang, Weijing; Oehlschlaeger, Matthew A

2013-02-21

A detailed kinetic model describing the oxidation of 2,5-dimethylfuran (DMF), a potential second-generation biofuel, is proposed. The kinetic model is based upon quantum chemical calculations for the initial DMF consumption reactions and important reactions of intermediates. The model is validated by comparison to new DMF shock tube ignition delay time measurements (over the temperature range 1300-1831 K and at nominal pressures of 1 and 4 bar) and the DMF pyrolysis speciation measurements of Lifshitz et al. [ J. Phys. Chem. A 1998 , 102 ( 52 ), 10655 - 10670 ]. Globally, modeling predictions are in good agreement with the considered experimental targets. In particular, ignition delay times are predicted well by the new model, with model-experiment deviations of at most a factor of 2, and DMF pyrolysis conversion is predicted well, to within experimental scatter of the Lifshitz et al. data. Additionally, comparisons of measured and model predicted pyrolysis speciation provides validation of theoretically calculated channels for the oxidation of DMF. Sensitivity and reaction flux analyses highlight important reactions as well as the primary reaction pathways responsible for the decomposition of DMF and formation and destruction of key intermediate and product species.

Quantum mechanical study of solvent effects in a prototype S{sub N}2 reaction in solution: Cl{sup −} attack on CH{sub 3}Cl

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

Kuechler, Erich R.; Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455-0431; York, Darrin M., E-mail: york@biomaps.rutgers.edu

2014-02-07

The nucleophilic attack of a chloride ion on methyl chloride is an important prototype S{sub N}2 reaction in organic chemistry that is known to be sensitive to the effects of the surrounding solvent. Herein, we develop a highly accurate Specific Reaction Parameter (SRP) model based on the Austin Model 1 Hamiltonian for chlorine to study the effects of solvation into an aqueous environment on the reaction mechanism. To accomplish this task, we apply high-level quantum mechanical calculations to study the reaction in the gas phase and combined quantum mechanical/molecular mechanical simulations with TIP3P and TIP4P-ew water models and the resultingmore » free energy profiles are compared with those determined from simulations using other fast semi-empirical quantum models. Both gas phase and solution results with the SRP model agree very well with experiment and provide insight into the specific role of solvent on the reaction coordinate. Overall, the newly parameterized SRP Hamiltonian is able to reproduce both the gas phase and solution phase barriers, suggesting it is an accurate and robust model for simulations in the aqueous phase at greatly reduced computational cost relative to comparably accurate ab initio and density functional models.« less

Quantum mechanical study of solvent effects in a prototype SN2 reaction in solution: Cl- attack on CH3Cl

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.; York, Darrin M.

2014-02-01

The nucleophilic attack of a chloride ion on methyl chloride is an important prototype SN2 reaction in organic chemistry that is known to be sensitive to the effects of the surrounding solvent. Herein, we develop a highly accurate Specific Reaction Parameter (SRP) model based on the Austin Model 1 Hamiltonian for chlorine to study the effects of solvation into an aqueous environment on the reaction mechanism. To accomplish this task, we apply high-level quantum mechanical calculations to study the reaction in the gas phase and combined quantum mechanical/molecular mechanical simulations with TIP3P and TIP4P-ew water models and the resulting free energy profiles are compared with those determined from simulations using other fast semi-empirical quantum models. Both gas phase and solution results with the SRP model agree very well with experiment and provide insight into the specific role of solvent on the reaction coordinate. Overall, the newly parameterized SRP Hamiltonian is able to reproduce both the gas phase and solution phase barriers, suggesting it is an accurate and robust model for simulations in the aqueous phase at greatly reduced computational cost relative to comparably accurate ab initio and density functional models.

Quantum mechanical study of solvent effects in a prototype SN2 reaction in solution: Cl- attack on CH3Cl.

PubMed

Kuechler, Erich R; York, Darrin M

2014-02-07

The nucleophilic attack of a chloride ion on methyl chloride is an important prototype SN2 reaction in organic chemistry that is known to be sensitive to the effects of the surrounding solvent. Herein, we develop a highly accurate Specific Reaction Parameter (SRP) model based on the Austin Model 1 Hamiltonian for chlorine to study the effects of solvation into an aqueous environment on the reaction mechanism. To accomplish this task, we apply high-level quantum mechanical calculations to study the reaction in the gas phase and combined quantum mechanical/molecular mechanical simulations with TIP3P and TIP4P-ew water models and the resulting free energy profiles are compared with those determined from simulations using other fast semi-empirical quantum models. Both gas phase and solution results with the SRP model agree very well with experiment and provide insight into the specific role of solvent on the reaction coordinate. Overall, the newly parameterized SRP Hamiltonian is able to reproduce both the gas phase and solution phase barriers, suggesting it is an accurate and robust model for simulations in the aqueous phase at greatly reduced computational cost relative to comparably accurate ab initio and density functional models.

Microkinetic modeling of H 2SO 4 formation on Pt based diesel oxidation catalysts

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

Sharma, Hom N.; Sun, Yunwei; Glascoe, Elizabeth A.

The presence of water vapor and sulfur oxides in diesel engine exhaust leads to the formation of sulfuric acid (H 2SO 4), which severely impacts the performance of Pt/Pd based emissions aftertreatment catalysts. In this study, a microkinetic model is developed to investigate the reaction pathways of H 2SO 4 formation on Pt based diesel oxidation catalysts (DOCs). The microkinetic model consists of 14 elementary step reactions (7 reversible pairs) and yields prediction in excellent agreement with data obtained from experiments at practically relevant sulfur oxides environment in engine exhaust. The model simulation utilizing a steady-state plug flow reactor demonstratesmore » that it matches experimental data in both kinetically and thermodynamically controlled regions. Results clearly show the negative impact of SO 3 on the SO 2 oxidation light-off temperature, consistent with experimental observations. A reaction pathway analysis shows that the primary pathway of sulfuric acid formation on Pt surface involves SO 2* oxidation to form SO 3* with the subsequent interaction of SO 3* with H 2O* to form H 2SO 4*.« less

Microkinetic modeling of H 2SO 4 formation on Pt based diesel oxidation catalysts

DOE PAGES

Sharma, Hom N.; Sun, Yunwei; Glascoe, Elizabeth A.

2017-08-10

The presence of water vapor and sulfur oxides in diesel engine exhaust leads to the formation of sulfuric acid (H 2SO 4), which severely impacts the performance of Pt/Pd based emissions aftertreatment catalysts. In this study, a microkinetic model is developed to investigate the reaction pathways of H 2SO 4 formation on Pt based diesel oxidation catalysts (DOCs). The microkinetic model consists of 14 elementary step reactions (7 reversible pairs) and yields prediction in excellent agreement with data obtained from experiments at practically relevant sulfur oxides environment in engine exhaust. The model simulation utilizing a steady-state plug flow reactor demonstratesmore » that it matches experimental data in both kinetically and thermodynamically controlled regions. Results clearly show the negative impact of SO 3 on the SO 2 oxidation light-off temperature, consistent with experimental observations. A reaction pathway analysis shows that the primary pathway of sulfuric acid formation on Pt surface involves SO 2* oxidation to form SO 3* with the subsequent interaction of SO 3* with H 2O* to form H 2SO 4*.« less

Bond Graph Modeling of Chemiosmotic Biomolecular Energy Transduction.

PubMed

Gawthrop, Peter J

2017-04-01

Engineering systems modeling and analysis based on the bond graph approach has been applied to biomolecular systems. In this context, the notion of a Faraday-equivalent chemical potential is introduced which allows chemical potential to be expressed in an analogous manner to electrical volts thus allowing engineering intuition to be applied to biomolecular systems. Redox reactions, and their representation by half-reactions, are key components of biological systems which involve both electrical and chemical domains. A bond graph interpretation of redox reactions is given which combines bond graphs with the Faraday-equivalent chemical potential. This approach is particularly relevant when the biomolecular system implements chemoelectrical transduction - for example chemiosmosis within the key metabolic pathway of mitochondria: oxidative phosphorylation. An alternative way of implementing computational modularity using bond graphs is introduced and used to give a physically based model of the mitochondrial electron transport chain To illustrate the overall approach, this model is analyzed using the Faraday-equivalent chemical potential approach and engineering intuition is used to guide affinity equalisation: a energy based analysis of the mitochondrial electron transport chain.

Model study on transesterification of soybean oil to biodiesel with methanol using solid base catalyst.

PubMed

Liu, Xuejun; Piao, Xianglan; Wang, Yujun; Zhu, Shenlin

2010-03-25

Modeling of the transesterification of vegetable oils to biodiesel using a solid base as a catalyst is very important because the mutual solubilities of oil and methanol will increase with the increasing biodiesel yield. The heterogeneous liquid-liquid-solid reaction system would become a liquid-solid system when the biodiesel reaches a certain content. In this work, we adopted a two-film theory and a steady state approximation assumption, then established a heterogeneous liquid-liquid-solid model in the first stage. After the diffusion coefficients on the liquid-liquid interface and the liquid-solid interface were calculated on the basis of the properties of the system, the theoretical value of biodiesel productivity changing with time was obtained. The predicted values were very near the experimental data, which indicated that the proposed models were suitable for the transesterification of soybean oil to biodiesel when solid bases were used as catalysts. Meanwhile, the model indicated that the transesterification reaction was controlled by both mass transfer and reaction. The total resistance will decrease with the increase in biodiesel yield in the liquid-liquid-solid stage. The solid base catalyst exhibited an activation energy range of 9-20 kcal/mol, which was consistent with the reported activation energy range of homogeneous catalysts.

A Multidimensional B-Spline Correction for Accurate Modeling Sugar Puckering in QM/MM Simulations.

PubMed

Huang, Ming; Dissanayake, Thakshila; Kuechler, Erich; Radak, Brian K; Lee, Tai-Sung; Giese, Timothy J; York, Darrin M

2017-09-12

The computational efficiency of approximate quantum mechanical methods allows their use for the construction of multidimensional reaction free energy profiles. It has recently been demonstrated that quantum models based on the neglect of diatomic differential overlap (NNDO) approximation have difficulty modeling deoxyribose and ribose sugar ring puckers and thus limit their predictive value in the study of RNA and DNA systems. A method has been introduced in our previous work to improve the description of the sugar puckering conformational landscape that uses a multidimensional B-spline correction map (BMAP correction) for systems involving intrinsically coupled torsion angles. This method greatly improved the adiabatic potential energy surface profiles of DNA and RNA sugar rings relative to high-level ab initio methods even for highly problematic NDDO-based models. In the present work, a BMAP correction is developed, implemented, and tested in molecular dynamics simulations using the AM1/d-PhoT semiempirical Hamiltonian for biological phosphoryl transfer reactions. Results are presented for gas-phase adiabatic potential energy surfaces of RNA transesterification model reactions and condensed-phase QM/MM free energy surfaces for nonenzymatic and RNase A-catalyzed transesterification reactions. The results show that the BMAP correction is stable, efficient, and leads to improvement in both the potential energy and free energy profiles for the reactions studied, as compared with ab initio and experimental reference data. Exploration of the effect of the size of the quantum mechanical region indicates the best agreement with experimental reaction barriers occurs when the full CpA dinucleotide substrate is treated quantum mechanically with the sugar pucker correction.

A Model-based B2B (Batch to Batch) Control for An Industrial Batch Polymerization Process

NASA Astrophysics Data System (ADS)

Ogawa, Morimasa

This paper describes overview of a model-based B2B (batch to batch) control for an industrial batch polymerization process. In order to control the reaction temperature precisely, several methods based on the rigorous process dynamics model are employed at all design stage of the B2B control, such as modeling and parameter estimation of the reaction kinetics which is one of the important part of the process dynamics model. The designed B2B control consists of the gain scheduled I-PD/II2-PD control (I-PD with double integral control), the feed-forward compensation at the batch start time, and the model adaptation utilizing the results of the last batch operation. Throughout the actual batch operations, the B2B control provides superior control performance compared with that of conventional control methods.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Mechanisms underlying the influence of saliency on value-based decisions

PubMed Central

Chen, Xiaomo; Mihalas, Stefan; Niebur, Ernst; Stuphorn, Veit

2013-01-01

Objects in the environment differ in their low-level perceptual properties (e.g., how easily a fruit can be recognized) as well as in their subjective value (how tasty it is). We studied the influence of visual salience on value-based decisions using a two alternative forced choice task, in which human subjects rapidly chose items from a visual display. All targets were equally easy to detect. Nevertheless, both value and salience strongly affected choices made and reaction times. We analyzed the neuronal mechanisms underlying these behavioral effects using stochastic accumulator models, allowing us to characterize not only the averages of reaction times but their full distributions. Independent models without interaction between the possible choices failed to reproduce the observed choice behavior, while models with mutual inhibition between alternative choices produced much better results. Mutual inhibition thus is an important feature of the decision mechanism. Value influenced the amount of accumulation in all models. In contrast, increased salience could either lead to an earlier start (onset model) or to a higher rate (speed model) of accumulation. Both models explained the data from the choice trials equally well. However, salience also affected reaction times in no-choice trials in which only one item was present, as well as error trials. Only the onset model could explain the observed reaction time distributions of error trials and no-choice trials. In contrast, the speed model could not, irrespective of whether the rate increase resulted from more frequent accumulated quanta or from larger quanta. Visual salience thus likely provides an advantage in the onset, not in the processing speed, of value-based decision making. PMID:24167161

A Geochemical Reaction Model for Titration of Contaminated Soil and Groundwater at the Oak Ridge Reservation

NASA Astrophysics Data System (ADS)

Zhang, F.; Parker, J. C.; Gu, B.; Luo, W.; Brooks, S. C.; Spalding, B. P.; Jardine, P. M.; Watson, D. B.

2007-12-01

This study investigates geochemical reactions during titration of contaminated soil and groundwater at the Oak Ridge Reservation in eastern Tennessee. The soils and groundwater exhibits low pH and high concentrations of aluminum, calcium, magnesium, manganese, various trace metals such as nickel and cobalt, and radionuclides such as uranium and technetium. The mobility of many of the contaminant species diminishes with increasing pH. However, base additions to increase pH are strongly buffered by various precipitation/dissolution and adsorption/desorption reactions. The ability to predict acid-base behavior and associated geochemical effects is thus critical to evaluate remediation performance of pH manipulation strategies. This study was undertaken to develop a practical but generally applicable geochemical model to predict aqueous and solid-phase speciation during soil and groundwater titration. To model titration in the presence of aquifer solids, an approach proposed by Spalding and Spalding (2001) was utilized, which treats aquifer solids as a polyprotic acid. Previous studies have shown that Fe and Al-oxyhydroxides strongly sorb dissolved Ni, U and Tc species. In this study, since the total Fe concentration is much smaller than that of Al, only ion exchange reactions associated with Al hydroxides are considered. An equilibrium reaction model that includes aqueous complexation, precipitation, ion exchange, and soil buffering reactions was developed and implemented in the code HydroGeoChem 5.0 (HGC5). Comparison of model results with experimental titration curves for contaminated groundwater alone and for soil- water systems indicated close agreement. This study is expected to facilitate field-scale modeling of geochemical processes under conditions with highly variable pH to develop practical methods to control contaminant mobility at geochemically complex sites.

Nonelastic nuclear reactions and accompanying gamma radiation

NASA Technical Reports Server (NTRS)

Snow, R.; Rosner, H. R.; George, M. C.; Hayes, J. D.

1971-01-01

Several aspects of nonelastic nuclear reactions which proceed through the formation of a compound nucleus are dealt with. The full statistical model and the partial statistical model are described and computer programs based on these models are presented along with operating instructions and input and output for sample problems. A theoretical development of the expression for the reaction cross section for the hybrid case which involves a combination of the continuum aspects of the full statistical model with the discrete level aspects of the partial statistical model is presented. Cross sections for level excitation and gamma production by neutron inelastic scattering from the nuclei Al-27, Fe-56, Si-28, and Pb-208 are calculated and compared with avaliable experimental data.

Comparison between phenomenological and ab-initio reaction and relaxation models in DSMC

NASA Astrophysics Data System (ADS)

Sebastião, Israel B.; Kulakhmetov, Marat; Alexeenko, Alina

2016-11-01

New state-specific vibrational-translational energy exchange and dissociation models, based on ab-initio data, are implemented in direct simulation Monte Carlo (DSMC) method and compared to the established Larsen-Borgnakke (LB) and total collision energy (TCE) phenomenological models. For consistency, both the LB and TCE models are calibrated with QCT-calculated O2+O data. The model comparison test cases include 0-D thermochemical relaxation under adiabatic conditions and 1-D normal shockwave calculations. The results show that both the ME-QCT-VT and LB models can reproduce vibrational relaxation accurately but the TCE model is unable to reproduce nonequilibrium rates even when it is calibrated to accurate equilibrium rates. The new reaction model does capture QCT-calculated nonequilibrium rates. For all investigated cases, we discuss the prediction differences based on the new model features.

TG study of the Li0.4Fe2.4Zn0.2O4 ferrite synthesis

NASA Astrophysics Data System (ADS)

Lysenko, E. N.; Nikolaev, E. V.; Surzhikov, A. P.

2016-02-01

In this paper, the kinetic analysis of Li-Zn ferrite synthesis was studied using thermogravimetry (TG) method through the simultaneous application of non-linear regression to several measurements run at different heating rates (multivariate non-linear regression). Using TG-curves obtained for the four heating rates and Netzsch Thermokinetics software package, the kinetic models with minimal adjustable parameters were selected to quantitatively describe the reaction of Li-Zn ferrite synthesis. It was shown that the experimental TG-curves clearly suggest a two-step process for the ferrite synthesis and therefore a model-fitting kinetic analysis based on multivariate non-linear regressions was conducted. The complex reaction was described by a two-step reaction scheme consisting of sequential reaction steps. It is established that the best results were obtained using the Yander three-dimensional diffusion model at the first stage and Ginstling-Bronstein model at the second step. The kinetic parameters for lithium-zinc ferrite synthesis reaction were found and discussed.

Model-based analysis of coupled equilibrium-kinetic processes: indirect kinetic studies of thermodynamic parameters using the dynamic data.

PubMed

Emami, Fereshteh; Maeder, Marcel; Abdollahi, Hamid

2015-05-07

Thermodynamic studies of equilibrium chemical reactions linked with kinetic procedures are mostly impossible by traditional approaches. In this work, the new concept of generalized kinetic study of thermodynamic parameters is introduced for dynamic data. The examples of equilibria intertwined with kinetic chemical mechanisms include molecular charge transfer complex formation reactions, pH-dependent degradation of chemical compounds and tautomerization kinetics in micellar solutions. Model-based global analysis with the possibility of calculating and embedding the equilibrium and kinetic parameters into the fitting algorithm has allowed the complete analysis of the complex reaction mechanisms. After the fitting process, the optimal equilibrium and kinetic parameters together with an estimate of their standard deviations have been obtained. This work opens up a promising new avenue for obtaining equilibrium constants through the kinetic data analysis for the kinetic reactions that involve equilibrium processes.

Fluid dynamic modeling of nano-thermite reactions

NASA Astrophysics Data System (ADS)

Martirosyan, Karen S.; Zyskin, Maxim; Jenkins, Charles M.; Yuki Horie, Yasuyuki

2014-03-01

This paper presents a direct numerical method based on gas dynamic equations to predict pressure evolution during the discharge of nanoenergetic materials. The direct numerical method provides for modeling reflections of the shock waves from the reactor walls that generates pressure-time fluctuations. The results of gas pressure prediction are consistent with the experimental evidence and estimates based on the self-similar solution. Artificial viscosity provides sufficient smoothing of shock wave discontinuity for the numerical procedure. The direct numerical method is more computationally demanding and flexible than self-similar solution, in particular it allows study of a shock wave in its early stage of reaction and allows the investigation of "slower" reactions, which may produce weaker shock waves. Moreover, numerical results indicate that peak pressure is not very sensitive to initial density and reaction time, providing that all the material reacts well before the shock wave arrives at the end of the reactor.

Fluid dynamic modeling of nano-thermite reactions

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

Martirosyan, Karen S., E-mail: karen.martirosyan@utb.edu; Zyskin, Maxim; Jenkins, Charles M.

2014-03-14

This paper presents a direct numerical method based on gas dynamic equations to predict pressure evolution during the discharge of nanoenergetic materials. The direct numerical method provides for modeling reflections of the shock waves from the reactor walls that generates pressure-time fluctuations. The results of gas pressure prediction are consistent with the experimental evidence and estimates based on the self-similar solution. Artificial viscosity provides sufficient smoothing of shock wave discontinuity for the numerical procedure. The direct numerical method is more computationally demanding and flexible than self-similar solution, in particular it allows study of a shock wave in its early stagemore » of reaction and allows the investigation of “slower” reactions, which may produce weaker shock waves. Moreover, numerical results indicate that peak pressure is not very sensitive to initial density and reaction time, providing that all the material reacts well before the shock wave arrives at the end of the reactor.« less

Reply to 'Comment on kinetic modeling of microbially-driven redox chemistry of subsurface environments: coupling transport, microbial metabolism and geochemistry' by J. Griffioen

NASA Astrophysics Data System (ADS)

Hunter, K. S.; Van Cappellen, P.

2000-01-01

Our paper, 'Kinetic modeling of microbially-driven redox chemistry of subsurface environments: coupling transport, microbial metabolism and geochemistry' (Hunter et al., 1998), presents a theoretical exploration of biogeochemical reaction networks and their importance to the biogeochemistry of groundwater systems. As with any other model, the kinetic reaction-transport model developed in our paper includes only a subset of all physically, biologically and chemically relevant processes in subsurface environments. It considers aquifer systems where the primary energy source driving microbial activity is the degradation of organic matter. In addition to the primary biodegradation pathways of organic matter (i.e. respiration and fermentation), the redox chemistry of groundwaters is also affected by reactions not directly involving organic matter oxidation. We refer to the latter as secondary reactions. By including secondary redox reactions which consume reduced reaction products (e.g., Mn2+, FeS, H2S), and in the process compete with microbial heterotrophic populations for available oxidants (i.e. O2, NO3-, Mn(IV), Fe(III), SO42-), we predict spatio-temporal distributions of microbial activity which differ significantly from those of models which consider only the biodegradation reactions. That is, the secondary reactions have a significant impact on the distributions of the rates of heterotrophic and chemolithotrophic metabolic pathways. We further show that secondary redox reactions, as well as non-redox reactions, significantly influence the acid-base chemistry of groundwaters. The distributions of dissolved inorganic redox species along flowpaths, however, are similar in simulations with and without secondary reactions (see Figs. 3(b) and 7(b) in Hunter et al., 1998), indicating that very different biogeochemical reaction dynamics may lead to essentially the same chemical redox zonation of a groundwater system.

A statistical approach to develop a detailed soot growth model using PAH characteristics

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

Raj, Abhijeet; Celnik, Matthew; Shirley, Raphael

A detailed PAH growth model is developed, which is solved using a kinetic Monte Carlo algorithm. The model describes the structure and growth of planar PAH molecules, and is referred to as the kinetic Monte Carlo-aromatic site (KMC-ARS) model. A detailed PAH growth mechanism based on reactions at radical sites available in the literature, and additional reactions obtained from quantum chemistry calculations are used to model the PAH growth processes. New rates for the reactions involved in the cyclodehydrogenation process for the formation of 6-member rings on PAHs are calculated in this work based on density functional theory simulations. Themore » KMC-ARS model is validated by comparing experimentally observed ensembles on PAHs with the computed ensembles for a C{sub 2}H{sub 2} and a C{sub 6}H{sub 6} flame at different heights above the burner. The motivation for this model is the development of a detailed soot particle population balance model which describes the evolution of an ensemble of soot particles based on their PAH structure. However, at present incorporating such a detailed model into a population balance is computationally unfeasible. Therefore, a simpler model referred to as the site-counting model has been developed, which replaces the structural information of the PAH molecules by their functional groups augmented with statistical closure expressions. This closure is obtained from the KMC-ARS model, which is used to develop correlations and statistics in different flame environments which describe such PAH structural information. These correlations and statistics are implemented in the site-counting model, and results from the site-counting model and the KMC-ARS model are in good agreement. Additionally the effect of steric hindrance in large PAH structures is investigated and correlations for sites unavailable for reaction are presented. (author)« less

Numerical simulation of two-dimensional flow over a heated carbon surface with coupled heterogeneous and homogeneous reactions

NASA Astrophysics Data System (ADS)

Johnson, Ryan Federick; Chelliah, Harsha Kumar

2017-01-01

For a range of flow and chemical timescales, numerical simulations of two-dimensional laminar flow over a reacting carbon surface were performed to understand further the complex coupling between heterogeneous and homogeneous reactions. An open-source computational package (OpenFOAM®) was used with previously developed lumped heterogeneous reaction models for carbon surfaces and a detailed homogeneous reaction model for CO oxidation. The influence of finite-rate chemical kinetics was explored by varying the surface temperatures from 1800 to 2600 K, while flow residence time effects were explored by varying the free-stream velocity up to 50 m/s. The reacting boundary layer structure dependence on the residence time was analysed by extracting the ratio of chemical source and species diffusion terms. The important contributions of radical species reactions on overall carbon removal rate, which is often neglected in multi-dimensional simulations, are highlighted. The results provide a framework for future development and validation of lumped heterogeneous reaction models based on multi-dimensional reacting flow configurations.

Modules based on the geochemical model PHREEQC for use in scripting and programming languages

USGS Publications Warehouse

Charlton, Scott R.; Parkhurst, David L.

2011-01-01

The geochemical model PHREEQC is capable of simulating a wide range of equilibrium reactions between water and minerals, ion exchangers, surface complexes, solid solutions, and gases. It also has a general kinetic formulation that allows modeling of nonequilibrium mineral dissolution and precipitation, microbial reactions, decomposition of organic compounds, and other kinetic reactions. To facilitate use of these reaction capabilities in scripting languages and other models, PHREEQC has been implemented in modules that easily interface with other software. A Microsoft COM (component object model) has been implemented, which allows PHREEQC to be used by any software that can interface with a COM server—for example, Excel®, Visual Basic®, Python, or MATLAB". PHREEQC has been converted to a C++ class, which can be included in programs written in C++. The class also has been compiled in libraries for Linux and Windows that allow PHREEQC to be called from C++, C, and Fortran. A limited set of methods implements the full reaction capabilities of PHREEQC for each module. Input methods use strings or files to define reaction calculations in exactly the same formats used by PHREEQC. Output methods provide a table of user-selected model results, such as concentrations, activities, saturation indices, and densities. The PHREEQC module can add geochemical reaction capabilities to surface-water, groundwater, and watershed transport models. It is possible to store and manipulate solution compositions and reaction information for many cells within the module. In addition, the object-oriented nature of the PHREEQC modules simplifies implementation of parallel processing for reactive-transport models. The PHREEQC COM module may be used in scripting languages to fit parameters; to plot PHREEQC results for field, laboratory, or theoretical investigations; or to develop new models that include simple or complex geochemical calculations.

Modules based on the geochemical model PHREEQC for use in scripting and programming languages

USGS Publications Warehouse

Charlton, S.R.; Parkhurst, D.L.

2011-01-01

The geochemical model PHREEQC is capable of simulating a wide range of equilibrium reactions between water and minerals, ion exchangers, surface complexes, solid solutions, and gases. It also has a general kinetic formulation that allows modeling of nonequilibrium mineral dissolution and precipitation, microbial reactions, decomposition of organic compounds, and other kinetic reactions. To facilitate use of these reaction capabilities in scripting languages and other models, PHREEQC has been implemented in modules that easily interface with other software. A Microsoft COM (component object model) has been implemented, which allows PHREEQC to be used by any software that can interface with a COM server-for example, Excel??, Visual Basic??, Python, or MATLAB??. PHREEQC has been converted to a C++ class, which can be included in programs written in C++. The class also has been compiled in libraries for Linux and Windows that allow PHREEQC to be called from C++, C, and Fortran. A limited set of methods implements the full reaction capabilities of PHREEQC for each module. Input methods use strings or files to define reaction calculations in exactly the same formats used by PHREEQC. Output methods provide a table of user-selected model results, such as concentrations, activities, saturation indices, and densities. The PHREEQC module can add geochemical reaction capabilities to surface-water, groundwater, and watershed transport models. It is possible to store and manipulate solution compositions and reaction information for many cells within the module. In addition, the object-oriented nature of the PHREEQC modules simplifies implementation of parallel processing for reactive-transport models. The PHREEQC COM module may be used in scripting languages to fit parameters; to plot PHREEQC results for field, laboratory, or theoretical investigations; or to develop new models that include simple or complex geochemical calculations. ?? 2011.

Use of Chemistry Software to Teach and Assess Model-Based Reaction and Equation Knowledge

ERIC Educational Resources Information Center

Pyatt, Kevin

2014-01-01

This study investigated the challenges students face when learning chemical reactions in a first-year chemistry course and the effectiveness of a curriculum and software implementation that was used to teach and assess student understanding of chemical reactions and equations. This study took place over a two year period in a public suburban…

Applying constraints on model-based methods: Estimation of rate constants in a second order consecutive reaction

NASA Astrophysics Data System (ADS)

Kompany-Zareh, Mohsen; Khoshkam, Maryam

2013-02-01

This paper describes estimation of reaction rate constants and pure ultraviolet/visible (UV-vis) spectra of the component involved in a second order consecutive reaction between Ortho-Amino benzoeic acid (o-ABA) and Diazoniom ions (DIAZO), with one intermediate. In the described system, o-ABA was not absorbing in the visible region of interest and thus, closure rank deficiency problem did not exist. Concentration profiles were determined by solving differential equations of the corresponding kinetic model. In that sense, three types of model-based procedures were applied to estimate the rate constants of the kinetic system, according to Levenberg/Marquardt (NGL/M) algorithm. Original data-based, Score-based and concentration-based objective functions were included in these nonlinear fitting procedures. Results showed that when there is error in initial concentrations, accuracy of estimated rate constants strongly depends on the type of applied objective function in fitting procedure. Moreover, flexibility in application of different constraints and optimization of the initial concentrations estimation during the fitting procedure were investigated. Results showed a considerable decrease in ambiguity of obtained parameters by applying appropriate constraints and adjustable initial concentrations of reagents.

Direct Air Capture of CO2 with an Amine Resin: A Molecular Modeling Study of the CO2 Capturing Process

PubMed Central

2017-01-01

Several reactions, known from other amine systems for CO2 capture, have been proposed for Lewatit R VP OC 1065. The aim of this molecular modeling study is to elucidate the CO2 capture process: the physisorption process prior to the CO2-capture and the reactions. Molecular modeling yields that the resin has a structure with benzyl amine groups on alternating positions in close vicinity of each other. Based on this structure, the preferred adsorption mode of CO2 and H2O was established. Next, using standard Density Functional Theory two catalytic reactions responsible for the actual CO2 capture were identified: direct amine and amine-H2O catalyzed formation of carbamic acid. The latter is a new type of catalysis. Other reactions are unlikely. Quantitative verification of the molecular modeling results with known experimental CO2 adsorption isotherms, applying a dual site Langmuir adsorption isotherm model, further supports all results of this molecular modeling study. PMID:29142339

The mechanism of myrmekite formation deduced from steady-diffusion modeling based on petrography: Case study of the Okueyama granitic body, Kyushu, Japan

NASA Astrophysics Data System (ADS)

Yuguchi, Takashi; Nishiyama, Tadao

2008-12-01

Myrmekite is an intergrowth texture consisting of vermicular quartz and albitic plagioclase (Ab 93An 7 in this study), typically occurring between K-feldspar and plagioclase. It occurs ubiquitously in both metamorphic and granitic rocks; however, its genesis has been an enigma. This paper describes myrmekite's petrography and discusses its genesis from the Okueyama granitic body (OKG), which is a young (14 Ma) granite in Southwest Japan with no evidence of deformation after solidification. The genesis of a newly observed texture, the 'reaction rim', will be also discussed in relation to myrmekite. The reaction rim is an albite layer (Ab 95An 5) with no vermicular quartz between K-feldspar and plagioclase, and it occasionally makes a composite texture with myrmekite. Both myrmekite and the reaction rim are accompanied by a diffusive boundary layer (Olg-layer) with a mean composition of oligoclase (Ab 75An 25) in the rim of neighboring plagioclase rim. The overall reactions in an open system for the formation of myrmekite and that for the reaction rim are derived based on the following two models: 1) one based on the assumption of conservation of solid volume with arbitrarily specified closure components, and 2) the other based on the assumption of closure of AlO 3/2 together with an arbitrarily specified volume factor. Steady diffusion modeling in an open system based on the overall reaction thus derived defines the stability field of myrmekite and of the reaction rim in terms of the ratios of phenomenological coefficients ( L-ratios). The steady diffusion models for the above two models have essentially the same features. Myrmekite is stable for large values (> 10) of LAlAl/ LCaCa, for moderate values of LAlAl/ LSiSi, and for only small values (< 1) of LAlAl/ LNaNa. In the case of the reaction rim, the stability field is much wider in a plot of LAlAl/ LCaCa vs. LAlAl/ LNaNa, and its dependence on LAlAl/ LSiSi is stronger than that of myrmekite. The reaction rim is stable only for large values of LAlAl/ LCaCa, which is consistent with the case of myrmekite. Exchange cycles for myrmekite and the reaction rim show that the essential formation mechanism is albitization of K-feldspar: KAlSi 3O 8 + NaO 1/2 = NaAlSi 3O 8 + KO 1/2, which is coupled with albitization of plagioclase via diffusive transport of NaO 1/2 and SiO 2: CaAl 2Si 2O 8 + NaO 1/2 + SiO 2 = NaAlSi 3O 8 + CaO + AlO 3/2. Formation of myrmekite requires more SiO 2 than development of the reaction rim; some of the SiO 2 is given by decomposition of K-feldspar and some is supplied from the environment to the boundary between K-feldspar and plagioclase.

Uncertainty evaluation of nuclear reaction model parameters using integral and microscopic measurements. Covariances evaluation with CONRAD code

NASA Astrophysics Data System (ADS)

de Saint Jean, C.; Habert, B.; Archier, P.; Noguere, G.; Bernard, D.; Tommasi, J.; Blaise, P.

2010-10-01

In the [eV;MeV] energy range, modelling of the neutron induced reactions are based on nuclear reaction models having parameters. Estimation of co-variances on cross sections or on nuclear reaction model parameters is a recurrent puzzle in nuclear data evaluation. Major breakthroughs were asked by nuclear reactor physicists to assess proper uncertainties to be used in applications. In this paper, mathematical methods developped in the CONRAD code[2] will be presented to explain the treatment of all type of uncertainties, including experimental ones (statistical and systematic) and propagate them to nuclear reaction model parameters or cross sections. Marginalization procedure will thus be exposed using analytical or Monte-Carlo solutions. Furthermore, one major drawback found by reactor physicist is the fact that integral or analytical experiments (reactor mock-up or simple integral experiment, e.g. ICSBEP, …) were not taken into account sufficiently soon in the evaluation process to remove discrepancies. In this paper, we will describe a mathematical framework to take into account properly this kind of information.

Cure Kinetics of Benzoxazine/Cycloaliphatic Epoxy Resin by Differential Scanning Calorimetry

NASA Astrophysics Data System (ADS)

Gouni, Sreeja Reddy

Understanding the curing kinetics of a thermoset resin has a significant importance in developing and optimizing curing cycles in various industrial manufacturing processes. This can assist in improving the quality of final product and minimizing the manufacturing-associated costs. One approach towards developing such an understanding is to formulate kinetic models that can be used to optimize curing time and temperature to reach a full cure state or to determine time to apply pressure in an autoclave process. Various phenomenological reaction models have been used in the literature to successfully predict the kinetic behavior of a thermoset system. The current research work was designed to investigate the cure kinetics of Bisphenol-A based Benzoxazine (BZ-a) and Cycloaliphatic epoxy resin (CER) system under isothermal and nonisothermal conditions by Differential Scanning Calorimetry (DSC). The cure characteristics of BZ-a/CER copolymer systems with 75/25 wt% and 50/50 wt% have been studied and compared to that of pure benzoxazine under nonisothermal conditions. The DSC thermograms exhibited by these BZ-a/CER copolymer systems showed a single exothermic peak, indicating that the reactions between benzoxazine-benzoxazine monomers and benzoxazine-cycloaliphatic epoxy resin were interactive and occurred simultaneously. The Kissinger method and isoconversional methods including Ozawa-Flynn-Wall and Freidman were employed to obtain the activation energy values and determine the nature of the reaction. The cure behavior and the kinetic parameters were determined by adopting a single step autocatalytic model based on Kamal and Sourour phenomenological reaction model. The model was found to suitably describe the cure kinetics of copolymer system prior to the diffusion-control reaction. Analyzing and understanding the thermoset resin system under isothermal conditions is also important since it is the most common practice in the industry. The BZ-a/CER copolymer system with 75/25 wt% ratio which exhibited high glass transition temperature compared to polybenzoxazine was investigated under isothermal conditions. The copolymer system exhibited the maximum reaction rate at an intermediate degree of cure (20 to 40%), indicating that the reaction was autocatalytic. Similar to the nonisothermal cure kinetics, Kamal and Sourour phenomenological reaction model was adopted to determine the kinetic behavior of the system. The theoretical values based on the developed model showed a deviation from the obtained experimental values, which indicated the change in kinetics from a reaction-controlled mechanism to a diffusion-controlled mechanism with increasing reaction conversion. To substantiate the hypothesis, Fournier et al's diffusion factor was introduced into the model, resulting in an agreement between the theoretical and experimental values. The changes in cross-linking density and the glass transition temperature (Tg) with increasing epoxy concentration were investigated under Dynamic Mechanical Analyzer (DMA). The BZ-a/CER copolymer system with the epoxy content of less than 40 wt% exhibited the greatest Tg and cross-linking density compared to benzoxazine homopolymer and other ratios.

Hydrochemical characteristics and groundwater evolution modeling in sedimentary rocks of the Tono mine, Japan

NASA Astrophysics Data System (ADS)

Sasamoto, Hiroshi; Yui, Mikazu; Arthur, Randolph C.

Based on geochemical data collected by Japan Nuclear Cycle Development Institute (JNC) in the Tono uranium mine, a conceptual groundwater evolution model developed by JNC is tested to evaluate whether equilibrium-based concepts of water-rock interaction are consistent with observed variations in the mineralogy and hydrochemistry of the Tono mine area. The chemical evolution of the groundwaters is modeled assuming local equilibrium for selected mineral-fluid reactions, taking into account the rainwater origin of these solutions. Results suggest that it is possible to interpret approximately the actual groundwater chemistry (i.e., pH, Eh, total dissolved concentrations of Si, Na, Ca, K, Al, carbonate and sulfate) if the following assumptions are adopted (a) CO 2 concentration in the gas phase contacting pore solutions in the overlying soil zone=10 -1 atm, and (b) minerals in the rock zone that control the solubility of respective elements in the groundwater include: chalcedony (Si), albite (Na), kaolinite (Al), calcite (Ca and carbonate), muscovite (K) and pyrite (Eh and sulfate). This result helps to build confidence in the use of simplified geochemical modeling techniques to develop an understanding of dominant geochemical reactions controlling groundwater chemistry in rocks similar to those that could be used for the geological disposal of radioactive wastes. It is noted, however, that the available field data may not be sufficient to adequately constrain parameters in the groundwater evolution model. In particular, more detailed information characterizing certain site properties are needed to improve the model. For this reason, a model that accounts for ion-exchange reactions among clay minerals, and which is based on the results of laboratory experiments, has also been evaluated in the present study. Further improvement of model considering ion-exchange reactions are needed in future, however.

Identification of functional differences in metabolic networks using comparative genomics and constraint-based models.

PubMed

Hamilton, Joshua J; Reed, Jennifer L

2012-01-01

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here.

Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

PubMed Central

Hamilton, Joshua J.; Reed, Jennifer L.

2012-01-01

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here. PMID:22666308

Mesoscale simulations of shockwave energy dissipation via chemical reactions.

PubMed

Antillon, Edwin; Strachan, Alejandro

2015-02-28

We use a particle-based mesoscale model that incorporates chemical reactions at a coarse-grained level to study the response of materials that undergo volume-reducing chemical reactions under shockwave-loading conditions. We find that such chemical reactions can attenuate the shockwave and characterize how the parameters of the chemical model affect this behavior. The simulations show that the magnitude of the volume collapse and velocity at which the chemistry propagates are critical to weaken the shock, whereas the energetics in the reactions play only a minor role. Shock loading results in transient states where the material is away from local equilibrium and, interestingly, chemical reactions can nucleate under such non-equilibrium states. Thus, the timescales for equilibration between the various degrees of freedom in the material affect the shock-induced chemistry and its ability to attenuate the propagating shock.

Spatiotemporal pattern in somitogenesis: a non-Turing scenario with wave propagation.

PubMed

Nagahara, Hiroki; Ma, Yue; Takenaka, Yoshiko; Kageyama, Ryoichiro; Yoshikawa, Kenichi

2009-08-01

Living organisms maintain their lives under far-from-equilibrium conditions by creating a rich variety of spatiotemporal structures in a self-organized manner, such as temporal rhythms, switching phenomena, and development of the body. In this paper, we focus on the dynamical process of morphogens in somitogenesis in mice where propagation of the gene expression level plays an essential role in creating the spatially periodic patterns of the vertebral columns. We present a simple discrete reaction-diffusion model which includes neighboring interaction through an activator, but not diffusion of an inhibitor. We can produce stationary periodic patterns by introducing the effect of spatial discreteness to the field. Based on the present model, we discuss the underlying physical principles that are independent of the details of biomolecular reactions. We also discuss the framework of spatial discreteness based on the reaction-diffusion model in relation to a cellular array, by comparison with an actual experimental observation.

Students' mental models on the solubility and solubility product concept

NASA Astrophysics Data System (ADS)

Rahmi, Chusnur; Katmiati, Siti; Wiji, Mulyani, Sri

2017-05-01

This study aims to obtain some information regarding profile of students' mental models on the solubility and solubility product concept. A descriptive qualitative method was the method employed in the study. The participants of the study were students XI grade of a senior high school in Bandung. To collect the data, diagnostic test on mental model-prediction, observation, explanation (TDM-POE) instrument was employed in the study. The results of the study revealed that on the concept of precipitation formation of a reaction, 30% of students were not able to explain the precipitation formation of a reaction either in submicroscopic or symbolic level although the microscopic have been shown; 26% of students were able to explain the precipitation formation of a reaction based on the relation of Qsp and Ksp, but they were not able to explain the interaction of particles that involved in the reaction and to calculate Qsp; 26% of students were able to explain the precipitation formation of a reaction based on the relation of Qsp and Ksp, and determine the particles involved, but they did not have the knowledge about the interactions occured and were uncapable of calculating Qsp; and 18% of students were able to explain the precipitation formation of a reaction based on the relation of Qsp and Ksp, and determine the interactions of the particles involved in the reactions but they were not able to calculate Qsp. On the effect of adding common ions and decreasing pH towards the solubility concept, 96% of students were not able to explain the effect of adding common ions and decreasing pH towards the solubility either in submicroscopic or symbolic level although the microscopic have been shown; while 4% of students were only able to explain the effect of adding common ions towards the solubility based on the chemical equilibrium shifts and predict the effect of decreasing pH towards the solubility. However, they were not able to calculate the solubility before and after adding common ions and explain it up to the submicroscopic level either based on the shift of equilibrium solubility or the comparison of solubility calculation results before and after decreasing pH. Overall, the present study showed that most students obtain incomplete mental model on the solubility and solubility product concept. From the findings, it is recommended for the teachers to improve students' learning activity.

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.

Acid–base chemical reaction model for nucleation rates in the polluted atmospheric boundary layer

PubMed Central

Chen, Modi; Titcombe, Mari; Jiang, Jingkun; Jen, Coty; Kuang, Chongai; Fischer, Marc L.; Eisele, Fred L.; Siepmann, J. Ilja; Hanson, David R.; Zhao, Jun; McMurry, Peter H.

2012-01-01

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid–base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta. PMID:23091030

Acid-base chemical reaction model for nucleation rates in the polluted atmospheric boundary layer.

PubMed

Chen, Modi; Titcombe, Mari; Jiang, Jingkun; Jen, Coty; Kuang, Chongai; Fischer, Marc L; Eisele, Fred L; Siepmann, J Ilja; Hanson, David R; Zhao, Jun; McMurry, Peter H

2012-11-13

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid-base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta.

Effect of slow energy releasing on divergent detonation of Insensitive High Explosives

NASA Astrophysics Data System (ADS)

Hu, Xiaomian; Pan, Hao; Huang, Yong; Wu, Zihui

2014-03-01

There exists a slow energy releasing (SER) process in the slow reaction zone located behind the detonation wave due to the carbon cluster in the detonation products of Insensitive High Explosives (IHEs), and the process will affect the divergent detonation wave's propagation and the driving process of the explosives. To study the potential effect, a new artificial burn model including the SER process based on the programmed burn model is proposed in the paper. Quasi-steady analysis of the new model indicates that the nonlinearity of the detonation speed as a function of front curvature owes to the significant change of the reaction rate and the reaction zone length at the sonic state. What's more, in simulating the detonation of IHE JB-9014, the new model including the slow reaction can predict a slower jump-off velocity, in good agreement with the result of the test.

Scavenging and recombination kinetics in a radiation spur: The successive ordered scavenging events

NASA Astrophysics Data System (ADS)

Al-Samra, Eyad H.; Green, Nicholas J. B.

2018-03-01

This study describes stochastic models to investigate the successive ordered scavenging events in a spur of four radicals, a model system based on a radiation spur. Three simulation models have been developed to obtain the probabilities of the ordered scavenging events: (i) a Monte Carlo random flight (RF) model, (ii) hybrid simulations in which the reaction rate coefficient is used to generate scavenging times for the radicals and (iii) the independent reaction times (IRT) method. The results of these simulations are found to be in agreement with one another. In addition, a detailed master equation treatment is also presented, and used to extract simulated rate coefficients of the ordered scavenging reactions from the RF simulations. These rate coefficients are transient, the rate coefficients obtained for subsequent reactions are effectively equal, and in reasonable agreement with the simple correction for competition effects that has recently been proposed.

Critical evaluation of Jet-A spray combustion using propane chemical kinetics in gas turbine combustion simulated by KIVA-2

NASA Technical Reports Server (NTRS)

Nguyen, H. L.; Ying, S.-J.

1990-01-01

Jet-A spray combustion has been evaluated in gas turbine combustion with the use of propane chemical kinetics as the first approximation for the chemical reactions. Here, the numerical solutions are obtained by using the KIVA-2 computer code. The KIVA-2 code is the most developed of the available multidimensional combustion computer programs for application of the in-cylinder combustion dynamics of internal combustion engines. The released version of KIVA-2 assumes that 12 chemical species are present; the code uses an Arrhenius kinetic-controlled combustion model governed by a four-step global chemical reaction and six equilibrium reactions. Researchers efforts involve the addition of Jet-A thermophysical properties and the implementation of detailed reaction mechanisms for propane oxidation. Three different detailed reaction mechanism models are considered. The first model consists of 131 reactions and 45 species. This is considered as the full mechanism which is developed through the study of chemical kinetics of propane combustion in an enclosed chamber. The full mechanism is evaluated by comparing calculated ignition delay times with available shock tube data. However, these detailed reactions occupy too much computer memory and CPU time for the computation. Therefore, it only serves as a benchmark case by which to evaluate other simplified models. Two possible simplified models were tested in the existing computer code KIVA-2 for the same conditions as used with the full mechanism. One model is obtained through a sensitivity analysis using LSENS, the general kinetics and sensitivity analysis program code of D. A. Bittker and K. Radhakrishnan. This model consists of 45 chemical reactions and 27 species. The other model is based on the work published by C. K. Westbrook and F. L. Dryer.

A Memory-Based Model of Hick's Law

ERIC Educational Resources Information Center

Schneider, Darryl W.; Anderson, John R.

2011-01-01

We propose and evaluate a memory-based model of Hick's law, the approximately linear increase in choice reaction time with the logarithm of set size (the number of stimulus-response alternatives). According to the model, Hick's law reflects a combination of associative interference during retrieval from declarative memory and occasional savings…

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things

PubMed Central

Akan, Ozgur B.

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics. PMID:29415019

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things.

PubMed

Kuscu, Murat; Akan, Ozgur B

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics.

A computational study of ultrafast acid dissociation and acid-base neutralization reactions. I. The model.

PubMed

Maurer, Patrick; Thomas, Vibin; Rivard, Ugo; Iftimie, Radu

2010-07-28

Ultrafast, time-resolved investigations of acid-base neutralization reactions have recently been performed using systems containing the photoacid 8-hydroxypyrene-1,3,6-trisulfonic acid trisodium salt (HPTS) and various Bronsted bases. Two conflicting neutralization mechanisms have been formulated by Mohammed et al. [Science 310, 83 (2005)] and Siwick et al. [J. Am. Chem. Soc. 129, 13412 (2007)] for the same acid-base system. Herein an ab initio molecular dynamics based computational model is formulated, which is able to investigate the validity of the proposed mechanisms in the general context of ground-state acid-base neutralization reactions. Our approach consists of using 2,4,6-tricyanophenol (exp. pKa congruent with 1) as a model for excited-state HPTS( *) (pKa congruent with 1.4) and carboxylate ions for the accepting base. We employ our recently proposed dipole-field/quantum mechanics (QM) treatment [P. Maurer and R. Iftimie, J. Chem. Phys. 132, 074112 (2010)] of the proton donor and acceptor molecules. This approach allows one to tune the free energy of neutralization to any desired value as well as model initial nonequilibrium hydration effects caused by a sudden increase in acidity, making it possible to achieve a more realistic comparison with experimental data than could be obtained via a full-QM treatment of the entire system. It is demonstrated that the dipole-field/QM model reproduces correctly key properties of the 2,4,6-tricyanophenol acid molecule including gas-phase proton dissociation energies and dipole moments, and condensed-phase hydration structure and pKa values.

Finite element code development for modeling detonation of HMX composites

NASA Astrophysics Data System (ADS)

Duran, Adam V.; Sundararaghavan, Veera

2017-01-01

In this work, we present a hydrodynamics code for modeling shock and detonation waves in HMX. A stable efficient solution strategy based on a Taylor-Galerkin finite element (FE) discretization was developed to solve the reactive Euler equations. In our code, well calibrated equations of state for the solid unreacted material and gaseous reaction products have been implemented, along with a chemical reaction scheme and a mixing rule to define the properties of partially reacted states. A linear Gruneisen equation of state was employed for the unreacted HMX calibrated from experiments. The JWL form was used to model the EOS of gaseous reaction products. It is assumed that the unreacted explosive and reaction products are in both pressure and temperature equilibrium. The overall specific volume and internal energy was computed using the rule of mixtures. Arrhenius kinetics scheme was integrated to model the chemical reactions. A locally controlled dissipation was introduced that induces a non-oscillatory stabilized scheme for the shock front. The FE model was validated using analytical solutions for SOD shock and ZND strong detonation models. Benchmark problems are presented for geometries in which a single HMX crystal is subjected to a shock condition.

Direct modeling of the electrochemistry in the three-phase boundary of solid oxide fuel cell anodes by density functional theory: a critical overview.

PubMed

Shishkin, M; Ziegler, T

2014-02-07

The first principles modeling of electrochemical reactions has proven useful for the development of efficient, durable and low cost solid oxide full cells (SOFCs). In this account we focus on recent advances in modeling of structural, electronic and catalytic properties of the SOFC anodes based on density functional theory (DFT) first principle calculations. As a starting point, we highlight that the adequate analysis of cell electrochemistry generally requires modeling of chemical reactions at the metal/oxide interface rather than on individual metal or oxide surfaces. The atomic models of Ni/YSZ and Ni/CeO2 interfaces, required for DFT simulations of reactions on SOFC anodes are discussed next, together with the analysis of the electronic structure of these interfaces. Then we proceed to DFT-based findings on charge transfer mechanisms during redox reactions on these two anodes. We provide a comparison of the electronic properties of Ni/YSZ and Ni/CeO2 interfaces and present an interpretation of their different chemical performances. Subsequently we discuss the computed energy pathways of fuel oxidation mechanisms, obtained by various groups to date. We also discuss the results of DFT studies combined with microkinetic modeling as well as the results of kinetic Monte Carlo simulations. In conclusion we summarize the key findings of DFT modeling of metal/oxide interfaces to date and highlight possible directions in the future modeling of SOFC anodes.

Investigation to biodiesel production by the two-step homogeneous base-catalyzed transesterification.

PubMed

Ye, Jianchu; Tu, Song; Sha, Yong

2010-10-01

For the two-step transesterification biodiesel production made from the sunflower oil, based on the kinetics model of the homogeneous base-catalyzed transesterification and the liquid-liquid phase equilibrium of the transesterification product, the total methanol/oil mole ratio, the total reaction time, and the split ratios of methanol and reaction time between the two reactors in the stage of the two-step reaction are determined quantitatively. In consideration of the transesterification intermediate product, both the traditional distillation separation process and the improved separation process of the two-step reaction product are investigated in detail by means of the rigorous process simulation. In comparison with the traditional distillation process, the improved separation process of the two-step reaction product has distinct advantage in the energy duty and equipment requirement due to replacement of the costly methanol-biodiesel distillation column. Copyright 2010 Elsevier Ltd. All rights reserved.

Transport-reaction model for defect and carrier behavior within displacement cascades in gallium arsenide

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

Wampler, William R.; Myers, Samuel M.

2014-02-01

A model is presented for recombination of charge carriers at displacement damage in gallium arsenide, which includes clustering of the defects in atomic displacement cascades produced by neutron or ion irradiation. The carrier recombination model is based on an atomistic description of capture and emission of carriers by the defects with time evolution resulting from the migration and reaction of the defects. The physics and equations on which the model is based are presented, along with details of the numerical methods used for their solution. The model uses a continuum description of diffusion, field-drift and reaction of carriers and defectsmore » within a representative spherically symmetric cluster. The initial radial defect profiles within the cluster were chosen through pair-correlation-function analysis of the spatial distribution of defects obtained from the binary-collision code MARLOWE, using recoil energies for fission neutrons. Charging of the defects can produce high electric fields within the cluster which may influence transport and reaction of carriers and defects, and which may enhance carrier recombination through band-to-trap tunneling. Properties of the defects are discussed and values for their parameters are given, many of which were obtained from density functional theory. The model provides a basis for predicting the transient response of III-V heterojunction bipolar transistors to pulsed neutron irradiation.« less

Microscopic Study of the 6Li(p, α)3He Reaction at Low Energies

NASA Astrophysics Data System (ADS)

Solovyev, Alexander; Igashov, Sergey

2018-01-01

The 6Li(p, α)3He reaction important for nuclear astrophysics is studied in the framework of a microscopic approach based on a multichannel algebraic version of the resonating group model. Astrophysical S-factor for the reaction is calculated at low energies. The obtained result is compared with experimental data and other theoretical calculations.

One-Dimensional Transport with Equilibrium Chemistry (OTEQ) - A Reactive Transport Model for Streams and Rivers

USGS Publications Warehouse

Runkel, Robert L.

2010-01-01

OTEQ is a mathematical simulation model used to characterize the fate and transport of waterborne solutes in streams and rivers. The model is formed by coupling a solute transport model with a chemical equilibrium submodel. The solute transport model is based on OTIS, a model that considers the physical processes of advection, dispersion, lateral inflow, and transient storage. The equilibrium submodel is based on MINTEQ, a model that considers the speciation and complexation of aqueous species, acid-base reactions, precipitation/dissolution, and sorption. Within OTEQ, reactions in the water column may result in the formation of solid phases (precipitates and sorbed species) that are subject to downstream transport and settling processes. Solid phases on the streambed may also interact with the water column through dissolution and sorption/desorption reactions. Consideration of both mobile (waterborne) and immobile (streambed) solid phases requires a unique set of governing differential equations and solution techniques that are developed herein. The partial differential equations describing physical transport and the algebraic equations describing chemical equilibria are coupled using the sequential iteration approach. The model's ability to simulate pH, precipitation/dissolution, and pH-dependent sorption provides a means of evaluating the complex interactions between instream chemistry and hydrologic transport at the field scale. This report details the development and application of OTEQ. Sections of the report describe model theory, input/output specifications, model applications, and installation instructions. OTEQ may be obtained over the Internet at http://water.usgs.gov/software/OTEQ.

Reaction modeling of drainage quality in the Duluth Complex, northern Minnesota, USA

USGS Publications Warehouse

Seal, Robert; Lapakko, Kim; Piatak, Nadine; Woodruff, Laurel G.

2015-01-01

Reaction modeling can be a valuable tool in predicting the long-term behavior of waste material if representative rate constants can be derived from long-term leaching tests or other approaches. Reaction modeling using the REACT program of the Geochemist’s Workbench was conducted to evaluate long-term drainage quality affected by disseminated Cu-Ni-(Co-)-PGM sulfide mineralization in the basal zone of the Duluth Complex where significant resources have been identified. Disseminated sulfide minerals, mostly pyrrhotite and Cu-Fe sulfides, are hosted by clinopyroxene-bearing troctolites. Carbonate minerals are scarce to non-existent. Long-term simulations of up to 20 years of weathering of tailings used two different sets of rate constants: one based on published laboratory single-mineral dissolution experiments, and one based on leaching experiments using bulk material from the Duluth Complex conducted by the Minnesota Department of Natural Resources (MNDNR). The simulations included only plagioclase, olivine, clinopyroxene, pyrrhotite, and water as starting phases. Dissolved oxygen concentrations were assumed to be in equilibrium with atmospheric oxygen. The simulations based on the published single-mineral rate constants predicted that pyrrhotite would be effectively exhausted in less than two years and pH would rise accordingly. In contrast, only 20 percent of the pyrrhotite was depleted after two years using the MNDNR rate constants. Predicted pyrrhotite depletion by the simulation based on the MNDNR rate constant matched well with published results of laboratory tests on tailings. Modeling long-term weathering of mine wastes also can provide important insights into secondary reactions that may influence the permeability of tailings and thereby affect weathering behavior. Both models predicted the precipitation of a variety of secondary phases including goethite, gibbsite, and clay (nontronite).

Relating Derived Relations as a Model of Analogical Reasoning: Reaction Times and Event-Related Potentials

ERIC Educational Resources Information Center

Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M.; Whelan, Robert; Dymond, Simon

2005-01-01

The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as…

Model-based analysis of keratin intermediate filament assembly

NASA Astrophysics Data System (ADS)

Martin, Ines; Leitner, Anke; Walther, Paul; Herrmann, Harald; Marti, Othmar

2015-09-01

The cytoskeleton of epithelial cells consists of three types of filament systems: microtubules, actin filaments and intermediate filaments (IFs). Here, we took a closer look at type I and type II IF proteins, i.e. keratins. They are hallmark constituents of epithelial cells and are responsible for the generation of stiffness, the cellular response to mechanical stimuli and the integrity of entire cell layers. Thereby, keratin networks constitute an important instrument for cells to adapt to their environment. In particular, we applied models to characterize the assembly of keratin K8 and K18 into elongated filaments as a means for network formation. For this purpose, we measured the length of in vitro assembled keratin K8/K18 filaments by transmission electron microscopy at different time points. We evaluated the experimental data of the longitudinal annealing reaction using two models from polymer chemistry: the Schulz-Zimm model and the condensation polymerization model. In both scenarios one has to make assumptions about the reaction process. We compare how well the models fit the measured data and thus determine which assumptions fit best. Based on mathematical modelling of experimental filament assembly data we define basic mechanistic properties of the elongation reaction process.

Experimental Study of Serpentinization Reactions

NASA Technical Reports Server (NTRS)

Cohen, B. A.; Brearley, A. J.; Ganguly, J.; Liermann, H.-P.; Keil, K.

2004-01-01

Current carbonaceous chondrite parent-body thermal models [1-3] produce scenarios that are inconsistent with constraints on aqueous alteration conditions based on meteorite mineralogical evidence, such as phase stability relationships within the meteorite matrix minerals [4] and isotope equilibration arguments [5, 6]. This discrepancy arises principally because of the thermal runaway effect produced by silicate hydration reactions (here loosely called serpentinization, as the principal products are serpentine minerals), which are so exothermic as to produce more than enough heat to melt more ice and provide a self-sustaining chain reaction. One possible way to dissipate the heat of reaction is to use a very small parent body [e.g., 2] or possibly a rubble pile model. Another possibility is to release this heat more slowly, which depends on the alteration reaction path and kinetics.

Sensitivity of Polar Stratospheric Ozone Loss to Uncertainties in Chemical Reaction Kinetics

NASA Technical Reports Server (NTRS)

Kawa, S. Randolph; Stolarksi, Richard S.; Douglass, Anne R.; Newman, Paul A.

2008-01-01

Several recent observational and laboratory studies of processes involved in polar stratospheric ozone loss have prompted a reexamination of aspects of our understanding for this key indicator of global change. To a large extent, our confidence in understanding and projecting changes in polar and global ozone is based on our ability to simulate these processes in numerical models of chemistry and transport. The fidelity of the models is assessed in comparison with a wide range of observations. These models depend on laboratory-measured kinetic reaction rates and photolysis cross sections to simulate molecular interactions. A typical stratospheric chemistry mechanism has on the order of 50- 100 species undergoing over a hundred intermolecular reactions and several tens of photolysis reactions. The rates of all of these reactions are subject to uncertainty, some substantial. Given the complexity of the models, however, it is difficult to quantify uncertainties in many aspects of system. In this study we use a simple box-model scenario for Antarctic ozone to estimate the uncertainty in loss attributable to known reaction kinetic uncertainties. Following the method of earlier work, rates and uncertainties from the latest laboratory evaluations are applied in random combinations. We determine the key reactions and rates contributing the largest potential errors and compare the results to observations to evaluate which combinations are consistent with atmospheric data. Implications for our theoretical and practical understanding of polar ozone loss will be assessed.

Mode-Specific SN2 Reaction Dynamics.

PubMed

Wang, Yan; Song, Hongwei; Szabó, István; Czakó, Gábor; Guo, Hua; Yang, Minghui

2016-09-01

Despite its importance in chemistry, the microscopic dynamics of bimolecular nucleophilic substitution (SN2) reactions is still not completely elucidated. In this publication, the dynamics of a prototypical SN2 reaction (F(-) + CH3Cl → CH3F + Cl(-)) is investigated using a high-dimensional quantum mechanical model on an accurate potential energy surface (PES) and further analyzed by quasi-classical trajectories on the same PES. While the indirect mechanism dominates at low collision energies, the direct mechanism makes a significant contribution. The reactivity is found to depend on the specific reactant vibrational mode excitation. The mode specificity, which is more prevalent in the direct reaction, is rationalized by a transition-state-based model.

Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity.

PubMed

Schneider, Nadine; Lowe, Daniel M; Sayle, Roger A; Landrum, Gregory A

2015-01-26

Fingerprint methods applied to molecules have proven to be useful for similarity determination and as inputs to machine-learning models. Here, we present the development of a new fingerprint for chemical reactions and validate its usefulness in building machine-learning models and in similarity assessment. Our final fingerprint is constructed as the difference of the atom-pair fingerprints of products and reactants and includes agents via calculated physicochemical properties. We validated the fingerprints on a large data set of reactions text-mined from granted United States patents from the last 40 years that have been classified using a substructure-based expert system. We applied machine learning to build a 50-class predictive model for reaction-type classification that correctly predicts 97% of the reactions in an external test set. Impressive accuracies were also observed when applying the classifier to reactions from an in-house electronic laboratory notebook. The performance of the novel fingerprint for assessing reaction similarity was evaluated by a cluster analysis that recovered 48 out of 50 of the reaction classes with a median F-score of 0.63 for the clusters. The data sets used for training and primary validation as well as all python scripts required to reproduce the analysis are provided in the Supporting Information.

Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

PubMed Central

Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.

2011-01-01

The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001

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.

Scaffolding Students' Online Critiquing of Expert- and Peer-generated Molecular Models of Chemical Reactions

NASA Astrophysics Data System (ADS)

Chang, Hsin-Yi; Chang, Hsiang-Chi

2013-08-01

In this study, we developed online critiquing activities using an open-source computer learning environment. We investigated how well the activities scaffolded students to critique molecular models of chemical reactions made by scientists, peers, and a fictitious peer, and whether the activities enhanced the students' understanding of science models and chemical reactions. The activities were implemented in an eighth-grade class with 28 students in a public junior high school in southern Taiwan. The study employed mixed research methods. Data collected included pre- and post-instructional assessments, post-instructional interviews, and students' electronic written responses and oral discussions during the critiquing activities. The results indicated that these activities guided the students to produce overall quality critiques. Also, the students developed a more sophisticated understanding of chemical reactions and scientific models as a result of the intervention. Design considerations for effective model critiquing activities are discussed based on observational results, including the use of peer-generated artefacts for critiquing to promote motivation and collaboration, coupled with critiques of scientific models to enhance students' epistemological understanding of model purpose and communication.

Numerical modeling of coupled variably saturated fluid flow and reactive transport with fast and slow chemical reactions

NASA Astrophysics Data System (ADS)

Yeh, Gour-Tsyh (George); Siegel, Malcolm D.; Li, Ming-Hsu

2001-02-01

The couplings among chemical reaction rates, advective and diffusive transport in fractured media or soils, and changes in hydraulic properties due to precipitation and dissolution within fractures and in rock matrix are important for both nuclear waste disposal and remediation of contaminated sites. This paper describes the development and application of LEHGC2.0, a mechanistically based numerical model for simulation of coupled fluid flow and reactive chemical transport, including both fast and slow reactions in variably saturated media. Theoretical bases and numerical implementations are summarized, and two example problems are demonstrated. The first example deals with the effect of precipitation/dissolution on fluid flow and matrix diffusion in a two-dimensional fractured media. Because of the precipitation and decreased diffusion of solute from the fracture into the matrix, retardation in the fractured medium is not as large as the case wherein interactions between chemical reactions and transport are not considered. The second example focuses on a complicated but realistic advective-dispersive-reactive transport problem. This example exemplifies the need for innovative numerical algorithms to solve problems involving stiff geochemical reactions.

Interrogating the catalytic mechanism of nanoparticle mediated Stille coupling reactions employing bio-inspired Pd nanocatalysts.

PubMed

Pacardo, Dennis B; Slocik, Joseph M; Kirk, Kyle C; Naik, Rajesh R; Knecht, Marc R

2011-05-01

To address issues concerning the global environmental and energy state, new catalytic technologies must be developed that translate ambient and efficient conditions to heavily used reactions. To achieve this, the structure/function relationship between model catalysts and individual reactions must be critically discerned to identify structural motifs responsible for the reactivity. This is especially true for nanoparticle-based systems where this level of information remains limited. Here we present evidence indicating that peptide-capped Pd nanoparticles drive Stille C-C coupling reactions via Pd atom leaching. Through a series of reaction studies, the materials are shown to be optimized for reactivity under ambient conditions where increases in temperature or catalyst concentration deactivate reactivity due to the leaching process. A quartz crystal microbalance analysis demonstrates that Pd leaching occurs during the initial oxidative addition step at the nanoparticle surface by aryl halides. Together, this suggests that peptide-based materials may be optimally suited for use as model systems to isolate structural motifs responsible for the generation of catalytically reactive materials under ambient synthetic conditions. © The Royal Society of Chemistry 2011

Interrogating the catalytic mechanism of nanoparticle mediated Stille coupling reactions employing bio-inspired Pd nanocatalysts

NASA Astrophysics Data System (ADS)

Pacardo, Dennis B.; Slocik, Joseph M.; Kirk, Kyle C.; Naik, Rajesh R.; Knecht, Marc R.

2011-05-01

To address issues concerning the global environmental and energy state, new catalytic technologies must be developed that translate ambient and efficient conditions to heavily used reactions. To achieve this, the structure/function relationship between model catalysts and individual reactions must be critically discerned to identify structural motifs responsible for the reactivity. This is especially true for nanoparticle-based systems where this level of information remains limited. Here we present evidence indicating that peptide-capped Pd nanoparticles drive Stille C-C coupling reactions via Pd atom leaching. Through a series of reaction studies, the materials are shown to be optimized for reactivity under ambient conditions where increases in temperature or catalyst concentration deactivate reactivity due to the leaching process. A quartz crystal microbalance analysis demonstrates that Pd leaching occurs during the initial oxidative addition step at the nanoparticle surface by aryl halides. Together, this suggests that peptide-based materials may be optimally suited for use as model systems to isolate structural motifs responsible for the generation of catalytically reactive materials under ambient synthetic conditions.

Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods

PubMed Central

2014-01-01

Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614

User’s Guide for Biodegradation Reactions in TMVOCBio

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

Jung, Yoojin; Battistelli, Alfredo

TMVOCBio is an extended version of the TMVOC numerical reservoir simulator, with the capability of simulating multiple biodegradation reactions mediated by different microbial populations or based on different redox reactions, thus involving different electron acceptors. This modeling feature is implemented within the existing TMVOC module in iTOUGH2. TMVOCBio, originally developed by Battistelli (2003; 2004), uses a general modified form of the Monod kinetic rate equation to simulate biodegradation reactions, which effectively simulates the uptake of a substrate while accounting for various limiting factors (i.e., the limitation by substrate, electron acceptor, or nutrients). Two approaches are included: 1) a multiple Monodmore » kinetic rate equation, which assumes all the limiting factors simultaneously affect the substrate uptake rate, and 2) a minimum Monod model, which assumes that the substrate uptake rate is controlled by the most limiting factor among those acting for the specific substrate. As the limiting factors, biomass growth inhibition, toxicity effects, as well as competitive and non-competitive inhibition effects are included. The temperature and moisture dependence of biodegradation reactions is also considered. This report provides mathematical formulations and assumptions used for modeling the biodegradation reactions, and describes additional modeling capabilities. Detailed description of input format for biodegradation reactions is presented along with sample problems.« less

Simplified Modeling of Oxidation of Hydrocarbons

NASA Technical Reports Server (NTRS)

Bellan, Josette; Harstad, Kenneth

2008-01-01

A method of simplified computational modeling of oxidation of hydrocarbons is undergoing development. This is one of several developments needed to enable accurate computational simulation of turbulent, chemically reacting flows. At present, accurate computational simulation of such flows is difficult or impossible in most cases because (1) the numbers of grid points needed for adequate spatial resolution of turbulent flows in realistically complex geometries are beyond the capabilities of typical supercomputers now in use and (2) the combustion of typical hydrocarbons proceeds through decomposition into hundreds of molecular species interacting through thousands of reactions. Hence, the combination of detailed reaction- rate models with the fundamental flow equations yields flow models that are computationally prohibitive. Hence, further, a reduction of at least an order of magnitude in the dimension of reaction kinetics is one of the prerequisites for feasibility of computational simulation of turbulent, chemically reacting flows. In the present method of simplified modeling, all molecular species involved in the oxidation of hydrocarbons are classified as either light or heavy; heavy molecules are those having 3 or more carbon atoms. The light molecules are not subject to meaningful decomposition, and the heavy molecules are considered to decompose into only 13 specified constituent radicals, a few of which are listed in the table. One constructs a reduced-order model, suitable for use in estimating the release of heat and the evolution of temperature in combustion, from a base comprising the 13 constituent radicals plus a total of 26 other species that include the light molecules and related light free radicals. Then rather than following all possible species through their reaction coordinates, one follows only the reduced set of reaction coordinates of the base. The behavior of the base was examined in test computational simulations of the combustion of heptane in a stirred reactor at various initial pressures ranging from 0.1 to 6 MPa. Most of the simulations were performed for stoichiometric mixtures; some were performed for fuel/oxygen mole ratios of 1/2 and 2.

Unraveling the role of photons and electrons upon their chemical interaction with photoresist during EUV exposure

NASA Astrophysics Data System (ADS)

Pollentier, Ivan; Vesters, Yannick; Petersen, John S.; Vanelderen, Pieter; Rathore, Atish; de Simone, Danilo; Vandenberghe, Geert

2018-03-01

The interaction of 91.6 eV EUV photons with photoresist - in particular chemically amplified resist (CAR) - is different than exposure at 193 nm and 248 nm wavelengths. The latter is understood well and it is known that photons interact with electrons in the resist's molecular valence orbitals (for chemically amplified resist (CAR) the photon interacts with the photo acid generator (PAG), which leads to a deprotection reaction on a polymer after a thermal catalytic reaction during a post-exposure-bake.). At EUV however, more steps are involved in the radiolysis process between the absorption of the photon and the final chemical modification. These are related to the generation of primary electrons and their decay to lower energy secondary electrons, and most of this steps are not well understood. In this paper, the reaction products from EUV and low energy electron exposure are examined using Residual Gas Analysis (RGA), which measures and analyzes the outgassing products related to the ongoing reactions. This investigation is applied firstly on a model CAR where details of the resist chemical constituents were known prior to testing. The measurement not only resolved information on the expected acid related reactions from the PAG and protection groups, but also exhibited direct scission reactions of the polymer, where some of them lead to polymerization reactions. Moreover, the measurement quantifies the balance between the different ongoing reactions, which were confirmed by contrast curve measurements. Based on learnings on the model resist, applied the measurement technique to commercial resists, where actual resist chemistry composition is not known. Despite that, it was found that information could be deduced to distinguish between acid related ongoing reactions and direct scission of reaction on the base polymer and quantify their relation. Moreover, different generations of commercial resists based on similar chemistry platform were investigated, which revealed that improvements in printing performance could be explained by PAG reaction yield increase.

Unified connected theory of few-body reaction mechanisms in N-body scattering theory

NASA Technical Reports Server (NTRS)

Polyzou, W. N.; Redish, E. F.

1978-01-01

A unified treatment of different reaction mechanisms in nonrelativistic N-body scattering is presented. The theory is based on connected kernel integral equations that are expected to become compact for reasonable constraints on the potentials. The operators T/sub +-//sup ab/(A) are approximate transition operators that describe the scattering proceeding through an arbitrary reaction mechanism A. These operators are uniquely determined by a connected kernel equation and satisfy an optical theorem consistent with the choice of reaction mechanism. Connected kernel equations relating T/sub +-//sup ab/(A) to the full T/sub +-//sup ab/ allow correction of the approximate solutions for any ignored process to any order. This theory gives a unified treatment of all few-body reaction mechanisms with the same dynamic simplicity of a model calculation, but can include complicated reaction mechanisms involving overlapping configurations where it is difficult to formulate models.

Pop-it beads to introduce catalysis of reaction rate and substrate depletion effects.

PubMed

Gehret, Austin U

2017-03-04

A kinesthetic classroom activity was designed to help students understand enzyme activity and catalysis of reaction rate. Students served the role of enzymes by manipulating Pop-It Beads as the catalytic event. This activity illuminates the relationship between reaction rate and reaction progress by allowing students to experience first-hand the effect of substrate depletion on catalyzed reaction rate. Preliminary findings based on survey results and exam performance suggest the activity could prove beneficial to students in the targeted learning outcomes. Unique to previous kinesthetic approaches that model Michaelis-Menten kinetics, this activity models the effects of substrate depletion on catalyzed reaction rate. Therefore, it could prove beneficial for conveying the reasoning behind the initial rate simplification used in Michaelis-Menten kinetics. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(2):179-183, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

A novel approach of modeling continuous dark hydrogen fermentation.

PubMed

Alexandropoulou, Maria; Antonopoulou, Georgia; Lyberatos, Gerasimos

2018-02-01

In this study a novel modeling approach for describing fermentative hydrogen production in a continuous stirred tank reactor (CSTR) was developed, using the Aquasim modeling platform. This model accounts for the key metabolic reactions taking place in a fermentative hydrogen producing reactor, using fixed stoichiometry but different reaction rates. Biomass yields are determined based on bioenergetics. The model is capable of describing very well the variation in the distribution of metabolic products for a wide range of hydraulic retention times (HRT). The modeling approach is demonstrated using the experimental data obtained from a CSTR, fed with food industry waste (FIW), operating at different HRTs. The kinetic parameters were estimated through fitting to the experimental results. Hydrogen and total biogas production rates were predicted very well by the model, validating the basic assumptions regarding the implicated stoichiometric biochemical reactions and their kinetic rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Rongle Zhang; Jie Chang; Yuanyuan Xu

A new kinetic model of the Fischer-Tropsch synthesis (FTS) is proposed to describe the non-Anderson-Schulz-Flory (ASF) product distribution. The model is based on the double-polymerization monomers hypothesis, in which the surface C{sub 2}{asterisk} species acts as a chain-growth monomer in the light-product range, while C{sub 1}{asterisk} species acts as a chain-growth monomer in the heavy-product range. The detailed kinetic model in the Langmuir-Hinshelwood-Hougen-Watson type based on the elementary reactions is derived for FTS and the water-gas-shift reaction. Kinetic model candidates are evaluated by minimization of multiresponse objective functions with a genetic algorithm approach. The model of hydrocarbon product distribution ismore » consistent with experimental data (

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

PubMed

Bender, Andreas; Scheiber, Josef; Glick, Meir; Davies, John W; Azzaoui, Kamal; Hamon, Jacques; Urban, Laszlo; Whitebread, Steven; Jenkins, Jeremy L

2007-06-01

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions. Firstly, in silico (computational) Bayesian models for 70 PSP-related targets were built, which are able to detect 93% of the ligands binding at IC(50) < or = 10 microM at an overall correct classification rate of about 94%. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side-effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90% of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92%. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back-projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid mu and the muscarinic M2 receptors, as well as for cyclooxygenase-1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.

MapMaker and PathTracer for tracking carbon in genome-scale metabolic models

PubMed Central

Tervo, Christopher J.; Reed, Jennifer L.

2016-01-01

Constraint-based reconstruction and analysis (COBRA) modeling results can be difficult to interpret given the large numbers of reactions in genome-scale models. While paths in metabolic networks can be found, existing methods are not easily combined with constraint-based approaches. To address this limitation, two tools (MapMaker and PathTracer) were developed to find paths (including cycles) between metabolites, where each step transfers carbon from reactant to product. MapMaker predicts carbon transfer maps (CTMs) between metabolites using only information on molecular formulae and reaction stoichiometry, effectively determining which reactants and products share carbon atoms. MapMaker correctly assigned CTMs for over 97% of the 2,251 reactions in an Escherichia coli metabolic model (iJO1366). Using CTMs as inputs, PathTracer finds paths between two metabolites. PathTracer was applied to iJO1366 to investigate the importance of using CTMs and COBRA constraints when enumerating paths, to find active and high flux paths in flux balance analysis (FBA) solutions, to identify paths for putrescine utilization, and to elucidate a potential CO2 fixation pathway in E. coli. These results illustrate how MapMaker and PathTracer can be used in combination with constraint-based models to identify feasible, active, and high flux paths between metabolites. PMID:26771089

Thermodynamic analysis of Bacillus subtilis endospore protonation using isothermal titration calorimetry

NASA Astrophysics Data System (ADS)

Harrold, Zoë R.; Gorman-Lewis, Drew

2013-05-01

Bacterial proton and metal adsorption reactions have the capacity to affect metal speciation and transport in aqueous environments. We coupled potentiometric titration and isothermal titration calorimetry (ITC) analyses to study Bacillus subtilis spore-proton adsorption. We modeled the potentiometric data using a four and five-site non-electrostatic surface complexation model (NE-SCM). Heats of spore surface protonation from coupled ITC analyses were used to determine site specific enthalpies of protonation based on NE-SCMs. The five-site model resulted in a substantially better model fit for the heats of protonation but did not significantly improve the potentiometric titration model fit. The improvement observed in the five-site protonation heat model suggests the presence of a highly exothermic protonation reaction circa pH 7 that cannot be resolved in the less sensitive potentiometric data. From the log Ks and enthalpies we calculated corresponding site specific entropies. Log Ks and site concentrations describing spore surface protonation are statistically equivalent to B. subtilis cell surface protonation constants. Spore surface protonation enthalpies, however, are more exothermic relative to cell based adsorption suggesting a different bonding environment. The thermodynamic parameters defined in this study provide insight on molecular scale spore-surface protonation reactions. Coupled ITC and potentiometric titrations can reveal highly exothermic, and possibly endothermic, adsorption reactions that are overshadowed in potentiometric models alone. Spore-proton adsorption NE-SCMs derived in this study provide a framework for future metal adsorption studies.

How are the Concepts and Theories of Acid-Base Reactions Presented? Chemistry in Textbooks and as Presented by Teachers

ERIC Educational Resources Information Center

Furio-Mas, Carlos; Calatayud, Maria Luisa; Guisasola, Jenaro; Furio-Gomez, Cristina

2005-01-01

This paper investigates the views of science and scientific activity that can be found in chemistry textbooks and heard from teachers when acid-base reactions are introduced to grade 12 and university chemistry students. First, the main macroscopic and microscopic conceptual models are developed. Second, we attempt to show how the existence of…

Incorporating extrinsic noise into the stochastic simulation of biochemical reactions: A comparison of approaches

NASA Astrophysics Data System (ADS)

Thanh, Vo Hong; Marchetti, Luca; Reali, Federico; Priami, Corrado

2018-02-01

The stochastic simulation algorithm (SSA) has been widely used for simulating biochemical reaction networks. SSA is able to capture the inherently intrinsic noise of the biological system, which is due to the discreteness of species population and to the randomness of their reciprocal interactions. However, SSA does not consider other sources of heterogeneity in biochemical reaction systems, which are referred to as extrinsic noise. Here, we extend two simulation approaches, namely, the integration-based method and the rejection-based method, to take extrinsic noise into account by allowing the reaction propensities to vary in time and state dependent manner. For both methods, new efficient implementations are introduced and their efficiency and applicability to biological models are investigated. Our numerical results suggest that the rejection-based method performs better than the integration-based method when the extrinsic noise is considered.

Modeling study on the cleavage step of the self-splicing reaction in group I introns

NASA Technical Reports Server (NTRS)

Setlik, R. F.; Garduno-Juarez, R.; Manchester, J. I.; Shibata, M.; Ornstein, R. L.; Rein, R.

1993-01-01

A three-dimensional model of the Tetrahymena thermophila group I intron is used to further explore the catalytic mechanism of the transphosphorylation reaction of the cleavage step. Based on the coordinates of the catalytic core model proposed by Michel and Westhof (Michel, F., Westhof, E. J. Mol. Biol. 216, 585-610 (1990)), we first converted their ligation step model into a model of the cleavage step by the substitution of several bases and the removal of helix P9. Next, an attempt to place a trigonal bipyramidal transition state model in the active site revealed that this modified model for the cleavage step could not accommodate the transition state due to insufficient space. A lowering of P1 helix relative to surrounding helices provided the additional space required. Simultaneously, it provided a better starting geometry to model the molecular contacts proposed by Pyle et al. (Pyle, A. M., Murphy, F. L., Cech, T. R. Nature 358, 123-128. (1992)), based on mutational studies involving the J8/7 segment. Two hydrated Mg2+ complexes were placed in the active site of the ribozyme model, using the crystal structure of the functionally similar Klenow fragment (Beese, L.S., Steitz, T.A. EMBO J. 10, 25-33 (1991)) as a guide. The presence of two metal ions in the active site of the intron differs from previous models, which incorporate one metal ion in the catalytic site to fulfill the postulated roles of Mg2+ in catalysis. The reaction profile is simulated based on a trigonal bipyramidal transition state, and the role of the hydrated Mg2+ complexes in catalysis is further explored using molecular orbital calculations.

Reactive solute transport in streams: 1. Development of an equilibrium- based model

USGS Publications Warehouse

Runkel, Robert L.; Bencala, Kenneth E.; Broshears, Robert E.; Chapra, Steven C.

1996-01-01

An equilibrium-based solute transport model is developed for the simulation of trace metal fate and transport in streams. The model is formed by coupling a solute transport model with a chemical equilibrium submodel based on MINTEQ. The solute transport model considers the physical processes of advection, dispersion, lateral inflow, and transient storage, while the equilibrium submodel considers the speciation and complexation of aqueous species, precipitation/dissolution and sorption. Within the model, reactions in the water column may result in the formation of solid phases (precipitates and sorbed species) that are subject to downstream transport and settling processes. Solid phases on the streambed may also interact with the water column through dissolution and sorption/desorption reactions. Consideration of both mobile (water-borne) and immobile (streambed) solid phases requires a unique set of governing differential equations and solution techniques that are developed herein. The partial differential equations describing physical transport and the algebraic equations describing chemical equilibria are coupled using the sequential iteration approach.

Direct observation of the oxidation of DNA bases by phosphate radicals formed under radiation: a model of the backbone-to-base hole transfer.

PubMed

Ma, Jun; Marignier, Jean-Louis; Pernot, Pascal; Houée-Levin, Chantal; Kumar, Anil; Sevilla, Michael D; Adhikary, Amitava; Mostafavi, Mehran

2018-05-30

In irradiated DNA, by the base-to-base and backbone-to-base hole transfer processes, the hole (i.e., the unpaired spin) localizes on the most electropositive base, guanine. Phosphate radicals formed via ionization events in the DNA-backbone must play an important role in the backbone-to-base hole transfer process. However, earlier studies on irradiated hydrated DNA, on irradiated DNA-models in frozen aqueous solution and in neat dimethyl phosphate showed the formation of carbon-centered radicals and not phosphate radicals. Therefore, to model the backbone-to-base hole transfer process, we report picosecond pulse radiolysis studies of the reactions between H2PO4˙ with the DNA bases - G, A, T, and C in 6 M H3PO4 at 22 °C. The time-resolved observations show that in 6 M H3PO4, H2PO4˙ causes the one-electron oxidation of adenine, guanine and thymine, by forming the cation radicals via a single electron transfer (SET) process; however, the rate constant of the reaction of H2PO4˙ with cytosine is too low (<107 L mol-1 s-1) to be measured. The rates of these reactions are influenced by the protonation states and the reorganization energies of the base radicals and of the phosphate radical in 6 M H3PO4.

Reactive Fluid Flow and Applications to Diagenesis, Mineral Deposits, and Crustal Rocks

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

Rye, Danny M.; Bolton, Edward W.

2002-11-04

The objective is to initiate new: modeling of coupled fluid flow and chemical reactions of geologic environments; experimental and theoretical studies of water-rock reactions; collection and interpretation of stable isotopic and geochemical field data at many spatial scales of systems involving fluid flow and reaction in environments ranging from soils to metamorphic rocks. Theoretical modeling of coupled fluid flow and chemical reactions, involving kinetics, has been employed to understand the differences between equilibrium, steady-state, and non-steady-state behavior of the chemical evolution of open fluid-rock systems. The numerical codes developed in this project treat multi-component, finite-rate reactions combined with advective andmore » dispersive transport in multi-dimensions. The codes incorporate heat, mass, and isotopic transfer in both porous and fractured media. Experimental work has obtained the kinetic rate laws of pertinent silicate-water reactions and the rates of Sr release during chemical weathering. Ab-initio quantum mechanical techniques have been applied to obtain the kinetics and mechanisms of silicate surface reactions and isotopic exchange between water and dissolved species. Geochemical field-based studies were carried out on the Wepawaug metamorphic schist, on the Irish base-metal sediment-hosted ore system, in the Dalradian metamorphic complex in Scotland, and on weathering in the Columbia River flood basalts. The geochemical and isotopic field data, and the experimental and theoretical rate data, were used as constraints on the numerical models and to determine the length and time scales relevant to each of the field areas.« less

A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

PubMed

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Model for transport and reaction of defects and carriers within displacement cascades in gallium arsenide

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

Wampler, William R., E-mail: wrwampl@sandia.gov; Myers, Samuel M.

A model is presented for recombination of charge carriers at evolving displacement damage in gallium arsenide, which includes clustering of the defects in atomic displacement cascades produced by neutron or ion irradiation. The carrier recombination model is based on an atomistic description of capture and emission of carriers by the defects with time evolution resulting from the migration and reaction of the defects. The physics and equations on which the model is based are presented, along with the details of the numerical methods used for their solution. The model uses a continuum description of diffusion, field-drift and reaction of carriers,more » and defects within a representative spherically symmetric cluster of defects. The initial radial defect profiles within the cluster were determined through pair-correlation-function analysis of the spatial distribution of defects obtained from the binary-collision code MARLOWE, using recoil energies for fission neutrons. Properties of the defects are discussed and values for their parameters are given, many of which were obtained from density functional theory. The model provides a basis for predicting the transient response of III-V heterojunction bipolar transistors to displacement damage from energetic particle irradiation.« less

Saponification reaction system: a detailed mass transfer coefficient determination.

PubMed

Pečar, Darja; Goršek, Andreja

2015-01-01

The saponification of an aromatic ester with an aqueous sodium hydroxide was studied within a heterogeneous reaction medium in order to determine the overall kinetics of the selected system. The extended thermo-kinetic model was developed compared to the previously used simple one. The reaction rate within a heterogeneous liquid-liquid system incorporates a chemical kinetics term as well as mass transfer between both phases. Chemical rate constant was obtained from experiments within a homogeneous medium, whilst the mass-transfer coefficient was determined separately. The measured thermal profiles were then the bases for determining the overall reaction-rate. This study presents the development of an extended kinetic model for considering mass transfer regarding the saponification of ethyl benzoate with sodium hydroxide within a heterogeneous reaction medium. The time-dependences are presented for the mass transfer coefficient and the interfacial areas at different heterogeneous stages and temperatures. The results indicated an important role of reliable kinetic model, as significant difference in k(L)a product was obtained with extended and simple approach.

Particle-based modeling of heterogeneous chemical kinetics including mass transfer.

PubMed

Sengar, A; Kuipers, J A M; van Santen, Rutger A; Padding, J T

2017-08-01

Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.

Particle-based modeling of heterogeneous chemical kinetics including mass transfer

NASA Astrophysics Data System (ADS)

Sengar, A.; Kuipers, J. A. M.; van Santen, Rutger A.; Padding, J. T.

2017-08-01

Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.

Neurocomputation by Reaction Diffusion

NASA Astrophysics Data System (ADS)

Liang, Ping

1995-08-01

This Letter demonstrates the possible role nonsynaptic diffusion neurotransmission may play in neurocomputation using an artificial neural network model. A reaction-diffusion neural network model with field-based information-processing mechanisms is proposed. The advantages of nonsynaptic field neurotransmission from a computational viewpoint demonstrated in this Letter include long-range inhibition using only local interaction, nonhardwired and changeable (target specific) long-range communication pathways, and multiple simultaneous spatiotemporal organization processes in the same medium.

Space biosynthesis systems

NASA Technical Reports Server (NTRS)

Nyiri, L. K.; Toth, G. M.

1976-01-01

Model reactions based on chemical, enzymatic or cellular conversion of D glucose into d gluconic acid are designed to unequivocally define the advantages of microgravity on reaction mechanisms, mass-transfers and separation of organic chemicals and to serve as procedures to test the performance characteristics of space bioprocessing equipment.

Mathematical Description Development of Reactions of Metallic Gallium Using Kinetic Block Diagram

NASA Astrophysics Data System (ADS)

Yakovleva, A. A.; Soboleva, V. G.; Filatova, E. G.

2018-05-01

A kinetic block diagram based on a logical sequence of actions in the mathematical processing of a kinetic data is used. A type of reactions of metallic gallium in hydrochloric acid solutions is determined. It has been established that the reactions of the formation of gallium oxide and its salts proceed independently and in the absence of the diffusion resistance. Kinetic models connecting the constants of the reaction rate with the activation energy and describing the evolution of the process are obtained.

Solving gap metabolites and blocked reactions in genome-scale models: application to the metabolic network of Blattabacterium cuenoti.

PubMed

Ponce-de-León, Miguel; Montero, Francisco; Peretó, Juli

2013-10-31

Metabolic reconstruction is the computational-based process that aims to elucidate the network of metabolites interconnected through reactions catalyzed by activities assigned to one or more genes. Reconstructed models may contain inconsistencies that appear as gap metabolites and blocked reactions. Although automatic methods for solving this problem have been previously developed, there are many situations where manual curation is still needed. We introduce a general definition of gap metabolite that allows its detection in a straightforward manner. Moreover, a method for the detection of Unconnected Modules, defined as isolated sets of blocked reactions connected through gap metabolites, is proposed. The method has been successfully applied to the curation of iCG238, the genome-scale metabolic model for the bacterium Blattabacterium cuenoti, obligate endosymbiont of cockroaches. We found the proposed approach to be a valuable tool for the curation of genome-scale metabolic models. The outcome of its application to the genome-scale model B. cuenoti iCG238 is a more accurate model version named as B. cuenoti iMP240.

Kinetics of Cation and Oxyanion Adsorption and Desorption on Ferrihydrite: Roles of Ferrihydrite Binding Sites and a Unified Model

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

Tian, Lei; Shi, Zhenqing; Lu, Yang

Understanding the kinetics of toxic ion reactions with ferrihydrite is crucial for predicting the dynamic behavior of contaminants in soil environments. In this study, the kinetics of As(V), Cr(VI), Cu, and Pb adsorption and desorption on ferrihydrite were investigated with a combination of laboratory macroscopic experiments, microscopic investigation and mechanistic modeling. The rates of As(V), Cr(VI), Cu, and Pb adsorption and desorption on ferrihydrite, as systematically studied using a stirred-flow method, was highly dependent on the reaction pH and metal concentrations and varied significantly among four metals. Spherical aberration-corrected scanning transmission electron microscopy (Cs-STEM) showed, at sub-nano scales, all fourmore » metals were distributed within the ferrihydrite particle aggregates homogeneously after adsorption reactions, with no evidence of surface diffusion-controlled processes. Based on experimental results, we developed a unifying kinetics model for both cation and oxyanion adsorption/desorption on ferrihydrite based on the mechanistic-based equilibrium model CD-MUSIC. Overall, the model described the kinetic results well, and we quantitatively demonstrated how the equilibrium properties of the cation and oxyanion binding to various ferrihydrite sites affected the adsorption and desorption rates. Our results provided a unifying quantitative modeling method for the kinetics of both cation and oxyanion adsorption/desorption on iron minerals.« less

GOBF-ARMA based model predictive control for an ideal reactive distillation column.

PubMed

Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K

2015-11-01

This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. Copyright © 2015 Elsevier Inc. All rights reserved.

Fission fragment angular distributions in the reactions {sup 16}O+{sup 188}Os and {sup 28}Si+{sup 176}Yb

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

Tripathi, R.; Sudarshan, K.; Sharma, S. K.

2009-06-15

Fission fragment angular distributions have been measured in the reactions {sup 16}O+{sup 188}Os and {sup 28}Si+{sup 176}Yb to investigate the contribution from noncompound nucleus fission. Parameters for statistical model calculations were fixed using fission cross section data in the {sup 16}O+{sup 188}Os reaction. Experimental anisotropies were in reasonable agreement with those calculated using the statistical saddle point model for both reactions. The present results are also consistent with those of mass distribution studies in the fission of {sup 202}Po, formed in the reactions with varying entrance channel mass asymmetry. However, the present studies do not show a large fusion hindrancemore » as reported in the pre-actinide region based on the measurement of evaporation residue cross section.« less

Modeling languages for biochemical network simulation: reaction vs equation based approaches.

PubMed

Wiechert, Wolfgang; Noack, Stephan; Elsheikh, Atya

2010-01-01

Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.

STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies.

PubMed

Hepburn, Iain; Chen, Weiliang; Wils, Stefan; De Schutter, Erik

2012-05-10

Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems. We describe STEPS, a stochastic reaction-diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction-diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation. STEPS simulates models of cellular reaction-diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/

Kinetic Modeling of a Silicon Refining Process in a Moist Hydrogen Atmosphere

NASA Astrophysics Data System (ADS)

Chen, Zhiyuan; Morita, Kazuki

2018-03-01

We developed a kinetic model that considers both silicon loss and boron removal in a metallurgical grade silicon refining process. This model was based on the hypotheses of reversible reactions. The reaction rate coefficient kept the same form but error of terminal boron concentration could be introduced when relating irreversible reactions. Experimental data from published studies were used to develop a model that fit the existing data. At 1500 °C, our kinetic analysis suggested that refining silicon in a moist hydrogen atmosphere generates several primary volatile species, including SiO, SiH, HBO, and HBO2. Using the experimental data and the kinetic analysis of volatile species, we developed a model that predicts a linear relationship between the reaction rate coefficient k and both the quadratic function of p(H2O) and the square root of p(H2). Moreover, the model predicted the partial pressure values for the predominant volatile species and the prediction was confirmed by the thermodynamic calculations, indicating the reliability of the model. We believe this model provides a foundation for designing a silicon refining process with a fast boron removal rate and low silicon loss.

Kinetic Modeling of a Silicon Refining Process in a Moist Hydrogen Atmosphere

NASA Astrophysics Data System (ADS)

Chen, Zhiyuan; Morita, Kazuki

2018-06-01

We developed a kinetic model that considers both silicon loss and boron removal in a metallurgical grade silicon refining process. This model was based on the hypotheses of reversible reactions. The reaction rate coefficient kept the same form but error of terminal boron concentration could be introduced when relating irreversible reactions. Experimental data from published studies were used to develop a model that fit the existing data. At 1500 °C, our kinetic analysis suggested that refining silicon in a moist hydrogen atmosphere generates several primary volatile species, including SiO, SiH, HBO, and HBO2. Using the experimental data and the kinetic analysis of volatile species, we developed a model that predicts a linear relationship between the reaction rate coefficient k and both the quadratic function of p(H2O) and the square root of p(H2). Moreover, the model predicted the partial pressure values for the predominant volatile species and the prediction was confirmed by the thermodynamic calculations, indicating the reliability of the model. We believe this model provides a foundation for designing a silicon refining process with a fast boron removal rate and low silicon loss.

DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

PubMed

Smith, Robert W; van Rosmalen, Rik P; Martins Dos Santos, Vitor A P; Fleck, Christian

2018-06-19

Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values. This greatly reduces the mathematical complexity, while providing a reasonably good description of the system in steady state. However, without a large number of constraints, many different flux sets can describe the optimal model and we obtain no information on how metabolite levels dynamically change. Thus, to accurately determine what is taking place within the cell, finer quality data and more detailed models need to be constructed. In this paper we present a computational framework, DMPy, that uses a network scheme as input to automatically search for kinetic rates and produce a mathematical model that describes temporal changes of metabolite fluxes. The parameter search utilises several online databases to find measured reaction parameters. From this, we take advantage of previous modelling efforts, such as Parameter Balancing, to produce an initial mathematical model of a metabolic pathway. We analyse the effect of parameter uncertainty on model dynamics and test how recent flux-based model reduction techniques alter system properties. To our knowledge this is the first time such analysis has been performed on large models of metabolism. Our results highlight that good estimates of at least 80% of the reaction rates are required to accurately model metabolic systems. Furthermore, reducing the size of the model by grouping reactions together based on fluxes alters the resulting system dynamics. The presented pipeline automates the modelling process for large metabolic networks. From this, users can simulate their pathway of interest and obtain a better understanding of how altering conditions influences cellular dynamics. By testing the effects of different parameterisations we are also able to provide suggestions to help construct more accurate models of complete metabolic systems in the future.

Quantum chemical approach to estimating the thermodynamics of metabolic reactions.

PubMed

Jinich, Adrian; Rappoport, Dmitrij; Dunn, Ian; Sanchez-Lengeling, Benjamin; Olivares-Amaya, Roberto; Noor, Elad; Even, Arren Bar; Aspuru-Guzik, Alán

2014-11-12

Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfer reactions and for reactions not including multiply charged anions. The errors in standard Gibbs reaction energy estimates are correlated with the charges of the participating molecules. The quantum chemical approach is amenable to systematic improvements and holds potential for providing thermodynamic data for all of metabolism.

Reactivity of fluoroalkanes in reactions of coordinated molecular decomposition

NASA Astrophysics Data System (ADS)

Pokidova, T. S.; Denisov, E. T.

2017-08-01

Experimental results on the coordinated molecular decomposition of RF fluoroalkanes to olefin and HF are analyzed using the model of intersecting parabolas (IPM). The kinetic parameters are calculated to allow estimates of the activation energy ( E) and rate constant ( k) of these reactions, based on enthalpy and IPM algorithms. Parameters E and k are found for the first time for eight RF decomposition reactions. The factors that affect activation energy E of RF decomposition (the enthalpy of the reaction, the electronegativity of the atoms of reaction centers, and the dipole-dipole interaction of polar groups) are determined. The values of E and k for reverse reactions of addition are estimated.

Linking actin networks and cell membrane via a reaction-diffusion-elastic description of nonlinear filopodia initiation.

PubMed

Ben Isaac, Eyal; Manor, Uri; Kachar, Bechara; Yochelis, Arik; Gov, Nir S

2013-08-01

Reaction-diffusion models have been used to describe pattern formation on the cellular scale, and traditionally do not include feedback between cellular shape changes and biochemical reactions. We introduce here a distinct reaction-diffusion-elasticity approach: The reaction-diffusion part describes bistability between two actin orientations, coupled to the elastic energy of the cell membrane deformations. This coupling supports spatially localized patterns, even when such solutions do not exist in the uncoupled self-inhibited reaction-diffusion system. We apply this concept to describe the nonlinear (threshold driven) initiation mechanism of actin-based cellular protrusions and provide support by several experimental observations.

A fluorescence high throughput screening method for the detection of reactive electrophiles as potential skin sensitizers

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

Avonto, Cristina; Chittiboyina, Amar G.; Rua, Diego

2015-12-01

Skin sensitization is an important toxicological end-point in the risk assessment of chemical allergens. Because of the complexity of the biological mechanisms associated with skin sensitization, integrated approaches combining different chemical, biological and in silico methods are recommended to replace conventional animal tests. Chemical methods are intended to characterize the potential of a sensitizer to induce earlier molecular initiating events. The presence of an electrophilic mechanistic domain is considered one of the essential chemical features to covalently bind to the biological target and induce further haptenation processes. Current in chemico assays rely on the quantification of unreacted model nucleophiles aftermore » incubation with the candidate sensitizer. In the current study, a new fluorescence-based method, ‘HTS-DCYA assay’, is proposed. The assay aims at the identification of reactive electrophiles based on their chemical reactivity toward a model fluorescent thiol. The reaction workflow enabled the development of a High Throughput Screening (HTS) method to directly quantify the reaction adducts. The reaction conditions have been optimized to minimize solubility issues, oxidative side reactions and increase the throughput of the assay while minimizing the reaction time, which are common issues with existing methods. Thirty-six chemicals previously classified with LLNA, DPRA or KeratinoSens™ were tested as a proof of concept. Preliminary results gave an estimated 82% accuracy, 78% sensitivity, 90% specificity, comparable to other in chemico methods such as Cys-DPRA. In addition to validated chemicals, six natural products were analyzed and a prediction of their sensitization potential is presented for the first time. - Highlights: • A novel fluorescence-based method to detect electrophilic sensitizers is proposed. • A model fluorescent thiol was used to directly quantify the reaction products. • A discussion of the reaction workflow and critical parameters is presented. • The method could provide a useful tool to complement existing chemical assays.« less

A large eddy simulation scheme for turbulent reacting flows

NASA Technical Reports Server (NTRS)

Gao, Feng

1993-01-01

The recent development of the dynamic subgrid-scale (SGS) model has provided a consistent method for generating localized turbulent mixing models and has opened up great possibilities for applying the large eddy simulation (LES) technique to real world problems. Given the fact that the direct numerical simulation (DNS) can not solve for engineering flow problems in the foreseeable future (Reynolds 1989), the LES is certainly an attractive alternative. It seems only natural to bring this new development in SGS modeling to bear on the reacting flows. The major stumbling block for introducing LES to reacting flow problems has been the proper modeling of the reaction source terms. Various models have been proposed, but none of them has a wide range of applicability. For example, some of the models in combustion have been based on the flamelet assumption which is only valid for relatively fast reactions. Some other models have neglected the effects of chemical reactions on the turbulent mixing time scale, which is certainly not valid for fast and non-isothermal reactions. The probability density function (PDF) method can be usefully employed to deal with the modeling of the reaction source terms. In order to fit into the framework of LES, a new PDF, the large eddy PDF (LEPDF), is introduced. This PDF provides an accurate representation for the filtered chemical source terms and can be readily calculated in the simulations. The details of this scheme are described.

Modeling qRT-PCR dynamics with application to cancer biomarker quantification.

PubMed

Chervoneva, Inna; Freydin, Boris; Hyslop, Terry; Waldman, Scott A

2017-01-01

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is widely used for molecular diagnostics and evaluating prognosis in cancer. The utility of mRNA expression biomarkers relies heavily on the accuracy and precision of quantification, which is still challenging for low abundance transcripts. The critical step for quantification is accurate estimation of efficiency needed for computing a relative qRT-PCR expression. We propose a new approach to estimating qRT-PCR efficiency based on modeling dynamics of polymerase chain reaction amplification. In contrast, only models for fluorescence intensity as a function of polymerase chain reaction cycle have been used so far for quantification. The dynamics of qRT-PCR efficiency is modeled using an ordinary differential equation model, and the fitted ordinary differential equation model is used to obtain effective polymerase chain reaction efficiency estimates needed for efficiency-adjusted quantification. The proposed new qRT-PCR efficiency estimates were used to quantify GUCY2C (Guanylate Cyclase 2C) mRNA expression in the blood of colorectal cancer patients. Time to recurrence and GUCY2C expression ratios were analyzed in a joint model for survival and longitudinal outcomes. The joint model with GUCY2C quantified using the proposed polymerase chain reaction efficiency estimates provided clinically meaningful results for association between time to recurrence and longitudinal trends in GUCY2C expression.

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

Quasiclassical trajectory calculations to evaluate a kinematic constraint on internal energy in suprathreshold collision energy abstraction reactions

NASA Astrophysics Data System (ADS)

Shuman, Nicholas S.; Mihok, Morgan; Fistik, Margaret; Valentini, James J.

2005-08-01

Experimentally observed product quantum state distributions across a wide range of abstraction reactions at suprathreshold collision energies have shown a strong bias against product internal energy. Only a fraction, sometimes quite a small fraction, of the energetically accessible product quantum states are populated. Picconatto et al. [J. Chem. Phys. 114, 1663 (2001)] noted a simple mathematical relationship between the highest-energy rovibrational states observed and the kinematics of the reaction system. They proposed a reaction model based on reaction kinematics that quantitatively explains this behavior. The model is in excellent agreement with measured quantum state distributions. The assumptions of the model invoke detailed characteristics of reactive trajectories at suprathreshold collision energies. Here we test those assumptions using quasiclassical trajectory calculations for the abstraction reactions H +HCl→H2+Cl, D +HCl→HD+Cl, and H +DCl→HD+Cl. Trajectories were run on a potential-energy surface calculated with a London-Eyring-Polyani-Sato function with a localized 3-center term (LEPS-3C) previously shown to accurately reproduce experimentally observed product state distributions for the H +HCl abstraction reaction. The trajectories sample collision energies near threshold and also substantially above it. Although the trajectories demonstrate some aspects of the model, they show that it is not valid. However, the inadequacy of the proposed model does not invalidate the apparent kinematic basis of the observed energy constraint. The present results show that there must be some other molecular behavior rooted in the reaction kinematics that is the explanation and the source of the constraint.

Solution phase and membrane immobilized iron-based free radical reactions: Fundamentals and applications for water treatment

NASA Astrophysics Data System (ADS)

Lewis, Scott Romak

Membrane-based separation processes have been used extensively for drinking water purification, wastewater treatment, and numerous other applications. Reactive membranes synthesized through functionalization of the membrane pores offer enhanced reactivity due to increased surface area at the polymer-solution interface and low diffusion limitations. Oxidative techniques utilizing free radicals have proven effective for both the destruction of toxic organics and non-environmental applications. Most previous work focuses on reactions in the homogeneous phase; however, the immobilization of reactants in membrane pores offers several advantages. The use of polyanions immobilized in a membrane or chelates in solution prevents ferric hydroxide precipitation at near-neutral pH, a common limitation of iron(Fe(II/III))-catalyzed hydrogen peroxide (H 2O2) decomposition. The objectives of this research are to develop a membrane-based platform for the generation of free radicals, degrade toxic organic compounds using this and similar solution-based reactions, degrade toxic organic compounds in droplet form, quantify hydroxyl radical production in these reactions, and develop kinetic models for both processes. In this study, a functionalized membrane containing poly(acrylic acid) (PAA) was used to immobilize iron ions and conduct free radical reactions by permeating H2O2 through the membrane. The membrane's responsive behavior to pH and divalent cations was investigated and modeled. The conversion of Fe(II) to Fe(III) in the membrane and its effect on the decomposition of hydrogen peroxide were monitored and used to develop kinetic models for predicting H2O2 decomposition in these systems. The rate of hydroxyl radical production, and hence contaminant degradation can be varied by changing the residence time, H2O2 concentration, and/or iron loading. Using these membrane-immobilized systems, successful removal of toxic organic compounds, such as pentachlorophenol (PCP), from water was demonstrated. Another toxic organic compound of interest for water treatment applications is trichloroethylene (TCE). Due to its limited solubility in water, a majority of the TCE is often present in the form of droplets. In this study, effective TCE droplet degradation using chelate-modified, iron-catalyzed free radical reactions at near-neutral pH was demonstrated. In order to predict the degradation of aqueous and non-aqueous phase TCE for these reactions, a mathematical model was constructed through the use of droplet mass transfer correlations and free radical reaction kinetics. KEYWORDS: Functionalized membrane, free radical, hydrogen peroxide, chelate-modified, membrane reactor

The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model

NASA Astrophysics Data System (ADS)

Chen, Cathy W. S.; Yang, Ming Jing; Gerlach, Richard; Jim Lo, H.

2006-07-01

In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both the conditional mean and variance equations simultaneously by employing two threshold variables, to analyze the stock markets’ reactions to different types of information (good/bad news) generated from the domestic markets and the US stock market. By applying the four-regime DTGARCH model, this study finds that the interaction between the information of domestic and US stock markets leads to the asymmetric reactions of stock returns and their variability. In addition, this research also finds that the positive autocorrelation reported in the previous studies of financial markets may in fact be mis-specified, and actually due to the local market's positive response to the US stock market.

Effects of macromolecular crowding on biochemical reaction equilibria: a molecular thermodynamic perspective.

PubMed

Hu, Zhongqiao; Jiang, Jianwen; Rajagopalan, Raj

2007-09-01

A molecular thermodynamic model is developed to investigate the effects of macromolecular crowding on biochemical reactions. Three types of reactions, representing protein folding/conformational isomerization, coagulation/coalescence, and polymerization/association, are considered. The reactants, products, and crowders are modeled as coarse-grained spherical particles or as polymer chains, interacting through hard-sphere interactions with or without nonbonded square-well interactions, and the effects of crowder size and chain length as well as product size are examined. The results predicted by this model are consistent with experimentally observed crowding effects based on preferential binding or preferential exclusion of the crowders. Although simple hard-core excluded-volume arguments do in general predict the qualitative aspects of the crowding effects, the results show that other intermolecular interactions can substantially alter the extent of enhancement or reduction of the equilibrium and can even change the direction of the shift. An advantage of the approach presented here is that competing reactions can be incorporated within the model.

A Detailed Chemical Kinetic Model for TNT

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

Pitz, W J; Westbrook, C K

2005-01-13

A detailed chemical kinetic mechanism for 2,4,6-tri-nitrotoluene (TNT) has been developed to explore problems of explosive performance and soot formation during the destruction of munitions. The TNT mechanism treats only gas-phase reactions. Reactions for the decomposition of TNT and for the consumption of intermediate products formed from TNT are assembled based on information from the literature and on current understanding of aromatic chemistry. Thermodynamic properties of intermediate and radical species are estimated by group additivity. Reaction paths are developed based on similar paths for aromatic hydrocarbons. Reaction-rate constant expressions are estimated from the literature and from analogous reactions where themore » rate constants are available. The detailed reaction mechanism for TNT is added to existing reaction mechanisms for RDX and for hydrocarbons. Computed results show the effect of oxygen concentration on the amount of soot precursors that are formed in the combustion of RDX and TNT mixtures in N{sub 2}/O{sub 2} mixtures.« less

The environmental zero-point problem in evolutionary reaction norm modeling.

PubMed

Ergon, Rolf

2018-04-01

There is a potential problem in present quantitative genetics evolutionary modeling based on reaction norms. Such models are state-space models, where the multivariate breeder's equation in some form is used as the state equation that propagates the population state forward in time. These models use the implicit assumption of a constant reference environment, in many cases set to zero. This zero-point is often the environment a population is adapted to, that is, where the expected geometric mean fitness is maximized. Such environmental reference values follow from the state of the population system, and they are thus population properties. The environment the population is adapted to, is, in other words, an internal population property, independent of the external environment. It is only when the external environment coincides with the internal reference environment, or vice versa, that the population is adapted to the current environment. This is formally a result of state-space modeling theory, which is an important theoretical basis for evolutionary modeling. The potential zero-point problem is present in all types of reaction norm models, parametrized as well as function-valued, and the problem does not disappear when the reference environment is set to zero. As the environmental reference values are population characteristics, they ought to be modeled as such. Whether such characteristics are evolvable is an open question, but considering the complexity of evolutionary processes, such evolvability cannot be excluded without good arguments. As a straightforward solution, I propose to model the reference values as evolvable mean traits in their own right, in addition to other reaction norm traits. However, solutions based on an evolvable G matrix are also possible.

Application of Ionic Liquids in Pot-in-Pot Reactions.

PubMed

Çınar, Simge; Schulz, Michael D; Oyola-Reynoso, Stephanie; Bwambok, David K; Gathiaka, Symon M; Thuo, Martin

2016-02-26

Pot-in-pot reactions are designed such that two reaction media (solvents, catalysts and reagents) are isolated from each other by a polymeric membrane similar to matryoshka dolls (Russian nesting dolls). The first reaction is allowed to progress to completion before triggering the second reaction in which all necessary solvents, reactants, or catalysts are placed except for the starting reagent for the target reaction. With the appropriate trigger, in most cases unidirectional flux, the product of the first reaction is introduced to the second medium allowing a second transformation in the same glass reaction pot--albeit separated by a polymeric membrane. The basis of these reaction systems is the controlled selective flux of one reagent over the other components of the first reaction while maintaining steady-state catalyst concentration in the first "pot". The use of ionic liquids as tools to control chemical potential across the polymeric membranes making the first pot is discussed based on standard diffusion models--Fickian and Payne's models. Besides chemical potential, use of ionic liquids as delivery agent for a small amount of a solvent that slightly swells the polymeric membrane, hence increasing flux, is highlighted. This review highlights the critical role ionic liquids play in site-isolation of multiple catalyzed reactions in a standard pot-in-pot reaction.

Pre-clinical methods for detecting the hypersensitivity potential of pharmaceuticals: regulatory considerations.

PubMed

Hastings, K L

2001-02-02

Immune-based systemic hypersensitivities account for a significant number of adverse drug reactions. There appear to be no adequate nonclinical models to predict systemic hypersensitivity to small molecular weight drugs. Although there are very good methods for detecting drugs that can induce contact sensitization, these have not been successfully adapted for prediction of systemic hypersensitivity. Several factors have made the development of adequate models difficult. The term systemic hypersensitivity encompases many discrete immunopathologies. Each type of immunopathology presumably is the result of a specific cluster of immunologic and biochemical phenomena. Certainly other factors, such as genetic predisposition, metabolic idiosyncrasies, and concomitant diseases, further complicate the problem. Therefore, it may be difficult to find common mechanisms upon which to construct adequate models to predict specific types of systemic hypersensitivity reactions. There is some reason to hope, however, that adequate methods could be developed for at least identifying drugs that have the potential to produce signs indicative of a general hazard for immune-based reactions.

Kinetics of patulin degradation in model solution, apple cider and apple juice by ultraviolet radiation.

PubMed

Zhu, Yan; Koutchma, Tatiana; Warriner, Keith; Shao, Suqin; Zhou, Ting

2013-08-01

Patulin is a mycotoxin produced by a wide range of molds involved in fruit spoilage, most commonly by Penicillium expansum and is a health concern for both consumers and manufacturers. The current study evaluated feasibility of monochromatic ultraviolet (UV) radiation at 253.7 nm as a possible commercial application for the reduction of patulin in fresh apple cider and juice. The R-52G MINERALIGHT® UV bench top lamp was used for patulin destruction. It was shown that 56.5%, 87.5%, 94.8% and 98.6% reduction of patulin can be achieved, respectively, in the model solution, apple cider, apple juice without ascorbic acid addition and apple juice with ascorbic acid addition in 2-mm thickness sample initially spiked by 1 mg·L(-1) of patulin after UV exposure for 40 min at UV irradiance of 3.00 mW·cm(-2). A mathematic model to compare the degradation rate and effective UV dose was developed. The effective UV doses that were directly absorbed by patulin for photochemical reaction were 430, 674, 724 and 763 mJ·cm(-3), respectively. The fluence-based decimal reduction time was estimated to 309.3, 31.3, 28.9 and 5.1 mW·cm(-2)·min, respectively, in four media mentioned above. The degradation of patulin followed the first-order reaction model. The time-based and fluence-based reaction rate constants were determined to predict patulin degradation. The time-based reaction rate constant of samples treated in dynamic regime with constant stirring (model solution: 2.95E-4 s(-1), juice: 4.31E-4 s(-1)) were significantly higher than samples treated in static regime (model solution: 2.79E-4 s(-1), juice: 3.49E-4 s(-1), p < 0.05) when applied UV irradiance and sample thickness were consistent. The reaction rate constant of patulin degradation in apple juice was significantly higher than model solution (p < 0.05). Although further investigations are still needed, the results of this study demonstrated that UV radiation may be an effective method for treating patulin-containing apple cider and juice.

Extraterrestrial cold chemistry. A need for a specific database.

NASA Astrophysics Data System (ADS)

Pernot, P.; Carrasco, N.; Dobrijevic, M.; Hébrard, E.; Plessis, S.; Wakelam, V.

2008-09-01

The major resource databases for building chemical models for photochemistry in cold environments are mainly based on those designed for Earth atmospheric chemistry or combustion, in which reaction rates are reported for temperatures typically above 300 K [1,2]. Kinetic data measured at low temperatures are very sparse; for instance, in stateoftheart photochemical models of Titan atmosphere, less than 10% of the rates have been measured in the relevant temperature range (100200 K) [35]. In consequence, photochemical models rely mostly on lowT extrapolations by Arrheniustype laws. There is more and more evidence that this is often inappropriate [6], and low T extrapolations are hindered by very high uncertainty [3] (Fig.1). The predictions of models based on those extrapolations are expected to be very inaccurate [4,7]. We argue that there is not much sense in increasing the complexity of the present models as long as this predictivity issue has not been resolved. Fig. 1 Uncertainty of low temperature extrapolation for the N(2D) +C2H4 reaction rate, from measurements in the range 225 292 K [10], assuming an Arrhenius law (blue line). The sample of rate laws is generated by Monte Carlo uncertainty propagation after a Bayesian Data reAnalysis (BDA) of experimental data. A dialogue between modellers and experimentalists is necessary to improve this situation. Considering the heavy costs of low temperature reaction kinetics experiments, the identification of key reactions has to be based on an optimal strategy to improve the predictivity of photochemical models. This can be achieved by global sensitivity analysis, as illustrated on Titan atmospheric chemistry [8]. The main difficulty of this scheme is that it requires a lot of inputs, mainly the evaluation of uncertainty for extrapolated reaction rates. Although a large part has already been achieved by Hébrard et al. [3], extension and validation requires a group of experts. A new generation of collaborative kinetic database is needed to implement efficiently this scheme. The KIDA project [9], initiated by V. Wakelam for astrochemistry, has been joined by planetologists with similar prospects. EuroPlaNet will contribute to this effort through the organization of comities of experts on specific processes in atmospheric photochemistry.

Applicability of PM3 to transphosphorylation reaction path: Toward designing a minimal ribozyme

NASA Technical Reports Server (NTRS)

Manchester, John I.; Shibata, Masayuki; Setlik, Robert F.; Ornstein, Rick L.; Rein, Robert

1993-01-01

A growing body of evidence shows that RNA can catalyze many of the reactions necessary both for replication of genetic material and the possible transition into the modern protein-based world. However, contemporary ribozymes are too large to have self-assembled from a prebiotic oligonucleotide pool. Still, it is likely that the major features of the earliest ribozymes have been preserved as molecular fossils in the catalytic RNA of today. Therefore, the search for a minimal ribozyme has been aimed at finding the necessary structural features of a modern ribozyme (Beaudry and Joyce, 1990). Both a three-dimensional model and quantum chemical calculations are required to quantitatively determine the effects of structural features of the ribozyme on the reaction it catalyzes. Using this model, quantum chemical calculations must be performed to determine quantitatively the effects of structural features on catalysis. Previous studies of the reaction path have been conducted at the ab initio level, but these methods are limited to small models due to enormous computational requirements. Semiempirical methods have been applied to large systems in the past; however, the accuracy of these methods depends largely on a simple model of the ribozyme-catalyzed reaction, or hydrolysis of phosphoric acid. We find that the results are qualitatively similar to ab initio results using large basis sets. Therefore, PM3 is suitable for studying the reaction path of the ribozyme-catalyzed reaction.

Dynamic partitioning for hybrid simulation of the bistable HIV-1 transactivation network.

PubMed

Griffith, Mark; Courtney, Tod; Peccoud, Jean; Sanders, William H

2006-11-15

The stochastic kinetics of a well-mixed chemical system, governed by the chemical Master equation, can be simulated using the exact methods of Gillespie. However, these methods do not scale well as systems become more complex and larger models are built to include reactions with widely varying rates, since the computational burden of simulation increases with the number of reaction events. Continuous models may provide an approximate solution and are computationally less costly, but they fail to capture the stochastic behavior of small populations of macromolecules. In this article we present a hybrid simulation algorithm that dynamically partitions the system into subsets of continuous and discrete reactions, approximates the continuous reactions deterministically as a system of ordinary differential equations (ODE) and uses a Monte Carlo method for generating discrete reaction events according to a time-dependent propensity. Our approach to partitioning is improved such that we dynamically partition the system of reactions, based on a threshold relative to the distribution of propensities in the discrete subset. We have implemented the hybrid algorithm in an extensible framework, utilizing two rigorous ODE solvers to approximate the continuous reactions, and use an example model to illustrate the accuracy and potential speedup of the algorithm when compared with exact stochastic simulation. Software and benchmark models used for this publication can be made available upon request from the authors.

Using a CBL Unit, a Temperature Sensor, and a Graphing Calculator to Model the Kinetics of Consecutive First-Order Reactions as Safe In-Class Demonstrations

ERIC Educational Resources Information Center

Moore-Russo, Deborah A.; Cortes-Figueroa, Jose E.; Schuman, Michael J.

2006-01-01

The use of Calculator-Based Laboratory (CBL) technology, the graphing calculator, and the cooling and heating of water to model the behavior of consecutive first-order reactions is presented, where B is the reactant, I is the intermediate, and P is the product for an in-class demonstration. The activity demonstrates the spontaneous and consecutive…

Inversed estimation of critical factors for controlling over-prediction of summertime tropospheric O3 over East Asia based of the combination of DDM sensitivity analysis and modeled Green's function method

NASA Astrophysics Data System (ADS)

Itahashi, S.; Yumimoto, K.; Uno, I.; Kim, S.

2012-12-01

Air quality studies based on the chemical transport model have been provided many important results for promoting our knowledge of air pollution phenomena, however, discrepancies between modeling results and observation data are still important issue to overcome. One of the concerning issue would be an over-prediction of summertime tropospheric ozone in remote area of Japan. This problem has been pointed out in the model comparison study of both regional scale (e.g., MICS-Asia) and global scale model (e.g., TH-FTAP). Several reasons for this issue can be listed as, (i) the modeled reproducibility on the penetration of clean oceanic air mass, (ii) correct estimation of the anthropogenic NOx / VOC emissions over East Asia, (iii) the chemical reaction scheme used in model simulation. In this study, we attempt to inverse estimation of some important chemical reactions based on the combining system of DDM (decoupled direct method) sensitivity analysis and modeled Green's function approach. The decoupled direct method (DDM) is an efficient and accurate way of performing sensitivity analysis to model inputs, calculates sensitivity coefficients representing the responsiveness of atmospheric chemical concentrations to perturbations in a model input or parameter. The inverse solutions with the Green's functions are given by a linear, least-squares method but are still robust against nonlinearities, To construct the response matrix (i.e., Green's functions), we can directly use the results of DDM sensitivity analysis. The solution of chemical reaction constants which have relatively large uncertainties are determined with constraints of observed ozone concentration data over the remote area in Japan. Our inversed estimation demonstrated that the underestimation of reaction constant to produce HNO3 (NO2 + OH + M → HNO3 + M) in SAPRC99 chemical scheme, and the inversed results indicated the +29.0 % increment to this reaction. This estimation has good agreement when compared with the CB4 and CB5, and also to the SAPRC07 estimation. For the NO2 photolysis rates, 49.4 % reduction was pronounced. This result indicates the importance of heavy aerosol effect for the change of photolysis rate must be incorporated in the numerical study.

Ab Initio Studies of Shock-Induced Chemical Reactions of Inter-Metallics

NASA Astrophysics Data System (ADS)

Zaharieva, Roussislava; Hanagud, Sathya

2009-06-01

Shock-induced and shock assisted chemical reactions of intermetallic mixtures are studied by many researchers, using both experimental and theoretical techniques. The theoretical studies are primarily at continuum scales. The model frameworks include mixture theories and meso-scale models of grains of porous mixtures. The reaction models vary from equilibrium thermodynamic model to several non-equilibrium thermodynamic models. The shock-effects are primarily studied using appropriate conservation equations and numerical techniques to integrate the equations. All these models require material constants from experiments and estimates of transition states. Thus, the objective of this paper is to present studies based on ab initio techniques. The ab inito studies, to date, use ab inito molecular dynamics. This paper presents a study that uses shock pressures, and associated temperatures as starting variables. Then intermetallic mixtures are modeled as slabs. The required shock stresses are created by straining the lattice. Then, ab initio binding energy calculations are used to examine the stability of the reactions. Binding energies are obtained for different strain components super imposed on uniform compression and finite temperatures. Then, vibrational frequencies and nudge elastic band techniques are used to study reactivity and transition states. Examples include Ni and Al.

Aerosol Fragmentation Driven by Coupling of Acid-Base and Free-Radical Chemistry in the Heterogeneous Oxidation of Aqueous Citric Acid by OH Radicals.

PubMed

Liu, Matthew J; Wiegel, Aaron A; Wilson, Kevin R; Houle, Frances A

2017-08-10

A key uncertainty in the heterogeneous oxidation of carboxylic acids by hydroxyl radicals (OH) in aqueous-phase aerosol is how the free-radical reaction pathways might be altered by acid-base chemistry. In particular, if acid-base reactions occur concurrently with acyloxy radical formation and unimolecular decomposition of alkoxy radicals, there is a possibility that differences in reaction pathways impact the partitioning of organic carbon between the gas and aqueous phases. To examine these questions, a kinetic model is developed for the OH-initiated oxidation of citric acid aerosol at high relative humidity. The reaction scheme, containing both free-radical and acid-base elementary reaction steps with physically validated rate coefficients, accurately predicts the experimentally observed molecular composition, particle size, and average elemental composition of the aerosol upon oxidation. The difference between the two reaction channels centers on the reactivity of carboxylic acid groups. Free-radical reactions mainly add functional groups to the carbon skeleton of neutral citric acid, because carboxylic acid moieties deactivate the unimolecular fragmentation of alkoxy radicals. In contrast, the conjugate carboxylate groups originating from acid-base equilibria activate both acyloxy radical formation and carbon-carbon bond scission of alkoxy radicals, leading to the formation of low molecular weight, highly oxidized products such as oxalic and mesoxalic acid. Subsequent hydration of carbonyl groups in the oxidized products increases the aerosol hygroscopicity and accelerates the substantial water uptake and volume growth that accompany oxidation. These results frame the oxidative lifecycle of atmospheric aerosol: it is governed by feedbacks between reactions that first increase the particle oxidation state, then eventually promote water uptake and acid-base chemistry. When coupled to free-radical reactions, acid-base channels lead to formation of low molecular weight gas-phase reaction products and decreasing particle size.

Aerosol Fragmentation Driven by Coupling of Acid–Base and Free-Radical Chemistry in the Heterogeneous Oxidation of Aqueous Citric Acid by OH Radicals

DOE PAGES

Liu, Matthew J.; Wiegel, Aaron A.; Wilson, Kevin R.; ...

2017-07-14

A key uncertainty in the heterogeneous oxidation of carboxylic acids by hydroxyl radicals (OH) in aqueous-phase aerosol is how the free-radical reaction pathways might be altered by acid-base chemistry. In particular, if acid-base reactions occur concurrently with acyloxy radical formation and unimolecular decomposition of alkoxy radicals, there is a possibility that differences in reaction pathways impact the partitioning of organic carbon between the gas and aqueous phases. To examine these questions, a kinetic model is developed for the OH-initiated oxidation of citric acid aerosol at high relative humidity. The reaction scheme, containing both free-radical and acid-base elementary reaction steps withmore » physically validated rate coefficients, accurately predicts the experimentally observed molecular composition, particle size, and average elemental composition of the aerosol upon oxidation. The difference between the two reaction channels centers on the reactivity of carboxylic acid groups. Free-radical reactions mainly add functional groups to the carbon skeleton of neutral citric acid, because carboxylic acid moieties deactivate the unimolecular fragmentation of alkoxy radicals. In contrast, the conjugate carboxylate groups originating from acid-base equilibria activate both acyloxy radical formation and carbon-carbon bond scission of alkoxy radicals, leading to the formation of low molecular weight, highly oxidized products such as oxalic and mesoxalic acid. Subsequent hydration of carbonyl groups in the oxidized products increases the aerosol hygroscopicity and accelerates the substantial water uptake and volume growth that accompany oxidation. These results frame the oxidative lifecycle of atmospheric aerosol: it is governed by feedbacks between reactions that first increase the particle oxidation state, then eventually promote water uptake and acid-base chemistry. When coupled to free-radical reactions, acid-base channels lead to formation of low molecular weight gas-phase reaction products and decreasing particle size.« less

Aerosol Fragmentation Driven by Coupling of Acid–Base and Free-Radical Chemistry in the Heterogeneous Oxidation of Aqueous Citric Acid by OH Radicals

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

Liu, Matthew J.; Wiegel, Aaron A.; Wilson, Kevin R.

A key uncertainty in the heterogeneous oxidation of carboxylic acids by hydroxyl radicals (OH) in aqueous-phase aerosol is how the free-radical reaction pathways might be altered by acid-base chemistry. In particular, if acid-base reactions occur concurrently with acyloxy radical formation and unimolecular decomposition of alkoxy radicals, there is a possibility that differences in reaction pathways impact the partitioning of organic carbon between the gas and aqueous phases. To examine these questions, a kinetic model is developed for the OH-initiated oxidation of citric acid aerosol at high relative humidity. The reaction scheme, containing both free-radical and acid-base elementary reaction steps withmore » physically validated rate coefficients, accurately predicts the experimentally observed molecular composition, particle size, and average elemental composition of the aerosol upon oxidation. The difference between the two reaction channels centers on the reactivity of carboxylic acid groups. Free-radical reactions mainly add functional groups to the carbon skeleton of neutral citric acid, because carboxylic acid moieties deactivate the unimolecular fragmentation of alkoxy radicals. In contrast, the conjugate carboxylate groups originating from acid-base equilibria activate both acyloxy radical formation and carbon-carbon bond scission of alkoxy radicals, leading to the formation of low molecular weight, highly oxidized products such as oxalic and mesoxalic acid. Subsequent hydration of carbonyl groups in the oxidized products increases the aerosol hygroscopicity and accelerates the substantial water uptake and volume growth that accompany oxidation. These results frame the oxidative lifecycle of atmospheric aerosol: it is governed by feedbacks between reactions that first increase the particle oxidation state, then eventually promote water uptake and acid-base chemistry. When coupled to free-radical reactions, acid-base channels lead to formation of low molecular weight gas-phase reaction products and decreasing particle size.« less

The Stochastic Early Reaction, Inhibition, and late Action (SERIA) model for antisaccades

PubMed Central

2017-01-01

The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the early decision process postulated by the SERIA model is, to a large extent, insensitive to the cue presented in a single trial. Finally, we use parameter estimates to demonstrate that changes in reaction time and error rate due to the probability of a trial type (pro- or antisaccade) are best explained by faster or slower inhibition and the probability of generating late voluntary prosaccades. PMID:28767650

Kinetics of the creatine kinase reaction in neonatal rabbit heart: An empirical analysis of the rate equation

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

McAuliffe, J.J.; Perry, S.B.; Brooks, E.E.

1991-03-12

Here the authors define the kinetics of the creatine kinase (CK) reaction in an intact mammalian heart containing the full rnage of CK isoenzymes. Previously derived kinetic constants were refit for the reaction occurring at 37C. Steady-state metabolite concentrations from {sup 31}P NMR and standard biochemical techniques were determined. {sup 31}P magnetization transfer data were obtained to determine unidirectional creatine kinase fluxes in hearts with differing total creatine contents and differing mitochondrial CK activities during KCl arrest and isovolumic work for both the forward reaction (MgATP synthesis) and reverse reaction (phosphocreatine synthesis). The NMR kinetic data and substrate concentrations datamore » were used in conjunction with a kinetic model based on MM-CK in solution to determine the applicability of the solution-based kinetic models to the CK kinetics of the intact heart. The results indicated that no single set of rate equation constants could describe both the KCl-arrested and working hearts. Analysis of the results indicated that the CK reaction is rate limited in the direction of ATP synthesis, the size of the guanidino substrate pool drives the measured CK flux in the intact heart, and during isovolumic work, the CK reaction operates under saturating conditions; that is, the substrate concentrations are at least 2-fold greater than the K{sub m} or K{sub im} for each substrate. However, during KCl arrest the reaction does not operate under saturating conditions and the CK reaction velocity is strongly influenced by the guanidino substrate pool size.« less

Ab Initio-Based Kinetic Modeling for the Design of Molecular Catalysts: The Case of H 2 Production Electrocatalysts

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

Ho, Ming-Hsun; Rousseau, Roger; Roberts, John A. S.

2015-09-04

Design of fast, efficient electrocatalysts for energy production and energy utilization requires a systematic approach to predict and tune the energetics of reaction intermediates and the kinetic barriers between them as well as to tune reaction conditions (e.g., concentration of reactants, acidity of the reaction medium, and applied electric potential). Thermodynamics schemes based on the knowledge of pKa values, hydride donor ability, redox potentials, and other relevant thermodynamic properties have been demonstrated to be very effective for exploring possible reaction pathways. We seek to identify high-energy intermediates, which may represent a catalytic bottleneck, and low-energy intermediates, which may represent amore » thermodynamic sink. In this study, working on a well-established Ni-based bioinspired electrocatalyst for H2 production, we performed a detailed kinetic analysis of the catalytic pathways to assess the limitations of our current (standard state) thermodynamic analysis with respect to prediction of optimal catalyst performance. To this end, we developed a microkinetic model based on extensive ab initio simulations. The model was validated against available experimental data, and it reproduces remarkably well the observed turnover rate as a function of the acid concentration and catalytic conditions, providing valuable information on the main factors limiting catalysis. Using this kinetic analysis as a reference, we show that indeed a purely thermodynamic analysis of the possible reaction pathways provides us with valuable information, such as a qualitative picture of the species involved during catalysis, identification of the possible branching points, and the origin of the observed overpotential, which are critical insights for electrocatalyst design. However, a significant limitation of this approach is understanding how these insights relate to rate, which is an equally critical piece of information. Taking our analysis a step further, we show that the kinetic model can easily be extended to different catalytic conditions by using linear free energy relationships for activation barriers based on simple thermodynamics quantities, such as pKa values. We also outline a possible procedure to extend it to other catalytic platforms, making it a general and effective way to design catalysts with improved performance.« less

IDENTIFICATION OF CASO4 FORMED BY REACTION OF CAO AND SO2

EPA Science Inventory

The injection of calcium-based sorbents into coal-fired boilers for reaction with, and reduction in the levels of, sulfur dioxide (SO2) in the flue gas has undergone considerable research and development. Significant effort has also been made in developing models for the overall ...

Theoretical modeling of PEB procedure on EUV resist using FDM formulation

NASA Astrophysics Data System (ADS)

Kim, Muyoung; Moon, Junghwan; Choi, Joonmyung; Lee, Byunghoon; Jeong, Changyoung; Kim, Heebom; Cho, Maenghyo

2018-03-01

Semiconductor manufacturing industry has reduced the size of wafer for enhanced productivity and performance, and Extreme Ultraviolet (EUV) light source is considered as a promising solution for downsizing. A series of EUV lithography procedures contain complex photo-chemical reaction on photoresist, and it causes technical difficulties on constructing theoretical framework which facilitates rigorous investigation of underlying mechanism. Thus, we formulated finite difference method (FDM) model of post exposure bake (PEB) process on positive chemically amplified resist (CAR), and it involved acid diffusion coupled-deprotection reaction. The model is based on Fick's second law and first-order chemical reaction rate law for diffusion and deprotection, respectively. Two kinetic parameters, diffusion coefficient of acid and rate constant of deprotection, which were obtained by experiment and atomic scale simulation were applied to the model. As a result, we obtained time evolutional protecting ratio of each functional group in resist monomer which can be used to predict resulting polymer morphology after overall chemical reactions. This achievement will be the cornerstone of multiscale modeling which provides fundamental understanding on important factors for EUV performance and rational design of the next-generation photoresist.

Finite element code development for modeling detonation of HMX composites

NASA Astrophysics Data System (ADS)

Duran, Adam; Sundararaghavan, Veera

2015-06-01

In this talk, we present a hydrodynamics code for modeling shock and detonation waves in HMX. A stable efficient solution strategy based on a Taylor-Galerkin finite element (FE) discretization was developed to solve the reactive Euler equations. In our code, well calibrated equations of state for the solid unreacted material and gaseous reaction products have been implemented, along with a chemical reaction scheme and a mixing rule to define the properties of partially reacted states. A linear Gruneisen equation of state was employed for the unreacted HMX calibrated from experiments. The JWL form was used to model the EOS of gaseous reaction products. It is assumed that the unreacted explosive and reaction products are in both pressure and temperature equilibrium. The overall specific volume and internal energy was computed using the rule of mixtures. Arrhenius kinetics scheme was integrated to model the chemical reactions. A locally controlled dissipation was introduced that induces a non-oscillatory stabilized scheme for the shock front. The FE model was validated using analytical solutions for sod shock and ZND strong detonation models and then used to perform 2D and 3D shock simulations. We will present benchmark problems for geometries in which a single HMX crystal is subjected to a shock condition. Our current progress towards developing microstructural models of HMX/binder composite will also be discussed.

Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model.

PubMed

Neic, Aurel; Campos, Fernando O; Prassl, Anton J; Niederer, Steven A; Bishop, Martin J; Vigmond, Edward J; Plank, Gernot

2017-10-01

Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.

Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model

NASA Astrophysics Data System (ADS)

Neic, Aurel; Campos, Fernando O.; Prassl, Anton J.; Niederer, Steven A.; Bishop, Martin J.; Vigmond, Edward J.; Plank, Gernot

2017-10-01

Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Impact of phloretin and phloridzin on the formation of Maillard reaction products in aqueous models composed of glucose and L-lysine or its derivatives.

PubMed

Ma, Jinyu; Peng, Xiaofang; Ng, Kwan-Ming; Che, Chi-Ming; Wang, Mingfu

2012-02-01

In the present study, the effects of phloretin and phloridzin on the formation of Maillard reaction products in a lysine-glucose model with different reactant ratios were systematically investigated. In terms of the formation of Maillard-type volatiles, phloretin and phloridzin treatmen could significantly reduce their generation, where the effects depend on the ratio of lysine to glucose used in the model systems. Phloretin and phloridzin could also affect the colour development of Maillard reactions; especially phloretin, which could significantly promote the formation of brown products in the system with the lowest ratio of lysine to glucose. Based on the carbon module labelling (CAMOLA) technique and HPLC-DAD-ESI/MS analysis, it was found that phloretin and phloridzin could actively participate in the Maillard reaction and directly react with different reactive carbonyl species. The effect of phloretin and phloridzin treatment in both N(α)-acetyllysine-glucose (AC-glu), and N-acetyl-gly-lys methyl ester acetate salt-glucose (AG-glu) model systems, which are close to the Maillard reactions occurring in real food, where the free amino groups of lysine residues were considered as the reactive site, were further investigated. Similar impacts on the formation of Maillard-type volatiles and brown products as in the lysine-glucose models were observed which can also be explained by the capability of phloretin and phloridzin to quench sugar fragments formed in these model reactions.

Theoretical and computer models of detonation in solid explosives

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

Tarver, C.M.; Urtiew, P.A.

1997-10-01

Recent experimental and theoretical advances in understanding energy transfer and chemical kinetics have led to improved models of detonation waves in solid explosives. The Nonequilibrium Zeldovich - von Neumann - Doring (NEZND) model is supported by picosecond laser experiments and molecular dynamics simulations of the multiphonon up-pumping and internal vibrational energy redistribution (IVR) processes by which the unreacted explosive molecules are excited to the transition state(s) preceding reaction behind the leading shock front(s). High temperature, high density transition state theory calculates the induction times measured by laser interferometric techniques. Exothermic chain reactions form product gases in highly excited vibrational states,more » which have been demonstrated to rapidly equilibrate via supercollisions. Embedded gauge and Fabry-Perot techniques measure the rates of reaction product expansion as thermal and chemical equilibrium is approached. Detonation reaction zone lengths in carbon-rich condensed phase explosives depend on the relatively slow formation of solid graphite or diamond. The Ignition and Growth reactive flow model based on pressure dependent reaction rates and Jones-Wilkins-Lee (JWL) equations of state has reproduced this nanosecond time resolved experimental data and thus has yielded accurate average reaction zone descriptions in one-, two- and three- dimensional hydrodynamic code calculations. The next generation reactive flow model requires improved equations of state and temperature dependent chemical kinetics. Such a model is being developed for the ALE3D hydrodynamic code, in which heat transfer and Arrhenius kinetics are intimately linked to the hydrodynamics.« less

High Temperature Degradation Mechanisms in Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Cunningham, Ronan A.

1996-01-01

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using a coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Organic functional group transformations in water at elevated temperature and pressure: Reversibility, reactivity, and mechanisms

NASA Astrophysics Data System (ADS)

Shipp, Jessie; Gould, Ian R.; Herckes, Pierre; Shock, Everett L.; Williams, Lynda B.; Hartnett, Hilairy E.

2013-03-01

Many transformation reactions involving hydrocarbons occur in the presence of H2O in hydrothermal systems and deep sedimentary systems. We investigate these reactions using laboratory-based organic chemistry experiments at high temperature and pressure (300 °C and 100 MPa). Organic functional group transformation reactions using model organic compounds based on cyclohexane with one or two methyl groups provided regio- and stereochemical markers that yield information about reversibility and reaction mechanisms. We found rapidly reversible interconversion between alkanes, alkenes, dienes, alcohols, ketones, and enones. The alkane-to-ketone reactions were not only completely reversible, but also exhibited such extensive reversibility that any of the functional groups along the reaction path (alcohol, ketone, and even the diene) could be used as the reactant and form all the other groups as products. There was also a propensity for these ring-based structures to dehydrogenate; presumably from the alkene, through a diene, to an aromatic ring. The product suites provide strong evidence that water behaved as a reactant and the various functional groups showed differing degrees of reactivity. Mechanistically-revealing products indicated reaction mechanisms that involve carbon-centered cation intermediates. This work therefore demonstrates that a wide range of organic compound types can be generated by abiotic reactions at hydrothermal conditions.

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.

Stochastic flux analysis of chemical reaction networks

PubMed Central

2013-01-01

Background Chemical reaction networks provide an abstraction scheme for a broad range of models in biology and ecology. The two common means for simulating these networks are the deterministic and the stochastic approaches. The traditional deterministic approach, based on differential equations, enjoys a rich set of analysis techniques, including a treatment of reaction fluxes. However, the discrete stochastic simulations, which provide advantages in some cases, lack a quantitative treatment of network fluxes. Results We describe a method for flux analysis of chemical reaction networks, where flux is given by the flow of species between reactions in stochastic simulations of the network. Extending discrete event simulation algorithms, our method constructs several data structures, and thereby reveals a variety of statistics about resource creation and consumption during the simulation. We use these structures to quantify the causal interdependence and relative importance of the reactions at arbitrary time intervals with respect to the network fluxes. This allows us to construct reduced networks that have the same flux-behavior, and compare these networks, also with respect to their time series. We demonstrate our approach on an extended example based on a published ODE model of the same network, that is, Rho GTP-binding proteins, and on other models from biology and ecology. Conclusions We provide a fully stochastic treatment of flux analysis. As in deterministic analysis, our method delivers the network behavior in terms of species transformations. Moreover, our stochastic analysis can be applied, not only at steady state, but at arbitrary time intervals, and used to identify the flow of specific species between specific reactions. Our cases study of Rho GTP-binding proteins reveals the role played by the cyclic reverse fluxes in tuning the behavior of this network. PMID:24314153

Stochastic flux analysis of chemical reaction networks.

PubMed

Kahramanoğulları, Ozan; Lynch, James F

2013-12-07

Chemical reaction networks provide an abstraction scheme for a broad range of models in biology and ecology. The two common means for simulating these networks are the deterministic and the stochastic approaches. The traditional deterministic approach, based on differential equations, enjoys a rich set of analysis techniques, including a treatment of reaction fluxes. However, the discrete stochastic simulations, which provide advantages in some cases, lack a quantitative treatment of network fluxes. We describe a method for flux analysis of chemical reaction networks, where flux is given by the flow of species between reactions in stochastic simulations of the network. Extending discrete event simulation algorithms, our method constructs several data structures, and thereby reveals a variety of statistics about resource creation and consumption during the simulation. We use these structures to quantify the causal interdependence and relative importance of the reactions at arbitrary time intervals with respect to the network fluxes. This allows us to construct reduced networks that have the same flux-behavior, and compare these networks, also with respect to their time series. We demonstrate our approach on an extended example based on a published ODE model of the same network, that is, Rho GTP-binding proteins, and on other models from biology and ecology. We provide a fully stochastic treatment of flux analysis. As in deterministic analysis, our method delivers the network behavior in terms of species transformations. Moreover, our stochastic analysis can be applied, not only at steady state, but at arbitrary time intervals, and used to identify the flow of specific species between specific reactions. Our cases study of Rho GTP-binding proteins reveals the role played by the cyclic reverse fluxes in tuning the behavior of this network.

Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison

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

Ovacik, Meric A.; Androulakis, Ioannis P., E-mail: yannis@rci.rutgers.edu; Biomedical Engineering Department, Rutgers University, Piscataway, NJ 08854

2013-09-15

Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogeneticmore » relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy.« less

One-electron oxidation reactions of purine and pyrimidine bases in cellular DNA

PubMed Central

Cadet, Jean; Wagner, J. Richard; Shafirovich, Vladimir; Geacintov, Nicholas E.

2014-01-01

Purpose The aim of this survey is to critically review the available information on one-electron oxidation reactions of nucleobases in cellular DNA with emphasis on damage induced through the transient generation of purine and pyrimidine radical cations. Since the indirect effect of ionizing radiation mediated by hydroxyl radical is predominant in cells, efforts have been made to selectively ionize bases using suitable one-electron oxidants that consist among others of high intensity UVC laser pulses. Thus, the main oxidation product in cellular DNA was found to be 8-oxo-7,8-dihydroguanine as a result of direct bi-photonic ionization of guanine bases and indirect formation of guanine radical cations through hole transfer reactions from other base radical cations. The formation of 8-oxo-7,8-dihydroguanine and other purine and pyrimidine degradation products was rationalized in terms of the initial generation of related radical cations followed by either hydration or deprotonation reactions in agreement with mechanistic pathways inferred from detailed mechanistic studies. The guanine radical cation has been shown to be implicated in three other nucleophilic additions that give rise to DNA-protein and DNA-DNA cross-links in model systems. Evidence was recently provided for the occurrence of these three reactions in cellular DNA. Conclusion There is growing evidence that one-electron oxidation reactions of nucleobases whose mechanisms have been characterized in model studies involving aqueous solutions take place in a similar way in cells. It may also be pointed out that the above cross-linked lesions are only produced from the guanine radical cation and may be considered as diagnostic products of the direct effect of ionizing radiation. PMID:24369822

One-electron oxidation reactions of purine and pyrimidine bases in cellular DNA.

PubMed

Cadet, Jean; Wagner, J Richard; Shafirovich, Vladimir; Geacintov, Nicholas E

2014-06-01

The aim of this survey is to critically review the available information on one-electron oxidation reactions of nucleobases in cellular DNA with emphasis on damage induced through the transient generation of purine and pyrimidine radical cations. Since the indirect effect of ionizing radiation mediated by hydroxyl radical is predominant in cells, efforts have been made to selectively ionize bases using suitable one-electron oxidants that consist among others of high intensity UVC laser pulses. Thus, the main oxidation product in cellular DNA was found to be 8-oxo-7,8-dihydroguanine as a result of direct bi-photonic ionization of guanine bases and indirect formation of guanine radical cations through hole transfer reactions from other base radical cations. The formation of 8-oxo-7,8-dihydroguanine and other purine and pyrimidine degradation products was rationalized in terms of the initial generation of related radical cations followed by either hydration or deprotonation reactions in agreement with mechanistic pathways inferred from detailed mechanistic studies. The guanine radical cation has been shown to be implicated in three other nucleophilic additions that give rise to DNA-protein and DNA-DNA cross-links in model systems. Evidence was recently provided for the occurrence of these three reactions in cellular DNA. There is growing evidence that one-electron oxidation reactions of nucleobases whose mechanisms have been characterized in model studies involving aqueous solutions take place in a similar way in cells. It may also be pointed out that the above cross-linked lesions are only produced from the guanine radical cation and may be considered as diagnostic products of the direct effect of ionizing radiation.

Development of a model and computer code to describe solar grade silicon production processes

NASA Technical Reports Server (NTRS)

Srivastava, R.; Gould, R. K.

1979-01-01

Mathematical models, and computer codes based on these models were developed which allow prediction of the product distribution in chemical reactors in which gaseous silicon compounds are converted to condensed phase silicon. The reactors to be modeled are flow reactors in which silane or one of the halogenated silanes is thermally decomposed or reacted with an alkali metal, H2 or H atoms. Because the product of interest is particulate silicon, processes which must be modeled, in addition to mixing and reaction of gas-phase reactants, include the nucleation and growth of condensed Si via coagulation, condensation, and heterogeneous reaction.

Catalytic effects of inorganic acids on the decomposition of ammonium nitrate.

PubMed

Sun, Jinhua; Sun, Zhanhui; Wang, Qingsong; Ding, Hui; Wang, Tong; Jiang, Chuansheng

2005-12-09

In order to evaluate the catalytic effects of inorganic acids on the decomposition of ammonium nitrate (AN), the heat releases of decomposition or reaction of pure AN and its mixtures with inorganic acids were analyzed by a heat flux calorimeter C80. Through the experiments, the different reaction mechanisms of AN and its mixtures were analyzed. The chemical reaction kinetic parameters such as reaction order, activation energy and frequency factor were calculated with the C80 experimental results for different samples. Based on these parameters and the thermal runaway models (Semenov and Frank-Kamenestkii model), the self-accelerating decomposition temperatures (SADTs) of AN and its mixtures were calculated and compared. The results show that the mixtures of AN with acid are more unsteady than pure AN. The AN decomposition reaction is catalyzed by acid. The calculated SADTs of AN mixtures with acid are much lower than that of pure AN.

Multiple dimensions of attitudes about homosexuality: development of a multifaceted scale measuring attitudes toward homosexuality.

PubMed

Adolfsen, Anna; Iedema, Jurjen; Keuzenkamp, Saskia

2010-01-01

Attitudes toward homosexuality are complex. To get a comprehensive view on the attitudes of people, different dimensions need to be included in research. Based on a review of the literature, we distinguish five dimensions: acceptance of homosexuality in a general sense; attitude toward equal rights; reactions to homosexuality "at close quarters"; reactions to homosexuality in public; and so-called modern homonegativity. In a study on a representative sample of Dutch Defence personnel (N = 1,607) we tested this model. Structural equation modeling of several items measuring the attitude toward homosexuality offers a six factor solution. These six factors are more or less comparable to the five dimensions we distinguished. The dimension "reactions to homosexuality at close quarters" is, however, empirically split in a dimension on affective reactions to homosexuality and homosexual persons in general and a dimension on affective reaction to homosexual friends or acquaintances.

Heterogeneous reactions in aircraft gas turbine engines

NASA Astrophysics Data System (ADS)

Brown, R. C.; Miake-Lye, R. C.; Lukachko, S. P.; Waitz, I. A.

2002-05-01

One-dimensional flow models and unity probability heterogeneous rate parameters are used to estimate the maximum effect of heterogeneous reactions on trace species evolution in aircraft gas turbines. The analysis includes reactions on soot particulates and turbine/nozzle material surfaces. Results for a representative advanced subsonic engine indicate the net change in reactant mixing ratios due to heterogeneous reactions is <10-6 for O2, CO2, and H2O, and <10-10 for minor combustion products such as SO2 and NO2. The change in the mixing ratios relative to the initial values is <0.01%. Since these estimates are based on heterogeneous reaction probabilities of unity, the actual changes will be even lower. Thus, heterogeneous chemistry within the engine cannot explain the high conversion of SO2 to SO3 which some wake models require to explain the observed levels of volatile aerosols. Furthermore, turbine heterogeneous processes will not effect exhaust NOx or NOy levels.

Preparation of functional polyamine scaffolds via Mitsunobu post-polymerization modification reactions.

PubMed

Kakuchi, Ryohei; Theato, Patrick

2014-03-01

A Mitsunobu reaction of trifluoroacetamide (TFA amide) and alcohols is used in a postpolymerization modification process. The reaction is conducted on polystyrene (PSt) bearing 20 mol% TFA amide groups with 4-methyl benzyl alcohol in the presence of a N,N,N′,N ′-tetramethylazodicarboxamide and tributylphosphine as mediators. The Mitsunobu reaction on polymer proceeds efficiently, as confirmed by the obvious precipitation generation during the reaction and the conversion of TFA amide moiety reached 88.6% confirmed by 19 F NMR measurement, yielding PSt bearing tertiary TFA amide moieties. The obtained polymers featuring tertiary TFA amide moieties are deprotected in the presence of tetrabutylammonium hydroxide as a base to afford corresponding polymers featuring functionalized polyamine scaffolds with 92.5% conversion. In addition, the precise structural assignment is proven by synthesis and analysis of the model monomeric compounds and the respective model polymers.

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

Alvarez-Ramirez, J.; Aguilar, R.; Lopez-Isunza, F.

FCC processes involve complex interactive dynamics which are difficult to operate and control as well as poorly known reaction kinetics. This work concerns the synthesis of temperature controllers for FCC units. The problem is addressed first for the case where perfect knowledge of the reaction kinetics is assumed, leading to an input-output linearizing state feedback. However, in most industrial FCC units, perfect knowledge of reaction kinetics and composition measurements is not available. To address the problem of robustness against uncertainties in the reaction kinetics, an adaptive model-based nonlinear controller with simplified reaction models is presented. The adaptive strategy makes usemore » of estimates of uncertainties derived from calorimetric (energy) balances. The resulting controller is similar in form to standard input-output linearizing controllers and can be tuned analogously. Alternatively, the controller can be tuned using a single gain parameter and is computationally efficient. The performance of the closed-loop system and the controller design procedure are shown with simulations.« less

Oxygen Diffusion and Reaction Kinetics in Continuous Fiber Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Halbig, Michael C.; Eckel, Andrew J.; Cawley, James D.

1999-01-01

Previous stressed oxidation tests of C/SiC composites at elevated temperatures (350 C to 1500 C) and sustained stresses (69 MPa and 172 MPa) have led to the development of a finite difference cracked matrix model. The times to failure in the samples suggest oxidation occurred in two kinetic regimes defined by the rate controlling mechanisms (i.e. diffusion controlled and reaction controlled kinetics). Microstructural analysis revealed preferential oxidation along as-fabricated, matrix microcracks and also suggested two regimes of oxidation kinetics dependent on the oxidation temperature. Based on experimental results, observation, and theory, a finite difference model was developed. The model simulates the diffusion of oxygen into a matrix crack bridged by carbon fibers. The model facilitates the study of the relative importance of temperature, the reaction rate constant, and the diffusion coefficient on the overall oxidation kinetics.

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multizone Reaction Kinetics: Modeling of Decarburization

NASA Astrophysics Data System (ADS)

Rout, Bapin Kumar; Brooks, Geoffrey; Akbar Rhamdhani, M.; Li, Zushu; Schrama, Frank N. H.; Overbosch, Aart

2018-06-01

In a previous study by the authors (Rout et al. in Metall Mater Trans B 49:537-557, 2018), a dynamic model for the BOF, employing the concept of multizone kinetics was developed. In the current study, the kinetics of decarburization reaction is investigated. The jet impact and slag-metal emulsion zones were identified to be primary zones for carbon oxidation. The dynamic parameters in the rate equation of decarburization such as residence time of metal drops in the emulsion, interfacial area evolution, initial size, and the effects of surface-active oxides have been included in the kinetic rate equation of the metal droplet. A modified mass-transfer coefficient based on the ideal Langmuir adsorption equilibrium has been proposed to take into account the surface blockage effects of SiO2 and P2O5 in slag on the decarburization kinetics of a metal droplet in the emulsion. Further, a size distribution function has been included in the rate equation to evaluate the effect of droplet size on reaction kinetics. The mathematical simulation indicates that decarburization of the droplet in the emulsion is a strong function of the initial size and residence time. A modified droplet generation rate proposed previously by the authors has been used to estimate the total decarburization rate by slag-metal emulsion. The model's prediction shows that about 76 pct of total carbon is removed by reactions in the emulsion, and the remaining is removed by reactions at the jet impact zone. The predicted bath carbon by the model has been found to be in good agreement with the industrially measured data.

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multizone Reaction Kinetics: Modeling of Decarburization

NASA Astrophysics Data System (ADS)

Rout, Bapin Kumar; Brooks, Geoffrey; Akbar Rhamdhani, M.; Li, Zushu; Schrama, Frank N. H.; Overbosch, Aart

2018-03-01

In a previous study by the authors (Rout et al. in Metall Mater Trans B 49:537-557, 2018), a dynamic model for the BOF, employing the concept of multizone kinetics was developed. In the current study, the kinetics of decarburization reaction is investigated. The jet impact and slag-metal emulsion zones were identified to be primary zones for carbon oxidation. The dynamic parameters in the rate equation of decarburization such as residence time of metal drops in the emulsion, interfacial area evolution, initial size, and the effects of surface-active oxides have been included in the kinetic rate equation of the metal droplet. A modified mass-transfer coefficient based on the ideal Langmuir adsorption equilibrium has been proposed to take into account the surface blockage effects of SiO2 and P2O5 in slag on the decarburization kinetics of a metal droplet in the emulsion. Further, a size distribution function has been included in the rate equation to evaluate the effect of droplet size on reaction kinetics. The mathematical simulation indicates that decarburization of the droplet in the emulsion is a strong function of the initial size and residence time. A modified droplet generation rate proposed previously by the authors has been used to estimate the total decarburization rate by slag-metal emulsion. The model's prediction shows that about 76 pct of total carbon is removed by reactions in the emulsion, and the remaining is removed by reactions at the jet impact zone. The predicted bath carbon by the model has been found to be in good agreement with the industrially measured data.

Learning to predict chemical reactions.

PubMed

Kayala, Matthew A; Azencott, Chloé-Agathe; Chen, Jonathan H; Baldi, Pierre

2011-09-26

Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry data set consisting of 1630 full multistep reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top-ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of nonproductive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system is generalizable, making reasonable predictions over reactants and conditions which the rule-based expert does not handle. A web interface to the machine learning based mechanistic reaction predictor is accessible through our chemoinformatics portal ( http://cdb.ics.uci.edu) under the Toolkits section.

Learning to Predict Chemical Reactions

PubMed Central

Kayala, Matthew A.; Azencott, Chloé-Agathe; Chen, Jonathan H.

2011-01-01

Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles respectively are not high-throughput, are not generalizable or scalable, or lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry dataset consisting of 1630 full multi-step reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval, problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of non-productive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system is generalizable, making reasonable predictions over reactants and conditions which the rule-based expert does not handle. A web interface to the machine learning based mechanistic reaction predictor is accessible through our chemoinformatics portal (http://cdb.ics.uci.edu) under the Toolkits section. PMID:21819139

Etude des proprietes de surface et des proprietes rheologiques des melanges polymeres thermotropes

NASA Astrophysics Data System (ADS)

Tovar Hernandez, Maria Gabriela

We studied the surface and rheological properties of thermotropic liquid crystal polymers (TLCP) mixed with thermoplastics. We first investigated acid-base interactions in polymer component as a function of temperature, and could identified the many phase changes in TLCP. We found that acid-base interactions in TLCP decrease significantly with temperature, down to a point Tc where they become negligible. To our knowledge, it is the first time such observation is reported concerning TLCP. Acid-base interactions in the thermoplastics also vary with temperature, but they remain non-negligible, and reach a plateau at high temperature. In theory, one can obtain compatible blends between polymers A and B when their interaction parameters are both small and similar. The negligible acid-base parameter of TLCP at T > Tc should enhance the compatibility with thermoplastics. For that reason, we prepared the TLCP/thermoplastic blends at temperatures superior and inferior to Tc. We restricted our investigation to blends prepared in a Brabender Plasticorder in order to control the temperature in the mixing chamber and reduce the effects of TLCP domains deformation and reorientation. We prepared Vectra/polycarbonate blends, optimizing the drying conditions and the TLCP concentration. We optimized the drying conditions based on our previous results, finding that the transesterification reaction in presence of water happens at high temperature. Transesterification reaction was identified using infrared spectroscopy in the polymer components and in the blends. We found that this reaction occurring mainly between the ester groups in the polymer components. The product of this reaction, concentrated at the interfaces, has a remarkable effect on the blend morphology, similar to the one in compatible blend, and on its mechanical properties. To measure the effect of transesterification at the interfaces, we studied the linear viscoelasticity properties of Vectra/polycarbonate blend and their relation with their morphology. We found from the time variation of the elastic modulus at very low frequencies that the transesterification reaction was still occurring during rheological measurements. We observed coalescence of the dispersed phase droplets in all blends. Size of the droplets changed with the blend composition, the preparation temperature and the rheological characterization temperature. In addition, we compared Palierne (1990, 1991) and Lee-Park models when applied to Vectra/polycarbonate blends. We found that the Palierne model does not predict the rheological behavior of the blend, due to the mixture rule used in that model. Lee-Park model, using a different mixture rule, gives a good prediction of the linear viscoelastic properties. We succeeded in modeling the Vectra/polycarbonate rheological properties combining the characteristic relaxation times of the Palierne and Lee-Park models. Using this approach, we could clearly show that the decrease of the interfacial tension is due to the copolymer produced at the interface by transesterification reaction.

Quantum Chemical Approach to Estimating the Thermodynamics of Metabolic Reactions

PubMed Central

Jinich, Adrian; Rappoport, Dmitrij; Dunn, Ian; Sanchez-Lengeling, Benjamin; Olivares-Amaya, Roberto; Noor, Elad; Even, Arren Bar; Aspuru-Guzik, Alán

2014-01-01

Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfer reactions and for reactions not including multiply charged anions. The errors in standard Gibbs reaction energy estimates are correlated with the charges of the participating molecules. The quantum chemical approach is amenable to systematic improvements and holds potential for providing thermodynamic data for all of metabolism. PMID:25387603

Exploring the controls of soil biogeochemistry in a restored coastal wetland using object-oriented computer simulations of uptake kinetics and thermodynamic optimization in batch reactors

NASA Astrophysics Data System (ADS)

Payn, R. A.; Helton, A. M.; Poole, G.; Izurieta, C.; Bernhardt, E. S.; Burgin, A. J.

2012-12-01

Many hypotheses have been proposed to predict patterns of biogeochemical redox reactions based on the availability of electron donors and acceptors and the thermodynamic theory of chemistry. Our objective was to develop a computer model that would allow us to test various alternatives of these hypotheses against data gathered from soil slurry batch reactors, experimental soil perfusion cores, and in situ soil profile observations from the restored Timberlake Wetland in coastal North Carolina, USA. Software requirements to meet this objective included the ability to rapidly develop and compare different hypothetical formulations of kinetic and thermodynamic theory, and the ability to easily change the list of potential biogeochemical reactions used in the optimization scheme. For future work, we also required an object pattern that could easily be coupled with an existing soil hydrologic model. These requirements were met using Network Exchange Objects (NEO), our recently developed object-oriented distributed modeling framework that facilitates simulations of multiple interacting currencies moving through network-based systems. An initial implementation of the object pattern was developed in NEO based on maximizing growth of the microbial community from available dissolved organic carbon. We then used this implementation to build a modeling system for comparing results across multiple simulated batch reactors with varied initial solute concentrations, varied biogeochemical parameters, or varied optimization schemes. Among heterotrophic aerobic and anaerobic reactions, we have found that this model reasonably predicts the use of terminal electron acceptors in simulated batch reactors, where reactions with higher energy yields occur before reactions with lower energy yields. However, among the aerobic reactions, we have also found this model predicts dominance of chemoautotrophs (e.g., nitrifiers) when their electron donor (e.g., ammonium) is abundant, despite the fact that aerobic respiration produces a higher energy yield from the available dissolved oxygen. This suggests that incorporation of an alternative hypothesis, such as a maximum efficiency model, may be necessary to explain an observation of substantial aerobic respiration occurring in the presence of high ammonium and oxygen concentrations. We are parameterizing and testing this model based on results from batch reactor experiments that have treated soil slurries with a full factorial combination of various levels of reactive solutes found in freshwater (e.g., nitrate) and seawater (e.g., sulfate). Initial comparisons suggest that the model may need to account for the biogeochemical reactivity of iron and the potential physical influence of salt to properly describe variability in the biogeochemistry of Timberlake soils. Comparisons of these evolving models with field-derived data from soils will ultimately reveal how thermodynamic theory may be used to explain the evolution of nutrient retention and greenhouse gas emission in the Timberlake Wetland, where nutrient behavior is changing after restoration from agricultural land use and where inputs of brackish water are expected to increase due to sea level rise.

Exploration of cellular reaction systems.

PubMed

Kirkilionis, Markus

2010-01-01

We discuss and review different ways to map cellular components and their temporal interaction with other such components to different non-spatially explicit mathematical models. The essential choices made in the literature are between discrete and continuous state spaces, between rule and event-based state updates and between deterministic and stochastic series of such updates. The temporal modelling of cellular regulatory networks (dynamic network theory) is compared with static network approaches in two first introductory sections on general network modelling. We concentrate next on deterministic rate-based dynamic regulatory networks and their derivation. In the derivation, we include methods from multiscale analysis and also look at structured large particles, here called macromolecular machines. It is clear that mass-action systems and their derivatives, i.e. networks based on enzyme kinetics, play the most dominant role in the literature. The tools to analyse cellular reaction networks are without doubt most complete for mass-action systems. We devote a long section at the end of the review to make a comprehensive review of related tools and mathematical methods. The emphasis is to show how cellular reaction networks can be analysed with the help of different associated graphs and the dissection into modules, i.e. sub-networks.

Quantitative structure-activity relationships for reactivities of sulfate and hydroxyl radicals with aromatic contaminants through single-electron transfer pathway.

PubMed

Luo, Shuang; Wei, Zongsu; Spinney, Richard; Villamena, Frederick A; Dionysiou, Dionysios D; Chen, Dong; Tang, Chong-Jian; Chai, Liyuan; Xiao, Ruiyang

2018-02-15

Sulfate radical anion (SO 4 •- ) and hydroxyl radical (OH) based advanced oxidation technologies has been extensively used for removal of aromatic contaminants (ACs) in waters. In this study, we investigated the Gibbs free energy (ΔG SET ∘ ) of the single electron transfer (SET) reactions for 76 ACs with SO 4 •- and OH, respectively. The result reveals that SO 4 •- possesses greater propensity to react with ACs through the SET channel than OH. We hypothesized that the electron distribution within the molecule plays an essential role in determining the ΔG SET ∘ and subsequent SET reactions. To test the hypothesis, a quantitative structure-activity relationship (QSAR) model was developed for predicting ΔG SET ∘ using the highest occupied molecular orbital energies (E HOMO ), a measure of electron distribution and donating ability. The standardized QSAR models are reported to be ΔG ° SET =-0.97×E HOMO - 181 and ΔG ° SET =-0.97×E HOMO - 164 for SO 4 •- and OH, respectively. The models were internally and externally validated to ensure robustness and predictability, and the application domain and limitations were discussed. The single-descriptor based models account for 95% of the variability for SO 4 •- and OH. These results provide the mechanistic insight into the SET reaction pathway of radical and non-radical bimolecular reactions, and have important applications for radical based oxidation technologies to remove target ACs in different waters. Copyright © 2017 Elsevier B.V. All rights reserved.

Tinnitus as an alarm bell: stress reaction tinnitus model.

PubMed

Alpini, D; Cesarani, A

2006-01-01

Stress is a significant factor influencing the clinical course of tinnitus. Auditory system is particularly sensitive to the effects of different stress factors (chemical, oxidative, emotional, etc.). Different stages of reaction (alarm, resistance, exhaustion) lead to different characteristics of tinnitus and different therapeutic approaches. Individual characteristics of stress reaction may explain different aspects of tinnitus in various patients with different responses to treatment, despite similar audiological and etiological factors. A model based on individual reactions to stress factors (stress reaction tinnitus model) could explain tinnitus as an alarm signal, just like an 'alarm bell', informing the patient that something potentially dangerous for subject homeostasis is happening. Tinnitus could become a disabling symptom when the subject is chronically exposed to a stress factor and is unable to switch off the alarm. Stress signals, specific for each patient, have to be identified during the 'alarm' phase in order to prevent an evolution toward the 'resistance' and 'exhaustion' phases. In these phases, identification of stressor is no more sufficient, due to the organization of a 'paradoxical auditory memory' and a 'pathologically shifted attention to tinnitus'. Identification of stress reaction phase requires accurate otolaryngology and anamnesis combined with audiological matching tests (Feldman Masking Test, for example) and psychometric questionnaires (Tinnitus Reaction and Tinnitus Cognitive Questionnaires). Copyright (c) 2006 S. Karger AG, Basel.

Thermocatalytic Behavior of Manganese (IV) Oxide as Nanoporous Material on the Dissociation of a Gas Mixture Containing Hydrogen Peroxide.

PubMed

Jildeh, Zaid B; Oberländer, Jan; Kirchner, Patrick; Wagner, Patrick H; Schöning, Michael J

2018-04-21

In this article, we present an overview on the thermocatalytic reaction of hydrogen peroxide (H 2 O 2 ) gas on a manganese (IV) oxide (MnO 2 ) catalytic structure. The principle of operation and manufacturing techniques are introduced for a calorimetric H 2 O 2 gas sensor based on porous MnO 2 . Results from surface analyses by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) of the catalytic material provide indication of the H 2 O 2 dissociation reaction schemes. The correlation between theory and the experiments is documented in numerical models of the catalytic reaction. The aim of the numerical models is to provide further information on the reaction kinetics and performance enhancement of the porous MnO 2 catalyst.

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

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

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

PubMed Central

2012-01-01

Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible. PMID:22663945

LASSIE: simulating large-scale models of biochemical systems on GPUs.

PubMed

Tangherloni, Andrea; Nobile, Marco S; Besozzi, Daniela; Mauri, Giancarlo; Cazzaniga, Paolo

2017-05-10

Mathematical modeling and in silico analysis are widely acknowledged as complementary tools to biological laboratory methods, to achieve a thorough understanding of emergent behaviors of cellular processes in both physiological and perturbed conditions. Though, the simulation of large-scale models-consisting in hundreds or thousands of reactions and molecular species-can rapidly overtake the capabilities of Central Processing Units (CPUs). The purpose of this work is to exploit alternative high-performance computing solutions, such as Graphics Processing Units (GPUs), to allow the investigation of these models at reduced computational costs. LASSIE is a "black-box" GPU-accelerated deterministic simulator, specifically designed for large-scale models and not requiring any expertise in mathematical modeling, simulation algorithms or GPU programming. Given a reaction-based model of a cellular process, LASSIE automatically generates the corresponding system of Ordinary Differential Equations (ODEs), assuming mass-action kinetics. The numerical solution of the ODEs is obtained by automatically switching between the Runge-Kutta-Fehlberg method in the absence of stiffness, and the Backward Differentiation Formulae of first order in presence of stiffness. The computational performance of LASSIE are assessed using a set of randomly generated synthetic reaction-based models of increasing size, ranging from 64 to 8192 reactions and species, and compared to a CPU-implementation of the LSODA numerical integration algorithm. LASSIE adopts a novel fine-grained parallelization strategy to distribute on the GPU cores all the calculations required to solve the system of ODEs. By virtue of this implementation, LASSIE achieves up to 92× speed-up with respect to LSODA, therefore reducing the running time from approximately 1 month down to 8 h to simulate models consisting in, for instance, four thousands of reactions and species. Notably, thanks to its smaller memory footprint, LASSIE is able to perform fast simulations of even larger models, whereby the tested CPU-implementation of LSODA failed to reach termination. LASSIE is therefore expected to make an important breakthrough in Systems Biology applications, for the execution of faster and in-depth computational analyses of large-scale models of complex biological systems.

A stochastic modeling of isotope exchange reactions in glutamine synthetase

NASA Astrophysics Data System (ADS)

Kazmiruk, N. V.; Boronovskiy, S. E.; Nartsissov, Ya R.

2017-11-01

The model presented in this work allows simulation of isotopic exchange reactions at chemical equilibrium catalyzed by a glutamine synthetase. To simulate the functioning of the enzyme the algorithm based on the stochastic approach was applied. The dependence of exchange rates for 14C and 32P on metabolite concentration was estimated. The simulation results confirmed the hypothesis of the ascertained validity for preferred order random binding mechanism. Corresponding values of K0.5 were also obtained.

Long Term Degradation of Resin for High Temperature Composites

NASA Technical Reports Server (NTRS)

Patekar, Kaustubh A.

2000-01-01

The durability of polymer matrix composites exposed to harsh environments is a major concern. Surface degradation and damage are observed in polyimide composites used in air at 125 to 300 C. It is believed that diffusion of oxygen into the material and oxidative chemical reactions in the matrix are responsible. Previous work has characterized and modeled diffusion behavior, and thermogravimetric analyses (TGAs) have been carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. However, the model developed using these data was not able to capture behavior seen in isothermal tests, especially those of long duration. A test program that focuses on lower temperatures and makes use of isothermal tests was undertaken to achieve a better understanding of the degradation reactions under use conditions. A new low-cost technique was developed to collect chemical degradation data for isothermal tests lasting over 200 hr in the temperature range 125 to 300 C. Results indicate complex behavior not captured by the previous TGA tests, including the presence of weight-adding reactions. Weight gain reactions dominated in the 125 to 225 C temperature range, while weight loss reactions dominated beyond 225 C. The data obtained from isothermal tests was used to develop a new model of the material behavior. This model was able to fully capture the behavior seen in the tests up to 275 C. Correlation of the current model with both isothermal data at 300 C and high rate TGA test data is mediocre. At 300 C and above, the reaction mechanisms appear to change. Attempts (which failed) to measure non-oxidative degradation indicate that oxidative reactions dominate the degradation at low temperatures. Based on this work, long term isothermal testing in an oxidative atmosphere is recommended for studying the degradation behavior of this class of materials.

Transient Macroscopic Chemistry in the DSMC Method

NASA Astrophysics Data System (ADS)

Goldsworthy, M. J.; Macrossan, M. N.; Abdel-Jawad, M.

2008-12-01

In the Direct Simulation Monte Carlo method, a combination of statistical and deterministic procedures applied to a finite number of `simulator' particles are used to model rarefied gas-kinetic processes. Traditionally, chemical reactions are modelled using information from specific colliding particle pairs. In the Macroscopic Chemistry Method (MCM), the reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell is used to determine a reaction rate coefficient for that cell. MCM has previously been applied to steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation and during the unsteady development of 2-D flow through a cavity. For the shock tube simulation, close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature and species mole fractions. For the cavity flow, a high degree of thermal non-equilibrium is present and non-equilibrium reaction rate correction factors are employed in MCM. Very close agreement is demonstrated for ensemble averaged mole fraction contours predicted by the particle and macroscopic methods at three different flow-times. A comparison of the accumulated number of net reactions per cell shows that both methods compute identical numbers of reaction events. For the 2-D flow, MCM required similar CPU and memory resources to the particle chemistry method. The Macroscopic Chemistry Method is applicable to any general DSMC code using any viscosity or non-reacting collision models and any non-reacting energy exchange models. MCM can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies.

Modeling for (physical) biologists: an introduction to the rule-based approach

PubMed Central

Chylek, Lily A; Harris, Leonard A; Faeder, James R; Hlavacek, William S

2015-01-01

Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions. PMID:26178138

Perspective on Diabatic Models of Chemical Reactivity as Illustrated by the Gas-Phase SN2 Reaction of Acetate Ion with 1,2-Dichloroethane

PubMed Central

Valero, Rosendo; Song, Lingchun; Gao, Jiali; Truhlar, Donald G.

2009-01-01

Diabatic models are widely employed for studying chemical reactivity in condensed phases and enzymes, but there has been little discussion of the pros and cons of various diabatic representations for this purpose. Here we discuss and contrast six different schemes for computing diabatic potentials for a charge rearrangement reaction. They include (i) the variational diabatic configurations (VDC) constructed by variationally optimizing individual valence bond structures and (ii) the consistent diabatic configurations (CDC) obtained by variationally optimizing the ground-state adiabatic energy, both in the nonorthogonal molecular orbital valence bond (MOVB) method, along with the orthogonalized (iii) VDC-MOVB and (iv) CDC-MOVB models. In addition, we consider (v) the fourfold way (based on diabatic molecular orbitals and configuration uniformity), and (vi) empirical valence bond (EVB) theory. To make the considerations concrete, we calculate diabatic electronic states and diabatic potential energies along the reaction path that connects the reactant and the product ion-molecule complexes of the gas-phase bimolecular nucleophilic substitution (SN2) reaction of 1,2-dichloethane (DCE) with acetate ion, which is a model reaction corresponding to the reaction catalyzed by haloalkane dehalogenase. We utilize ab initio block-localized molecular orbital theory to construct the MOVB diabatic states and ab initio multi-configuration quasidegenerate perturbation theory to construct the fourfold-way diabatic states; the latter are calculated at reaction path geometries obtained with the M06-2X density functional. The EVB diabatic states are computed with parameters taken from the literature. The MOVB and fourfold-way adiabatic and diabatic potential energy profiles along the reaction path are in qualitative but not quantitative agreement with each other. In order to validate that these wave-function-based diabatic states are qualitatively correct, we show that the reaction energy and barrier for the adiabatic ground state, obtained with these methods, agree reasonably well with the results of high-level calculations using the composite G3SX and G3SX(MP3) methods and the BMC-CCSD multi-coefficient correlation method. However, a comparison of the EVB gas-phase adiabatic ground-state reaction path with those obtained from MOVB and with the fourfold way reveals that the EVB reaction path geometries show a systematic shift towards the products region, and that the EVB lowest-energy path has a much lower barrier. The free energies of solvation and activation energy in water reported from dynamical calculations based on EVB also imply a low activation barrier in the gas phase. In addition, calculations of the free energy of solvation using the recently proposed SM8 continuum solvation model with CM4M partial atomic charges lead to an activation barrier in reasonable agreement with experiment only when the geometries and the gas-phase barrier are those obtained from electronic structure calculations, i.e., methods i–v. These comparisons show the danger of basing the diabatic states on molecular mechanics without the explicit calculation of electronic wave functions. Furthermore, comparison of schemes i–v with one another shows that significantly different quantitative results can be obtained by using different methods for extracting diabatic states from wave function calculations, and it is important for each user to justify the choice of diabatization method in the context of its intended use. PMID:20047005

Sequence-based Network Completion Reveals the Integrality of Missing Reactions in Metabolic Networks*

PubMed Central

Krumholz, Elias W.; Libourel, Igor G. L.

2015-01-01

Genome-scale metabolic models are central in connecting genotypes to metabolic phenotypes. However, even for well studied organisms, such as Escherichia coli, draft networks do not contain a complete biochemical network. Missing reactions are referred to as gaps. These gaps need to be filled to enable functional analysis, and gap-filling choices influence model predictions. To investigate whether functional networks existed where all gap-filling reactions were supported by sequence similarity to annotated enzymes, four draft networks were supplemented with all reactions from the Model SEED database for which minimal sequence similarity was found in their genomes. Quadratic programming revealed that the number of reactions that could partake in a gap-filling solution was vast: 3,270 in the case of E. coli, where 72% of the metabolites in the draft network could connect a gap-filling solution. Nonetheless, no network could be completed without the inclusion of orphaned enzymes, suggesting that parts of the biochemistry integral to biomass precursor formation are uncharacterized. However, many gap-filling reactions were well determined, and the resulting networks showed improved prediction of gene essentiality compared with networks generated through canonical gap filling. In addition, gene essentiality predictions that were sensitive to poorly determined gap-filling reactions were of poor quality, suggesting that damage to the network structure resulting from the inclusion of erroneous gap-filling reactions may be predictable. PMID:26041773

Energy- and wave-based beam-tracing prediction of room-acoustical parameters using different boundary conditions.

PubMed

Yousefzadeh, Behrooz; Hodgson, Murray

2012-09-01

A beam-tracing model was used to study the acoustical responses of three empty, rectangular rooms with different boundary conditions. The model is wave-based (accounting for sound phase) and can be applied to rooms with extended-reaction surfaces that are made of multiple layers of solid, fluid, or poroelastic materials-the acoustical properties of these surfaces are calculated using Biot theory. Three room-acoustical parameters were studied in various room configurations: sound strength, reverberation time, and RApid Speech Transmission Index. The main objective was to investigate the effects of modeling surfaces as either local or extended reaction on predicted values of these three parameters. Moreover, the significance of modeling interference effects was investigated, including the study of sound phase-change on surface reflection. Modeling surfaces as of local or extended reaction was found to be significant for surfaces consisting of multiple layers, specifically when one of the layers is air. For multilayers of solid materials with an air-cavity, this was most significant around their mass-air-mass resonance frequencies. Accounting for interference effects made significant changes in the predicted values of all parameters. Modeling phase change on reflection, on the other hand, was found to be relatively much less significant.

Reactivity of bromoalkanes in reactions of coordinated molecular decay

NASA Astrophysics Data System (ADS)

Pokidova, T. S.; Denisov, E. T.

2016-09-01

The results from experiments on reactions of the coordinated molecular decay of RBr bromoalkanes on olefin and HBr are analyzed using the model of intersecting parabolas (MIP). Kinetic parameters within the MIP are calculated from the experimental data, enabling calculation of the activation energies ( E) and rate constants ( k) of such reactions, based on the enthalphy of the reaction and the MIP algorithms. The factors affecting the E of the RBr decay reaction are established: the enthalphy of the reaction, triplet repulsion, the energy of radical R• stabilization, the presence of a π bond adjacent to the reaction center, and the dipole-dipole interaction of polar groups. The energy spectrum of the partial energies of activation is constructed for the reaction of coordinated molecular decay of RBr, and the E and k of inverse addition reactions are evaluated.

A Film Depositional Model of Permeability for Mineral Reactions in Unsaturated Media.

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

Freedman, Vicky L.; Saripalli, Prasad; Bacon, Diana H.

2004-11-15

A new modeling approach based on the biofilm models of Taylor et al. (1990, Water Resources Research, 26, 2153-2159) has been developed for modeling changes in porosity and permeability in saturated porous media and implemented in an inorganic reactive transport code. Application of the film depositional models to mineral precipitation and dissolution reactions requires that calculations of mineral films be dynamically changing as a function of time dependent reaction processes. Since calculations of film thicknesses do not consider mineral density, results show that the film porosity model does not adequately describe volumetric changes in the porous medium. These effects canmore » be included in permeability calculations by coupling the film permeability models (Mualem and Childs and Collis-George) to a volumetric model that incorporates both mineral density and reactive surface area. Model simulations demonstrate that an important difference between the biofilm and mineral film models is in the translation of changes in mineral radii to changes in pore space. Including the effect of tortuosity on pore radii changes improves the performance of the Mualem permeability model for both precipitation and dissolution. Results from simulation of simultaneous dissolution and secondary mineral precipitation provides reasonable estimates of porosity and permeability. Moreover, a comparison of experimental and simulated data show that the model yields qualitatively reasonable results for permeability changes due to solid-aqueous phase reactions.« less

Au and Pt nanoparticle supported catalysts tailored for H-2 production: From models to powder catalysts

DOE PAGES

T. D. Nguyen-Phan; Baber, A. E.; Rodriguez, J. A.; ...

2015-12-10

The use of metal nanoparticles (NPs), including Au and Pt, supported over oxides has been pivotal, and is ever increasing in enabling catalytic reactions which target the production of hydrogen. We review here the most recent works pertaining to the fundamental understanding of the structure, morphology, growth, characterization, and intrinsic phenomenological properties of Au– and Pt– based catalysts that influence the reactivity and selectivity to target hydrogen production. We draw on surface science and theoretical methods of model and powder catalysts using high resolution imaging, spectroscopy, scattering experiments, and theoretical studies. Based on these insights we identify key aspects ofmore » studies of supported metal nanoparticle (NP) catalysts for several reactions. The main focus of this review is on the intersection of catalytic chemistry related to the water-gas shift (WGS), oxygenate steam reforming (OSR), and solarassisted reactions (SAR).« less

Modification of heterogeneous chemistry by complex substrate morphology

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

Henson, B.F.; Buelow, S.J.; Robinson, J.M.

1998-12-31

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Chemistry in many environmental systems is determined at some stage by heterogeneous reaction with a surface. Typically the surface exists as a dispersion or matrix of particulate matter or pores, and a determination of the heterogeneous chemistry of the system must address the extent to which the complexity of the environmental surface affects the reaction rates. Reactions that are of current interest are the series of chlorine nitrate reactions important in polar ozone depletion. The authors have applied surfacemore » spectroscopic techniques developed at LANL to address the chemistry of chlorine nitrate reactions on porous nitric and sulfuric acid ice surfaces as a model study of the measurement of complex, heterogeneous reaction rates. The result of the study is an experimental determination of the surface coverage of one adsorbed reagent and a mechanism of reactivity based on the dependence of this coverage on temperature and vapor pressure. The resulting mechanism allows the first comprehensive modeling of chlorine nitrate reaction probability data from several laboratories.« less

Dissociative chemisorption of methane on metal surfaces: Tests of dynamical assumptions using quantum models and ab initio molecular dynamics

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

Jackson, Bret, E-mail: jackson@chem.umass.edu; Nattino, Francesco; Kroes, Geert-Jan

The dissociative chemisorption of methane on metal surfaces is of great practical and fundamental importance. Not only is it the rate-limiting step in the steam reforming of natural gas, the reaction exhibits interesting mode-selective behavior and a strong dependence on the temperature of the metal. We present a quantum model for this reaction on Ni(100) and Ni(111) surfaces based on the reaction path Hamiltonian. The dissociative sticking probabilities computed using this model agree well with available experimental data with regard to variation with incident energy, substrate temperature, and the vibrational state of the incident molecule. We significantly expand the vibrationalmore » basis set relative to earlier studies, which allows reaction probabilities to be calculated for doubly excited initial vibrational states, though it does not lead to appreciable changes in the reaction probabilities for singly excited initial states. Sudden models used to treat the center of mass motion parallel to the surface are compared with results from ab initio molecular dynamics and found to be reasonable. Similar comparisons for molecular rotation suggest that our rotationally adiabatic model is incorrect, and that sudden behavior is closer to reality. Such a model is proposed and tested. A model for predicting mode-selective behavior is tested, with mixed results, though we find it is consistent with experimental studies of normal vs. total (kinetic) energy scaling. Models for energy transfer into lattice vibrations are also examined.« less

Mesoscopic-microscopic spatial stochastic simulation with automatic system partitioning.

PubMed

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2017-12-21

The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simulation of spatially resolved stochastic chemical kinetics. Compared to off-lattice hard-sphere simulations with Brownian dynamics or Green's function reaction dynamics, the RDME can be orders of magnitude faster if the lattice spacing can be chosen coarse enough. However, strongly diffusion-controlled reactions mandate a very fine mesh resolution for acceptable accuracy. It is common that reactions in the same model differ in their degree of diffusion control and therefore require different degrees of mesh resolution. This renders mesoscopic simulation inefficient for systems with multiscale properties. Mesoscopic-microscopic hybrid methods address this problem by resolving the most challenging reactions with a microscale, off-lattice simulation. However, all methods to date require manual partitioning of a system, effectively limiting their usefulness as "black-box" simulation codes. In this paper, we propose a hybrid simulation algorithm with automatic system partitioning based on indirect a priori error estimates. We demonstrate the accuracy and efficiency of the method on models of diffusion-controlled networks in 3D.

Reaction Force of Micro-scale Liquid Droplets Constrained Between Parallel Plates through CFD

NASA Astrophysics Data System (ADS)

Free, Robert; Hekiri, Haider; Hawa, Takumi

2012-02-01

Micro-scale liquid droplets responding to depression between parallel plates are investigated analytically and numerically. The functional dependence of the reaction force accrued in such droplets on droplet size, surface tension, depression amount, and contact angle is explored. For both the 2D and 3D case, an analytical model is developed based on first principles. Computational fluid dynamics is then utilized to evaluate the validity of these models. The reaction force is highly nonlinear, initially increasing very slowly with increasing depression of the droplet, but eventually moving asymptotically to infinity. The force scales linearly with both the droplet free radius and surface tension of the liquid, but has a much more complicated dependence on the contact angle and depression. Explicit expressions for the reaction force have been determined, showing these dependencies. The 3D model has been largely supported by the CFD results. It very accurately predicts the reaction force on the upper plate as the droplet is crushed, accounting for the effect of contact angle, surface tension, and droplet size.

Reaction Wheel Disturbance Modeling, Jitter Analysis, and Validation Tests for Solar Dynamics Observatory

NASA Technical Reports Server (NTRS)

Liu,Kuo-Chia; Maghami, Peiman; Blaurock, Carl

2008-01-01

The Solar Dynamics Observatory (SDO) aims to study the Sun's influence on the Earth by understanding the source, storage, and release of the solar energy, and the interior structure of the Sun. During science observations, the jitter stability at the instrument focal plane must be maintained to less than a fraction of an arcsecond for two of the SDO instruments. To meet these stringent requirements, a significant amount of analysis and test effort has been devoted to predicting the jitter induced from various disturbance sources. One of the largest disturbance sources onboard is the reaction wheel. This paper presents the SDO approach on reaction wheel disturbance modeling and jitter analysis. It describes the verification and calibration of the disturbance model, and ground tests performed for validating the reaction wheel jitter analysis. To mitigate the reaction wheel disturbance effects, the wheels will be limited to operate at low wheel speeds based on the current analysis. An on-orbit jitter test algorithm is also presented in the paper which will identify the true wheel speed limits in order to ensure that the wheel jitter requirements are met.

Boehmite-An Efficient and Recyclable Acid-Base Bifunctional Catalyst for Aldol Condensation Reaction.

PubMed

Reshma, P C Rajan; Vikneshvaran, Sekar; Velmathi, Sivan

2018-06-01

In this work boehmite was used as an acid-base bifunctional catalyst for aldol condensation reactions of aromatic aldehydes and ketones. The catalyst was prepared by simple sol-gel method using Al(NO3)3·9H2O and NH4OH as precursors. The catalyst has been characterized by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), Scanning Electron Microscopy (SEM), UV-visible spectroscopy (DRS), BET surface area analyses. Boehmite is successfully applied as catalyst for the condensation reaction between 4-nitrobenzaldehyde and acetone as a model substrate giving α, β-unsaturated ketones without any side product. The scope of the reaction is extended for various substituted aldehydes. A probable mechanism has been suggested to explain the cooperative behavior of the acidic and basic sites. The catalyst is environmentally friendly and easily recovered from the reaction mixture. Also the catalyst is reusable up to 3 catalytic cycles.

Intervertebral reaction force prediction using an enhanced assembly of OpenSim models.

PubMed

Senteler, Marco; Weisse, Bernhard; Rothenfluh, Dominique A; Snedeker, Jess G

2016-01-01

OpenSim offers a valuable approach to investigating otherwise difficult to assess yet important biomechanical parameters such as joint reaction forces. Although the range of available models in the public repository is continually increasing, there currently exists no OpenSim model for the computation of intervertebral joint reactions during flexion and lifting tasks. The current work combines and improves elements of existing models to develop an enhanced model of the upper body and lumbar spine. Models of the upper body with extremities, neck and head were combined with an improved version of a lumbar spine from the model repository. Translational motion was enabled for each lumbar vertebrae with six controllable degrees of freedom. Motion segment stiffness was implemented at lumbar levels and mass properties were assigned throughout the model. Moreover, body coordinate frames of the spine were modified to allow straightforward variation of sagittal alignment and to simplify interpretation of results. Evaluation of model predictions for level L1-L2, L3-L4 and L4-L5 in various postures of forward flexion and moderate lifting (8 kg) revealed an agreement within 10% to experimental studies and model-based computational analyses. However, in an extended posture or during lifting of heavier loads (20 kg), computed joint reactions differed substantially from reported in vivo measures using instrumented implants. We conclude that agreement between the model and available experimental data was good in view of limitations of both the model and the validation datasets. The presented model is useful in that it permits computation of realistic lumbar spine joint reaction forces during flexion and moderate lifting tasks. The model and corresponding documentation are now available in the online OpenSim repository.

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

PubMed

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

Kinetics of Ethyl Acetate Synthesis Catalyzed by Acidic Resins

ERIC Educational Resources Information Center

Antunes, Bruno M.; Cardoso, Simao P.; Silva, Carlos M.; Portugal, Ines

2011-01-01

A low-cost experiment to carry out the second-order reversible reaction of acetic acid esterification with ethanol to produce ethyl acetate is presented to illustrate concepts of kinetics and reactor modeling. The reaction is performed in a batch reactor, and the acetic acid concentration is measured by acid-base titration versus time. The…

Total Reaction Cross Section Excitation Function Studies for 6He Interaction with 181Ta, 59Co, natSi, 9Be Nuclei

NASA Astrophysics Data System (ADS)

Sobolev, Yu. G.; Penionzhkevich, Yu. E.; Borcea, C.; Demekhina, N. A.; Eshanov, A. G.; Ivanov, M. P.; Kabdrakhimova, G. D.; Kabyshev, A. M.; Kugler, A.; Kuterbekov, K. A.; Lukyanov, K. V.; Maj, A.; Maslov, V. A.; Negret, A.; Skobelev, N. K.; Testov, D.; Trzaska, W. H.; Voskobojnik, E. I.; Zemlyanaya, E. V.

2015-06-01

Total reaction cross section excitation functions σR(E) were measured for 6He secondary beam particles on 181Ta, 59Co, natSi and 9Be targets in a wide energy range by direct and model-independent method. This experimental method was based on prompt n-γ 4π-technique applied in event-by event mode. A high efficiency CsI(Tl) γ-spectrometer was used for the detection of reaction products (prompt γ-quanta and neutrons) accompanying each reaction event. Using the ACCULINNA fragment-separator 6He fragments (produced by 11B primary beam with 9Be target) are separated and transported to n-γ shielded experimental cave at FLNR JINR. The measured total reaction cross section data σR(E) for the above mentioned reactions are compared with a theoretical calculation based on the optical potential with the real part having the double-folding form.

Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

NASA Astrophysics Data System (ADS)

Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao

2017-12-01

We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we developed 24 test items addressing the attributes of exothermic and endothermic reactions, chemical bonds and heat quantity change, reaction heat and enthalpy, thermochemical equations, and Hess's law. The test was administered to a sample base of 694 senior high school students taught in 3 schools across 2 cities. Results based on the Rule Space Model analysis indicated that (1) the test items developed by the Rule Space Model were of high psychometric quality for good analysis of difficulties, discriminations, reliabilities, and validities; (2) the Rule Space Model analysis classified the students into seven different attribute mastery patterns; and (3) the initial hypothesized learning progression was modified by the attribute mastery patterns and the learning paths to be more precise and detailed.

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

Multiplexed immunosensing and kinetics monitoring in nanofluidic devices with highly enhanced target capture efficiency

PubMed Central

Lin, Yii-Lih; Huang, Yen-Jun; Teerapanich, Pattamon; Leïchlé, Thierry

2016-01-01

Nanofluidic devices promise high reaction efficiency and fast kinetic responses due to the spatial constriction of transported biomolecules with confined molecular diffusion. However, parallel detection of multiple biomolecules, particularly proteins, in highly confined space remains challenging. This study integrates extended nanofluidics with embedded protein microarray to achieve multiplexed real-time biosensing and kinetics monitoring. Implementation of embedded standard-sized antibody microarray is attained by epoxy-silane surface modification and a room-temperature low-aspect-ratio bonding technique. An effective sample transport is achieved by electrokinetic pumping via electroosmotic flow. Through the nanoslit-based spatial confinement, the antigen-antibody binding reaction is enhanced with ∼100% efficiency and may be directly observed with fluorescence microscopy without the requirement of intermediate washing steps. The image-based data provide numerous spatially distributed reaction kinetic curves and are collectively modeled using a simple one-dimensional convection-reaction model. This study represents an integrated nanofluidic solution for real-time multiplexed immunosensing and kinetics monitoring, starting from device fabrication, protein immobilization, device bonding, sample transport, to data analysis at Péclet number less than 1. PMID:27375819

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.

Ab initio state-specific N2 + O dissociation and exchange modeling for molecular simulations

NASA Astrophysics Data System (ADS)

Luo, Han; Kulakhmetov, Marat; Alexeenko, Alina

2017-02-01

Quasi-classical trajectory (QCT) calculations are used in this work to calculate state-specific N2(X1Σ ) +O(3P ) →2 N(4S ) +O(3P ) dissociation and N2(X1Σ ) +O(3P ) →NO(X2Π ) +N(4S ) exchange cross sections and rates based on the 13A″ and 13A' ab initio potential energy surface by Gamallo et al. [J. Chem. Phys. 119, 2545-2556 (2003)]. The calculations consider translational energies up to 23 eV and temperatures between 1000 K and 20 000 K. Vibrational favoring is observed for dissociation reaction at the whole range of collision energies and for exchange reaction around the dissociation limit. For the same collision energy, cross sections for v = 30 are 4 to 6 times larger than those for the ground state. The exchange reaction has an effective activation energy that is dependent on the initial rovibrational level, which is different from dissociation reaction. In addition, the exchange cross sections have a maximum when the total collision energy (TCE) approaches dissociation energy. The calculations are used to generate compact QCT-derived state-specific dissociation (QCT-SSD) and QCT-derived state-specific exchange (QCT-SSE) models, which describe over 1 × 106 cross sections with about 150 model parameters. The models can be used directly within direct simulation Monte Carlo and computational fluid dynamics simulations. Rate constants predicted by the new models are compared to the experimental measurements, direct QCT calculations and predictions by other models that include: TCE model, Bose-Candler QCT-based exchange model, Macheret-Fridman dissociation model, Macheret's exchange model, and Park's two-temperature model. The new models match QCT-calculated and experimental rates within 30% under nonequilibrium conditions while other models under predict by over an order of magnitude under vibrationally-cold conditions.

Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

PubMed Central

Matsuura, Tomoaki; Tanimura, Naoki; Hosoda, Kazufumi; Yomo, Tetsuya; Shimizu, Yoshihiro

2017-01-01

To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions. PMID:28167777

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

Hay, J.; Schwender, J.

Computational simulation of large-scale biochemical networks can be used to analyze and predict the metabolic behavior of an organism, such as a developing seed. Based on the biochemical literature, pathways databases and decision rules defining reaction directionality we reconstructed bna572, a stoichiometric metabolic network model representing Brassica napus seed storage metabolism. In the highly compartmentalized network about 25% of the 572 reactions are transport reactions interconnecting nine subcellular compartments and the environment. According to known physiological capabilities of developing B. napus embryos, four nutritional conditions were defined to simulate heterotrophy or photoheterotrophy, each in combination with the availability of inorganicmore » nitrogen (ammonia, nitrate) or amino acids as nitrogen sources. Based on mathematical linear optimization the optimal solution space was comprehensively explored by flux variability analysis, thereby identifying for each reaction the range of flux values allowable under optimality. The range and variability of flux values was then categorized into flux variability types. Across the four nutritional conditions, approximately 13% of the reactions have variable flux values and 10-11% are substitutable (can be inactive), both indicating metabolic redundancy given, for example, by isoenzymes, subcellular compartmentalization or the presence of alternative pathways. About one-third of the reactions are never used and are associated with pathways that are suboptimal for storage synthesis. Fifty-seven reactions change flux variability type among the different nutritional conditions, indicating their function in metabolic adjustments. This predictive modeling framework allows analysis and quantitative exploration of storage metabolism of a developing B. napus oilseed.« less

Kinetics of liquid-solid reactions in naphthenic acid conversion and Kraft pulping

NASA Astrophysics Data System (ADS)

Yang, Ling

Two liquid-solid reactions, in which the morphology of the solid changes as the reactions proceeds, were examined. One is the NA conversion in oil by decarboxylation on metal oxides and carbonates, and the other is the Kraft pulping in which lignin removal by delignification reaction. In the study of the NA conversion, CaO was chosen as the catalyst for the kinetic study from the tested catalysts based on NA conversion. Two reaction mixtures, carrier oil plus commercial naphthenic acids and heavy vacuum gas oil (HVGO) from Athabasca bitumen, were applied in the kinetic study. The influence of TAN, temperature, and catalyst loading on the NA conversion and decarboxylation were studied systematically. The results showed that the removal rate of TAN and the decarboxylation of NA were both independent of the concentration of NA over the range studied, and significantly dependent on reaction temperature. The data from analyzing the spent catalyst demonstrated that calcium naphthenate was an intermediate of the decarboxylation reaction of NA, and the decomposition of calcium naphthenate was a rate-determining step. In the study on the delignification of the Kraft pulping, a new mechanism was proposed for the heterogeneous delignification reaction during the Kraft pulping process. In particular, the chemical reaction mechanism took into account the heterogeneous nature of Kraft pulping. Lignin reacted in parallel with sodium hydroxide and sodium sulfide. The mechanism consists of three key kinetic steps: (1) adsorption of hydroxide and hydrosulfide ions on lignin; (2) surface reaction on the solid surface to produce degraded lignin products; and (3) desorption of degradation products from the solid surface. The most important step for the delignification process is the surface reaction, rather than the reactions occurring in the liquid phase. A kinetic model has, thus, been developed based on the proposed mechanism. The derived kinetic model showed that the mechanism could be employed to predict the pulping behavior under a variety of conditions with good accuracy.

Stochastic reaction-diffusion algorithms for macromolecular crowding

NASA Astrophysics Data System (ADS)

Sturrock, Marc

2016-06-01

Compartment-based (lattice-based) reaction-diffusion algorithms are often used for studying complex stochastic spatio-temporal processes inside cells. In this paper the influence of macromolecular crowding on stochastic reaction-diffusion simulations is investigated. Reaction-diffusion processes are considered on two different kinds of compartmental lattice, a cubic lattice and a hexagonal close packed lattice, and solved using two different algorithms, the stochastic simulation algorithm and the spatiocyte algorithm (Arjunan and Tomita 2010 Syst. Synth. Biol. 4, 35-53). Obstacles (modelling macromolecular crowding) are shown to have substantial effects on the mean squared displacement and average number of molecules in the domain but the nature of these effects is dependent on the choice of lattice, with the cubic lattice being more susceptible to the effects of the obstacles. Finally, improvements for both algorithms are presented.

Total reaction cross sections in CEM and MCNP6 at intermediate energies

DOE PAGES

Kerby, Leslie M.; Mashnik, Stepan G.

2015-05-14

Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used inmore » the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.« less

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2017-07-01

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.

Total reaction cross sections in CEM and MCNP6 at intermediate energies

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

Kerby, Leslie M.; Mashnik, Stepan G.

Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used inmore » the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.« less

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

PubMed

Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

2012-12-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

13C metabolic flux analysis at a genome-scale.

PubMed

Gopalakrishnan, Saratram; Maranas, Costas D

2015-11-01

Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm. Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non-zero flux for the arginine degradation pathway was identified to meet biomass precursor demands as detailed in the iAF1260 model. Inferred ranges for 81% of the reactions in the genome-scale metabolic (GSM) model varied less than one-tenth of the basis glucose uptake rate (95% confidence test). This is because as many as 411 reactions in the GSM are growth coupled meaning that the single measurement of biomass formation rate locks the reaction flux values. This implies that accurate biomass formation rate and composition are critical for resolving metabolic fluxes away from central metabolism and suggests the importance of biomass composition (re)assessment under different genetic and environmental backgrounds. In addition, the loss of information associated with mapping fluxes from MFA on a core model to a GSM model is quantified. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Neuro-estimator based GMC control of a batch reactive distillation.

PubMed

Prakash, K J Jithin; Patle, Dipesh S; Jana, Amiya K

2011-07-01

In this paper, an artificial neural network (ANN)-based nonlinear control algorithm is proposed for a simulated batch reactive distillation (RD) column. In the homogeneously catalyzed reactive process, an esterification reaction takes place for the production of ethyl acetate. The fundamental model has been derived incorporating the reaction term in the model structure of the nonreactive distillation process. The process operation is simulated at the startup phase under total reflux conditions. The open-loop process dynamics is also addressed running the batch process at the production phase under partial reflux conditions. In this study, a neuro-estimator based generic model controller (GMC), which consists of an ANN-based state predictor and the GMC law, has been synthesized. Finally, this proposed control law has been tested on the representative batch reactive distillation comparing with a gain-scheduled proportional integral (GSPI) controller and with its ideal performance (ideal GMC). Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Extended optical model for fission

DOE PAGES

Sin, M.; Capote, R.; Herman, M. W.; ...

2016-03-07

A comprehensive formalism to calculate fission cross sections based on the extension of the optical model for fission is presented. It can be used for description of nuclear reactions on actinides featuring multi-humped fission barriers with partial absorption in the wells and direct transmission through discrete and continuum fission channels. The formalism describes the gross fluctuations observed in the fission probability due to vibrational resonances, and can be easily implemented in existing statistical reaction model codes. The extended optical model for fission is applied for neutron induced fission cross-section calculations on 234,235,238U and 239Pu targets. A triple-humped fission barrier ismore » used for 234,235U(n,f), while a double-humped fission barrier is used for 238U(n,f) and 239Pu(n,f) reactions as predicted by theoretical barrier calculations. The impact of partial damping of class-II/III states, and of direct transmission through discrete and continuum fission channels, is shown to be critical for a proper description of the measured fission cross sections for 234,235,238U(n,f) reactions. The 239Pu(n,f) reaction can be calculated in the complete damping approximation. Calculated cross sections for 235,238U(n,f) and 239Pu(n,f) reactions agree within 3% with the corresponding cross sections derived within the Neutron Standards least-squares fit of available experimental data. Lastly, the extended optical model for fission can be used for both theoretical fission studies and nuclear data evaluation.« less

Click mechanochemistry: quantitative synthesis of "ready to use" chiral organocatalysts by efficient two-fold thiourea coupling to vicinal diamines.

PubMed

Štrukil, Vjekoslav; Igrc, Marina D; Eckert-Maksić, Mirjana; Friščić, Tomislav

2012-07-02

Mechanochemical methods of neat grinding and liquid-assisted grinding have been applied to the synthesis of mono- and bis(thiourea)s by using the click coupling of aromatic and aliphatic diamines with aromatic isothiocyanates. The ability to modify the reaction conditions allowed the optimization of each reaction, leading to the quantitative formation of chiral bis(thiourea)s with known uses as organocatalysts or anion sensors. Quantitative reaction yields, combined with the fact that mechanochemical reaction conditions avoid the use of bulk solvents, enabled solution-based purification methods (such as chromatography or recrystallization) to be completely avoided. Importantly, by using selected model reactions, we also show that the described mechanochemical reaction procedures can be readily scaled up to at least the one-gram scale. In that way, mechanochemical synthesis provides a facile method to fully transform valuable enantiomerically pure reagents into useful products that can immediately be applied in their designed purpose. This was demonstrated by using some of the mechanochemically prepared reagents as organocatalysts in a model Morita-Baylis-Hillman reaction and as cyanide ion sensors in organic solvents. The use of electronically and sterically hindered ortho-phenylenediamine revealed that mechanochemical reaction conditions can be readily optimized to form either the 1:1 or the 1:2 click-coupling product, demonstrating that reaction stoichiometry can be more efficiently controlled under these conditions than in solution-based syntheses. In this way, it was shown that excellent stoichiometric control by mechanochemistry, previously established for mechanochemical syntheses of cocrystals and coordination polymers, can also be achieved in the context of covalent-bond formation. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rule-based modeling and simulations of the inner kinetochore structure.

PubMed

Tschernyschkow, Sergej; Herda, Sabine; Gruenert, Gerd; Döring, Volker; Görlich, Dennis; Hofmeister, Antje; Hoischen, Christian; Dittrich, Peter; Diekmann, Stephan; Ibrahim, Bashar

2013-09-01

Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins. Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts. Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modeling & processing of ceramic and polymer precursor ceramic matrix composite materials

NASA Astrophysics Data System (ADS)

Wang, Xiaolin

Synthesis and processing of novel materials with various advanced approaches have attracted much attention of engineers and scientists for the past thirty years. Many advanced materials display a number of exceptional properties and can be produced with different novel processing techniques. For example, AlN is a promising candidate for electronic, optical and opto-electronic applications due to its high thermal conductivity, high electrical resistivity, high acoustic wave velocity and large band gap. Large bulk AlN crystal can be produced by sublimation of AlN powder. Novel nonostructured multicomponent refractory metal-based ceramics (carbides, borides and nitrides) show a lot of exceptional mechanical, thermal and chemical properties, and can be easily produced by pyrolysis of suitable preceramic precursors mixed with metal particles. The objective of this work is to study sublimation and synthesis of AlN powder, and synthesis of SiC-based metal ceramics. For AlN sublimation crystal growth, we will focus on modeling the processes in the powder source that affect significantly the sublimation growth as a whole. To understand the powder porosity evolution and vapor transport during powder sublimation, the interplay between vapor transport and powder sublimation will be studied. A physics-based computational model will be developed considering powder sublimation and porosity evolution. Based on the proposed model, the effect of a central hole in the powder on the sublimation rate is studied and the result is compared to the case of powder without a hole. The effect of hole size on the sublimation rate will be studied. The effects of initial porosity, particle size and driving force on the sublimation rate are also studied. Moreover, the optimal growth condition for large diameter crystal quality and high growth rate will be determined. For synthesis of SiC-based metal ceramics, we will focus on developing a multi-scale process model to describe the dynamic behavior of filler particle reaction, microstructure evolution, at the microscale as well as transient fluid flow, heat transfer, and species transport at the macroscale. The model comprises of (i) a microscale model and (ii) a macroscale transport model, and aims to provide optimal conditions for the fabrication process of the ceramics. The porous media macroscale model for SiC-based metal-ceramic materials processing will be developed to understand the thermal polymer pyrolysis, chemical reaction of active fillers and transport phenomena in the porous media. The macroscale model will include heat and mass transfer, curing, pyrolysis, chemical reaction and crystallization in a mixture of preceramic polymers and submicron/nano-sized metal particles of uranium, zirconium, niobium, or hafnium. The effects of heating rate, sample size, size and volume ratio of the metal particles on the reaction rate and product uniformity will be studied. The microscale model will be developed for modeling the synthesis of SiC matrix and metal particles. The macroscale model provides thermal boundary conditions to the microscale model. The microscale model applies to repetitive units in the porous structure and describes mass transport, composition changes and motion of metal particles. The unit-cell is the representation unit of the source material, and it consists of several metal particles, SiC matrix and other components produced from the synthesis process. The reactions between different components, the microstructure evolution of the product will be considered. The effects of heating rate and metal particle size on species uniformity and microstructure are investigated.

Use of the Equity Implementation Model to Review Clinical System Implementation Efforts

PubMed Central

Lauer, Thomas W.; Joshi, Kailash; Browdy, Thomas

2000-01-01

This paper presents the equity implementation model (EIM) in the context of a case that describes the implementation of a medical scheduling system. The model is based on equity theory, a well-established theory in the social sciences that has been tested in hundreds of experimental and field studies. The predictions of equity theory have been supported in organizational, societal, family, and other social settings. Thus, the EIM helps provide a theory-based understanding for collecting and reviewing users' reactions to, and acceptance or rejection of, a new technology or system. The case study (implementation of a patient scheduling and appointment setting system in a large health maintenance organization) illustrates how the EIM can be used to examine users' reactions to the implementation of a new system. PMID:10641966

Propagation of Cutaneous Thermal Injury: A Mathematical Model

PubMed Central

Xue, Chuan; Chou, Ching-Shan; Kao, Chiu-Yen; Sen, Chandan K.; Friedman, Avner

2012-01-01

Cutaneous burn wounds represent a significant public health problem with 500,000 patients per year in the U.S. seeking medical attention. Immediately after skin burn injury, the volume of the wound burn expands due to a cascade of chemical reactions, including lipid peroxidation chain reactions. Based on these chemical reactions, the present paper develops for the first time a three-dimensional mathematical model to quantify the propagation of tissue damage within 12 hours post initial burn. We use the model to investigate the effect of supplemental antioxidant vitamin E for stopping the propagation. We show, for example, that if the production rate of vitamin E is increased, post burn, by five times the natural production in a healthy tissue, then this would slow down the lipid peroxide propagation by at least 50%. Our model is formulated in terms of differential equations, and sensitivity analysis is performed on the parameters to ensure the robustness of the results. PMID:22211391

A Model for Teaching Experiential Counseling Interventions to Novice Counselors.

ERIC Educational Resources Information Center

Cummings, Anne L.

1992-01-01

Describes model for teaching experiential interventions to novice counselors. Includes two experiential interventions that are focus for new model: two-chair approach based on Gestalt therapy principles and resolution of problematic reaction points. Cognitive, affective, and behavioral concepts of model are related to transfer of learning with the…

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

Development of an alkaline/surfactant/polymer compositional reservoir simulator

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

Bhuyan, D.

1989-01-01

The mathematical formulation of a generalized three-dimensional compositional reservoir simulator for high-pH chemical flooding processes is presented in this work. The model assumes local thermodynamic equilibrium with respect to both reaction chemistry and phase behavior and calculates equilibrium electrolyte and phase compositions as a function of time and position. The reaction chemistry considers aqueous electrolytic chemistry, precipitation/dissolution of minerals, ion exchange reactions on matrix surface, reaction of acidic components of crude oil with the bases in the aqueous solution and cation exchange reactions with the micelles. The simulator combines this detailed reaction chemistry associated with these processes with the extensivemore » physical and flow property modeling schemes of an existing chemical flood simulator (UTCHEM) to model the multiphase, multidimensional displacement processes. The formulation of the chemical equilibrium model is quite general and is adaptable to simulate a variety of chemical descriptions. In addition to its use in the simulation of high-pH chemical flooding processes, the model will find application in the simulation of other reactive flow problems like the ground water contamination, reinjection of produced water, chemical waste disposal, etc. in one, two or three dimensions and under multiphase flow conditions. In this work, the model is used to simulate several hypothetical cases of high-pH chemical floods, which include cases from a simple alkaline preflush of a micellar/polymer flood to surfactant enhanced alkaline-polymer flooding and the results are analyzed. Finally, a few published alkaline, alkaline-polymer and surfactant-alkaline-polymer corefloods are simulated and compared with the experimental results.« less

Combining SVM and flame radiation to forecast BOF end-point

NASA Astrophysics Data System (ADS)

Wen, Hongyuan; Zhao, Qi; Xu, Lingfei; Zhou, Munchun; Chen, Yanru

2009-05-01

Because of complex reactions in Basic Oxygen Furnace (BOF) for steelmaking, the main end-point control methods of steelmaking have insurmountable difficulties. Aiming at these problems, a support vector machine (SVM) method for forecasting the BOF steelmaking end-point is presented based on flame radiation information. The basis is that the furnace flame is the performance of the carbon oxygen reaction, because the carbon oxygen reaction is the major reaction in the steelmaking furnace. The system can acquire spectrum and image data quickly in the steelmaking adverse environment. The structure of SVM and the multilayer feed-ward neural network are similar, but SVM model could overcome the inherent defects of the latter. The model is trained and forecasted by using SVM and some appropriate variables of light and image characteristic information. The model training process follows the structure risk minimum (SRM) criterion and the design parameter can be adjusted automatically according to the sampled data in the training process. Experimental results indicate that the prediction precision of the SVM model and the executive time both meet the requirements of end-point judgment online.

Investigation and kinetic evaluation of the reactions of hydroxymethylfurfural with amino and thiol groups of amino acids.

PubMed

Hamzalıoğlu, Aytül; Gökmen, Vural

2018-02-01

In this study, reactions of hydroxymethylfurfural (HMF) with selected amino acids (arginine, cysteine and lysine) were investigated in HMF-amino acid (high moisture) and Coffee-amino acid (low moisture) model systems at 5, 25 and 50°C. The results revealed that HMF reacted efficiently and effectively with amino acids in both high and low moisture model systems. High-resolution mass spectrometry (HRMS) analyses of the reaction mixtures confirmed the formations of Michael adduct and Schiff base of HMF with amino acids. Calculated pseudo-first order reaction rate constants were in the following order; k Cysteine >k Arginine >k Lysine for high moisture model systems. Comparing to these rate constants, the k Cysteine decreased whereas, k Arginine and k Lysine increased under the low moisture conditions of Coffee-amino acid model systems. The temperature dependence of the rate constants was found to obey the Arrhenius law in a temperature range of 5-50°C under both low and high moisture conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

DEF: an automated dead-end filling approach based on quasi-endosymbiosis.

PubMed

Liu, Lili; Zhang, Zijun; Sheng, Taotao; Chen, Ming

2017-02-01

Gap filling for the reconstruction of metabolic networks is to restore the connectivity of metabolites via finding high-confidence reactions that could be missed in target organism. Current methods for gap filling either fall into the network topology or have limited capability in finding missing reactions that are indirectly related to dead-end metabolites but of biological importance to the target model. We present an automated dead-end filling (DEF) approach, which is derived from the wisdom of endosymbiosis theory, to fill gaps by finding the most efficient dead-end utilization paths in a constructed quasi-endosymbiosis model. The recalls of reactions and dead ends of DEF reach around 73% and 86%, respectively. This method is capable of finding indirectly dead-end-related reactions with biological importance for the target organism and is applicable to any given metabolic model. In the E. coli iJR904 model, for instance, about 42% of the dead-end metabolites were fixed by our proposed method. DEF is publicly available at http://bis.zju.edu.cn/DEF/. mchen@zju.edu.cn Supplementary data are available at Bioinformatics online.

Computing molecular fluctuations in biochemical reaction systems based on a mechanistic, statistical theory of irreversible processes.

PubMed

Kulasiri, Don

2011-01-01

We discuss the quantification of molecular fluctuations in the biochemical reaction systems within the context of intracellular processes associated with gene expression. We take the molecular reactions pertaining to circadian rhythms to develop models of molecular fluctuations in this chapter. There are a significant number of studies on stochastic fluctuations in intracellular genetic regulatory networks based on single cell-level experiments. In order to understand the fluctuations associated with the gene expression in circadian rhythm networks, it is important to model the interactions of transcriptional factors with the E-boxes in the promoter regions of some of the genes. The pertinent aspects of a near-equilibrium theory that would integrate the thermodynamical and particle dynamic characteristics of intracellular molecular fluctuations would be discussed, and the theory is extended by using the theory of stochastic differential equations. We then model the fluctuations associated with the promoter regions using general mathematical settings. We implemented ubiquitous Gillespie's algorithms, which are used to simulate stochasticity in biochemical networks, for each of the motifs. Both the theory and the Gillespie's algorithms gave the same results in terms of the time evolution of means and variances of molecular numbers. As biochemical reactions occur far away from equilibrium-hence the use of the Gillespie algorithm-these results suggest that the near-equilibrium theory should be a good approximation for some of the biochemical reactions. © 2011 Elsevier Inc. All rights reserved.

A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater

USGS Publications Warehouse

Han, L. F; Plummer, Niel

2016-01-01

Numerous methods have been proposed to estimate the pre-nuclear-detonation 14C content of dissolved inorganic carbon (DIC) recharged to groundwater that has been corrected/adjusted for geochemical processes in the absence of radioactive decay (14C0) - a quantity that is essential for estimation of radiocarbon age of DIC in groundwater. The models/approaches most commonly used are grouped as follows: (1) single-sample-based models, (2) a statistical approach based on the observed (curved) relationship between 14C and δ13C data for the aquifer, and (3) the geochemical mass-balance approach that constructs adjustment models accounting for all the geochemical reactions known to occur along a groundwater flow path. This review discusses first the geochemical processes behind each of the single-sample-based models, followed by discussions of the statistical approach and the geochemical mass-balance approach. Finally, the applications, advantages and limitations of the three groups of models/approaches are discussed.The single-sample-based models constitute the prevailing use of 14C data in hydrogeology and hydrological studies. This is in part because the models are applied to an individual water sample to estimate the 14C age, therefore the measurement data are easily available. These models have been shown to provide realistic radiocarbon ages in many studies. However, they usually are limited to simple carbonate aquifers and selection of model may have significant effects on 14C0 often resulting in a wide range of estimates of 14C ages.Of the single-sample-based models, four are recommended for the estimation of 14C0 of DIC in groundwater: Pearson's model, (Ingerson and Pearson, 1964; Pearson and White, 1967), Han & Plummer's model (Han and Plummer, 2013), the IAEA model (Gonfiantini, 1972; Salem et al., 1980), and Oeschger's model (Geyh, 2000). These four models include all processes considered in single-sample-based models, and can be used in different ranges of 13C values.In contrast to the single-sample-based models, the extended Gonfiantini & Zuppi model (Gonfiantini and Zuppi, 2003; Han et al., 2014) is a statistical approach. This approach can be used to estimate 14C ages when a curved relationship between the 14C and 13C values of the DIC data is observed. In addition to estimation of groundwater ages, the relationship between 14C and δ13C data can be used to interpret hydrogeological characteristics of the aquifer, e.g. estimating apparent rates of geochemical reactions and revealing the complexity of the geochemical environment, and identify samples that are not affected by the same set of reactions/processes as the rest of the dataset. The investigated water samples may have a wide range of ages, and for waters with very low values of 14C, the model based on statistics may give more reliable age estimates than those obtained from single-sample-based models. In the extended Gonfiantini & Zuppi model, a representative system-wide value of the initial 14C content is derived from the 14C and δ13C data of DIC and can differ from that used in single-sample-based models. Therefore, the extended Gonfiantini & Zuppi model usually avoids the effect of modern water components which might retain ‘bomb’ pulse signatures.The geochemical mass-balance approach constructs an adjustment model that accounts for all the geochemical reactions known to occur along an aquifer flow path (Plummer et al., 1983; Wigley et al., 1978; Plummer et al., 1994; Plummer and Glynn, 2013), and includes, in addition to DIC, dissolved organic carbon (DOC) and methane (CH4). If sufficient chemical, mineralogical and isotopic data are available, the geochemical mass-balance method can yield the most accurate estimates of the adjusted radiocarbon age. The main limitation of this approach is that complete information is necessary on chemical, mineralogical and isotopic data and these data are often limited.Failure to recognize the limitations and underlying assumptions on which the various models and approaches are based can result in a wide range of estimates of 14C0 and limit the usefulness of radiocarbon as a dating tool for groundwater. In each of the three generalized approaches (single-sample-based models, statistical approach, and geochemical mass-balance approach), successful application depends on scrutiny of the isotopic (14C and 13C) and chemical data to conceptualize the reactions and processes that affect the 14C content of DIC in aquifers. The recently developed graphical analysis method is shown to aid in determining which approach is most appropriate for the isotopic and chemical data from a groundwater system.

Phase-field model for the two-phase lithiation of silicon

NASA Astrophysics Data System (ADS)

Gao, Fangliang; Hong, Wei

2016-09-01

As an ideal anode material, silicon has the highest lithium-ion capacity in theory, but the broader application is limited by the huge volumetric strain caused by lithium insertion and extraction. To better understand the physical process and to resolve the related reliability issue, enormous efforts have been made. Recent experiments observed sharp reaction fronts in both crystalline and amorphous silicon during the first lithiation half-cycle. Such a concentration profile indicates that the process is likely to be reaction limited. Based on this postulation, a phase-field model is developed and implemented into a finite-element code to simulate the coupled large inelastic deformation and motion of the reaction front in a silicon electrode. In contrast to most existing models, the model treats both volumetric and deviatoric inelastic deformation in silicon as a direct consequence of the lithiation at the reaction front. The amount of deviatoric deformation is determined by using the recently developed kinetic model of stress-induced anisotropic reaction. By considering the role of stress in the lithiation process, this model successfully recovers the self-limiting phenomenon of silicon electrodes, and relates it to the local geometry of electrodes. The model is also used to evaluate the energy-release rate of the surface crack on a spherical electrode, and the result suggests a critical size of silicon nanoparticles to avert fracture. As examples, the morphology evolution of a silicon disk and a Si nanowire during lithiation are also investigated.

Chemical structure-based predictive model for the oxidation of trace organic contaminants by sulfate radical.

PubMed

Ye, Tiantian; Wei, Zongsu; Spinney, Richard; Tang, Chong-Jian; Luo, Shuang; Xiao, Ruiyang; Dionysiou, Dionysios D

2017-06-01

Second-order rate constants [Formula: see text] for the reaction of sulfate radical anion (SO 4 •- ) with trace organic contaminants (TrOCs) are of scientific and practical importance for assessing their environmental fate and removal efficiency in water treatment systems. Here, we developed a chemical structure-based model for predicting [Formula: see text] using 32 molecular fragment descriptors, as this type of model provides a quick estimate at low computational cost. The model was constructed using the multiple linear regression (MLR) and artificial neural network (ANN) methods. The MLR method yielded adequate fit for the training set (R training 2 =0.88,n=75) and reasonable predictability for the validation set (R validation 2 =0.62,n=38). In contrast, the ANN method produced a more statistical robustness but rather poor predictability (R training 2 =0.99andR validation 2 =0.42). The reaction mechanisms of SO 4 •- reactivity with TrOCs were elucidated. Our result shows that the coefficients of functional groups reflect their electron donating/withdrawing characters. For example, electron donating groups typically exhibit positive coefficients, indicating enhanced SO 4 •- reactivity. Electron withdrawing groups exhibit negative values, indicating reduced reactivity. With its quick and accurate features, we applied this structure-based model to 55 discrete TrOCs culled from the Contaminant Candidate List 4, and quantitatively compared their removal efficiency with SO 4 •- and OH in the presence of environmental matrices. This high-throughput model helps prioritize TrOCs that are persistent to SO 4 •- based oxidation technologies at the screening level, and provide diagnostics of SO 4 •- reaction mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Measurement of the cross section of the residues from the 11B-induced reaction on 89Y and 93Nb: Production of 97Ru and Rhm101

NASA Astrophysics Data System (ADS)

Kumar, Deepak; Maiti, Moumita

2017-06-01

Background: The heavy-ion induced reactions on intermediate mass targets are complex in nature, even at the low energies. To understand those nuclear reaction phenomena in detail, more experimental studies are required in a wide range of energies. Purpose: Investigation of heavy-ion reactions by measuring production cross sections of the residues produced in the 11B-induced reactions on 89Y and 93Nb at low energies, near and above the barrier, and to check the effectiveness of the different nuclear models to explain them. Further, aim is also to optimize the production parameters of neutron deficient medically relevant 97Ru and Rhm101 radioisotopes produced in those reactions, respectively. Method: The 11B beam was allowed to impinge on 89Y and 93Nb foils supported by an aluminum (Al) catcher foil, arranged in a stack, in 27.5-58.7 and 30.6-62.3 MeV energy range, respectively. The off-line γ -ray spectrometry was carried out after the end of bombardment to measure the activity of the radionuclides produced in each foil and cross sections were calculated. Measured cross-sectional data were analyzed in terms of compound and precompound model calculations. Results: The measured cross sections of Ru,9597, 96,95,94Tc, Mom93, Ym90 radionuclides produced in the 11B+89Y reaction, and 101,100,99Pd, 101m,100,99mRh, 97Ru produced in the 11B+93Nb reaction showed good agreement with the model calculations based on the Hauser-Feshbach formulation and exciton model. Unlike theoretical estimation, consistent production of Ym90 was observed in the 11B+89Y reaction. Substantial pre-equilibrium contribution was noticed in the 3 n reaction channel in both reactions. Conclusions: Theoretical estimations confirmed that major production yields are mostly contributed by the compound reaction process. Pre-equilibrium emissions contributed at the high energy tail of the 3 n channel for both reactions. Moreover, an indirect signature of a direct reaction influence was also observed in the Ym90 production.

Sensitivity of Polar Stratospheric Ozone Loss to Uncertainties in Chemical Reaction Kinetics

NASA Technical Reports Server (NTRS)

Kawa, S. Randolph; Stolarski, Richard S.; Douglass, Anne R.; Newman, Paul A.

2008-01-01

Several recent observational and laboratory studies of processes involved in polar stratospheric ozone loss have prompted a reexamination of aspect of out understanding for this key indicator of global change. To a large extent, our confidence in understanding and projecting changes in polar and global ozone is based on our ability to to simulate these process in numerical models of chemistry and transport. These models depend on laboratory-measured kinetic reaction rates and photlysis cross section to simulate molecular interactions. In this study we use a simple box-model scenario for Antarctic ozone to estimate the uncertainty in loss attributable to known reaction kinetic uncertainties. Following the method of earlier work, rates and uncertainties from the latest laboratory evaluation are applied in random combinations. We determine the key reaction and rates contributing the largest potential errors and compare the results to observations to evaluate which combinations are consistent with atmospheric data. Implications for our theoretical and practical understanding of polar ozone loss will be assessed.

Kinetic Model for the Radical Degradation of Tri-Halonitromethane Disinfection Byproducts in Water

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

Stephen P. Mezyk; Bruce J. Mincher; William J. Cooper

The halonitromethanes (HNMs) are byproducts of the ozonation and chlorine/chloramine treatment of drinking waters. Although typically occurring at low concentrations HNMs have high cytotoxicity and mutagenicity, and may therefore represent a significant human health hazard. In this study, we have investigated the radical based mineralization of fully-halogenated HNMs in water using the congeners bromodichloronitromethane and chlorodibromonitromethane. We have combined absolute reaction rate constants for their reactions with the hydroxyl radical and the hydrated electron as measured by electron pulse radiolysis and analytical measurements of stable product concentrations obtained by 60Co steady-state radiolysis with a kinetic computer model that includes watermore » radiolysis reactions and halide/nitrogen oxide radical chemistry to fully elucidate the reaction pathways of these HNMs. These results are compared to our previous similar study of the fully chlorinated HNM chloropicrin. The full optimized computer model, suitable for predicting the behavior of this class of compounds in irradiated drinking water is provided.« less

Mesoscopic Modeling of Blood Clotting: Coagulation Cascade and Platelets Adhesion

NASA Astrophysics Data System (ADS)

Yazdani, Alireza; Li, Zhen; Karniadakis, George

2015-11-01

The process of clot formation and growth at a site on a blood vessel wall involve a number of multi-scale simultaneous processes including: multiple chemical reactions in the coagulation cascade, species transport and flow. To model these processes we have incorporated advection-diffusion-reaction (ADR) of multiple species into an extended version of Dissipative Particle Dynamics (DPD) method which is considered as a coarse-grained Molecular Dynamics method. At the continuum level this is equivalent to the Navier-Stokes equation plus one advection-diffusion equation for each specie. The chemistry of clot formation is now understood to be determined by mechanisms involving reactions among many species in dilute solution, where reaction rate constants and species diffusion coefficients in plasma are known. The role of blood particulates, i.e. red cells and platelets, in the clotting process is studied by including them separately and together in the simulations. An agonist-induced platelet activation mechanism is presented, while platelets adhesive dynamics based on a stochastic bond formation/dissociation process is included in the model.

Linear free energy relationships between aqueous phase hydroxyl radical reaction rate constants and free energy of activation.

PubMed

Minakata, Daisuke; Crittenden, John

2011-04-15

The hydroxyl radical (HO(•)) is a strong oxidant that reacts with electron-rich sites on organic compounds and initiates complex radical chain reactions in aqueous phase advanced oxidation processes (AOPs). Computer based kinetic modeling requires a reaction pathway generator and predictions of associated reaction rate constants. Previously, we reported a reaction pathway generator that can enumerate the most important elementary reactions for aliphatic compounds. For the reaction rate constant predictor, we develop linear free energy relationships (LFERs) between aqueous phase literature-reported HO(•) reaction rate constants and theoretically calculated free energies of activation for H-atom abstraction from a C-H bond and HO(•) addition to alkenes. The theoretical method uses ab initio quantum mechanical calculations, Gaussian 1-3, for gas phase reactions and a solvation method, COSMO-RS theory, to estimate the impact of water. Theoretically calculated free energies of activation are found to be within approximately ±3 kcal/mol of experimental values. Considering errors that arise from quantum mechanical calculations and experiments, this should be within the acceptable errors. The established LFERs are used to predict the HO(•) reaction rate constants within a factor of 5 from the experimental values. This approach may be applied to other reaction mechanisms to establish a library of rate constant predictions for kinetic modeling of AOPs.

Accuracy of Reaction Cross Section for Exotic Nuclei in Glauber Model Based on MCMC Diagnostics

NASA Astrophysics Data System (ADS)

Rueter, Keiti; Novikov, Ivan

2017-01-01

Parameters of a nuclear density distribution for an exotic nuclei with halo or skin structures can be determined from the experimentally measured reaction cross-section. In the presented work, to extract parameters such as nuclear size information for a halo and core, we compare experimental data on reaction cross-sections with values obtained using expressions of the Glauber Model. These calculations are performed using a Markov Chain Monte Carlo algorithm. We discuss the accuracy of the Monte Carlo approach and its dependence on k*, the power law turnover point in the discreet power spectrum of the random number sequence and on the lag-1 autocorrelation time of the random number sequence.

Hybrid method for numerical modelling of LWR coolant chemistry

NASA Astrophysics Data System (ADS)

Swiatla-Wojcik, Dorota

2016-10-01

A comprehensive approach is proposed to model radiation chemistry of the cooling water under exposure to neutron and gamma radiation at 300 °C. It covers diffusion-kinetic processes in radiation tracks and secondary reactions in the bulk coolant. Steady-state concentrations of the radiolytic products have been assessed based on the simulated time dependent concentration profiles. The principal reactions contributing to the formation of H2, O2 and H2O2 were indicated. Simulation was carried out depending on the amount of extra hydrogen dissolved in the coolant to reduce concentration of corrosive agents. High sensitivity to the rate of reaction H+H2O=OH+H2 is shown and discussed.

Microscopic modelling of ignition and burning for well-arranged energetic crystals in response to drop-weight impact

NASA Astrophysics Data System (ADS)

Wu, Yanqing; Huang, Fenglei; Zhou, Min

2014-05-01

To probe into impact sensitivity of energetic crystals, a theoretical approach was developed for modelling a single layer of energetic particles between upper striker and below base. Considering the particle plasticity, frictional heating, melting, fracture, and chemical reaction at particle level, effects of loading parameters and sample characteristics on time-to-ignition and burning rate were compared. Finite element numerical simulations were simultaneously performed to provide supporting evidence for thermo-mechanical interactions among energetic particles. Once hot- spots ignition occurred during impact, the macrokinetics of chemical reactions were formulated by hot-spots density, combustion wave velocity and geometric factor. The resulting reaction may or may not develop into a violent event, may be sustained or be extinguished, which can be revealed from the subsequent burn reaction rate.

Thermocatalytic Behavior of Manganese (IV) Oxide as Nanoporous Material on the Dissociation of a Gas Mixture Containing Hydrogen Peroxide

PubMed Central

Jildeh, Zaid B.; Kirchner, Patrick; Wagner, Patrick H.

2018-01-01

In this article, we present an overview on the thermocatalytic reaction of hydrogen peroxide (H2O2) gas on a manganese (IV) oxide (MnO2) catalytic structure. The principle of operation and manufacturing techniques are introduced for a calorimetric H2O2 gas sensor based on porous MnO2. Results from surface analyses by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) of the catalytic material provide indication of the H2O2 dissociation reaction schemes. The correlation between theory and the experiments is documented in numerical models of the catalytic reaction. The aim of the numerical models is to provide further information on the reaction kinetics and performance enhancement of the porous MnO2 catalyst. PMID:29690519

Computational SN 2-Type Mechanism for the Difluoromethylation of Lithium Enolate with Fluoroform through Bimetallic C-F Bond Dual Activation.

PubMed

Honda, Kazuya; Harris, Travis V; Hatanaka, Miho; Morokuma, Keiji; Mikami, Koichi

2016-06-20

The reaction mechanism for difluoromethylation of lithium enolates with fluoroform was analyzed computationally (DFT calculations with the artificial force induced reaction (AFIR) method and solvation model based on density (SMD) solvation model (THF)), showing an SN 2-type carbon-carbon bond formation; the "bimetallic" lithium enolate and lithium trifluoromethyl carbenoid exert the C-F bond "dual" activation, in contrast to the monometallic butterfly-shaped carbenoid in the Simmons-Smith reaction. Lithium enolates, generated by the reaction of 2 equiv. of lithium hexamethyldisilazide (rather than 1 or 3 equiv.) with the cheap difluoromethylating species fluoroform, are the most useful alkali metal intermediates for the synthesis of pharmaceutically important α-difluoromethylated carbonyl products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

User's guide to PHREEQC (Version 2) : a computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations

USGS Publications Warehouse

Parkhurst, David L.; Appelo, C.A.J.

1999-01-01

PHREEQC version 2 is a computer program written in the C programming language that is designed to perform a wide variety of low-temperature aqueous geochemical calculations. PHREEQC is based on an ion-association aqueous model and has capabilities for (1) speciation and saturation-index calculations; (2) batch-reaction and one-dimensional (1D) transport calculations involving reversible reactions, which include aqueous, mineral, gas, solid-solution, surface-complexation, and ion-exchange equilibria, and irreversible reactions, which include specified mole transfers of reactants, kinetically controlled reactions, mixing of solutions, and temperature changes; and (3) inverse modeling, which finds sets of mineral and gas mole transfers that account for differences in composition between waters, within specified compositional uncertainty limits.New features in PHREEQC version 2 relative to version 1 include capabilities to simulate dispersion (or diffusion) and stagnant zones in 1D-transport calculations, to model kinetic reactions with user-defined rate expressions, to model the formation or dissolution of ideal, multicomponent or nonideal, binary solid solutions, to model fixed-volume gas phases in addition to fixed-pressure gas phases, to allow the number of surface or exchange sites to vary with the dissolution or precipitation of minerals or kinetic reactants, to include isotope mole balances in inverse modeling calculations, to automatically use multiple sets of convergence parameters, to print user-defined quantities to the primary output file and (or) to a file suitable for importation into a spreadsheet, and to define solution compositions in a format more compatible with spreadsheet programs. This report presents the equations that are the basis for chemical equilibrium, kinetic, transport, and inverse-modeling calculations in PHREEQC; describes the input for the program; and presents examples that demonstrate most of the program's capabilities.

Prediction of reaction knockouts to maximize succinate production by Actinobacillus succinogenes

PubMed Central

Nag, Ambarish; St. John, Peter C.; Crowley, Michael F.

2018-01-01

Succinate is a precursor of multiple commodity chemicals and bio-based succinate production is an active area of industrial bioengineering research. One of the most important microbial strains for bio-based production of succinate is the capnophilic gram-negative bacterium Actinobacillus succinogenes, which naturally produces succinate by a mixed-acid fermentative pathway. To engineer A. succinogenes to improve succinate yields during mixed acid fermentation, it is important to have a detailed understanding of the metabolic flux distribution in A. succinogenes when grown in suitable media. To this end, we have developed a detailed stoichiometric model of the A. succinogenes central metabolism that includes the biosynthetic pathways for the main components of biomass—namely glycogen, amino acids, DNA, RNA, lipids and UDP-N-Acetyl-α-D-glucosamine. We have validated our model by comparing model predictions generated via flux balance analysis with experimental results on mixed acid fermentation. Moreover, we have used the model to predict single and double reaction knockouts to maximize succinate production while maintaining growth viability. According to our model, succinate production can be maximized by knocking out either of the reactions catalyzed by the PTA (phosphate acetyltransferase) and ACK (acetyl kinase) enzymes, whereas the double knockouts of PEPCK (phosphoenolpyruvate carboxykinase) and PTA or PEPCK and ACK enzymes are the most effective in increasing succinate production. PMID:29381705

Prediction of reaction knockouts to maximize succinate production by Actinobacillus succinogenes.

PubMed

Nag, Ambarish; St John, Peter C; Crowley, Michael F; Bomble, Yannick J

2018-01-01

Succinate is a precursor of multiple commodity chemicals and bio-based succinate production is an active area of industrial bioengineering research. One of the most important microbial strains for bio-based production of succinate is the capnophilic gram-negative bacterium Actinobacillus succinogenes, which naturally produces succinate by a mixed-acid fermentative pathway. To engineer A. succinogenes to improve succinate yields during mixed acid fermentation, it is important to have a detailed understanding of the metabolic flux distribution in A. succinogenes when grown in suitable media. To this end, we have developed a detailed stoichiometric model of the A. succinogenes central metabolism that includes the biosynthetic pathways for the main components of biomass-namely glycogen, amino acids, DNA, RNA, lipids and UDP-N-Acetyl-α-D-glucosamine. We have validated our model by comparing model predictions generated via flux balance analysis with experimental results on mixed acid fermentation. Moreover, we have used the model to predict single and double reaction knockouts to maximize succinate production while maintaining growth viability. According to our model, succinate production can be maximized by knocking out either of the reactions catalyzed by the PTA (phosphate acetyltransferase) and ACK (acetyl kinase) enzymes, whereas the double knockouts of PEPCK (phosphoenolpyruvate carboxykinase) and PTA or PEPCK and ACK enzymes are the most effective in increasing succinate production.

Analysis of Functional Coupling: Mitochondrial Creatine Kinase and Adenine Nucleotide Translocase

PubMed Central

Vendelin, Marko; Lemba, Maris; Saks, Valdur A.

2004-01-01

The mechanism of functional coupling between mitochondrial creatine kinase (MiCK) and adenine nucleotide translocase (ANT) in isolated heart mitochondria is analyzed. Two alternative mechanisms are studied: 1), dynamic compartmentation of ATP and ADP, which assumes the differences in concentrations of the substrates between intermembrane space and surrounding solution due to some diffusion restriction and 2), direct transfer of the substrates between MiCK and ANT. The mathematical models based on these possible mechanisms were composed and simulation results were compared with the available experimental data. The first model, based on a dynamic compartmentation mechanism, was not sufficient to reproduce the measured values of apparent dissociation constants of MiCK reaction coupled to oxidative phosphorylation. The second model, which assumes the direct transfer of substrates between MiCK and ANT, is shown to be in good agreement with experiments—i.e., the second model reproduced the measured constants and the estimated ADP flux, entering mitochondria after the MiCK reaction. This model is thermodynamically consistent, utilizing the free energy profiles of reactions. The analysis revealed the minimal changes in the free energy profile of the MiCK-ANT interaction required to reproduce the experimental data. A possible free energy profile of the coupled MiCK-ANT system is presented. PMID:15240503

Modeling the oxidation kinetics of sono-activated persulfate's process on the degradation of humic acid.

PubMed

Songlin, Wang; Ning, Zhou; Si, Wu; Qi, Zhang; Zhi, Yang

2015-03-01

Ultrasound degradation of humic acid has been investigated in the presence of persulfate anions at ultrasonic frequency of 40 kHz. The effects of persulfate anion concentration, ultrasonic power input, humic acid concentration, reaction time, solution pH and temperature on humic acid removal efficiency were studied. It is found that up to 90% humic acid removal efficiency was achieved after 2 h reaction. In this system, sulfate radicals (SO₄⁻·) were considered to be the mainly oxidant to mineralize humic acid while persulfate anion can hardly react with humic acid directly. A novel kinetic model based on sulfate radicals (SO₄⁻·) oxidation was established to describe the humic acid mineralization process mathematically and chemically in sono-activated persulfate system. According to the new model, ultrasound power, persulfate dosage, solution pH and reaction temperature have great influence on humic acid degradation. Different initial concentration of persulfate anions and humic acid, ultrasonic power, initial pH and reaction temperature have been discussed to valid the effectiveness of the model, and the simulated data showed new model had good agreement with the experiments data.

Adaptive two-regime method: Application to front propagation

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

Robinson, Martin, E-mail: martin.robinson@maths.ox.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk; Flegg, Mark, E-mail: mark.flegg@monash.edu

2014-03-28

The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in termsmore » of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.« less

Computational Modeling of Cobalt-Based Water Oxidation: Current Status and Future Challenges

PubMed Central

Schilling, Mauro; Luber, Sandra

2018-01-01

A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context, mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysts. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability toward real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions. PMID:29721491

Computational Modeling of Cobalt-based Water Oxidation: Current Status and Future Challenges

NASA Astrophysics Data System (ADS)

Schilling, Mauro; Luber, Sandra

2018-04-01

A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysis. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability towards real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions.

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

Room-temperature and temperature-dependent QSRR modelling for predicting the nitrate radical reaction rate constants of organic chemicals using ensemble learning methods.

PubMed

Gupta, S; Basant, N; Mohan, D; Singh, K P

2016-07-01

Experimental determinations of the rate constants of the reaction of NO3 with a large number of organic chemicals are tedious, and time and resource intensive; and the development of computational methods has widely been advocated. In this study, we have developed room-temperature (298 K) and temperature-dependent quantitative structure-reactivity relationship (QSRR) models based on the ensemble learning approaches (decision tree forest (DTF) and decision treeboost (DTB)) for predicting the rate constant of the reaction of NO3 radicals with diverse organic chemicals, under OECD guidelines. Predictive powers of the developed models were established in terms of statistical coefficients. In the test phase, the QSRR models yielded a correlation (r(2)) of >0.94 between experimental and predicted rate constants. The applicability domains of the constructed models were determined. An attempt has been made to provide the mechanistic interpretation of the selected features for QSRR development. The proposed QSRR models outperformed the previous reports, and the temperature-dependent models offered a much wider applicability domain. This is the first report presenting a temperature-dependent QSRR model for predicting the nitrate radical reaction rate constant at different temperatures. The proposed models can be useful tools in predicting the reactivities of chemicals towards NO3 radicals in the atmosphere, hence, their persistence and exposure risk assessment.

Temperament in the Classroom: Children Low in Surgency are More Sensitive to Teachers' Reactions to Emotions

ERIC Educational Resources Information Center

Bassett, Hideko Hamada; Denham, Susanne A.; Fettig, Nicole B.; Curby, Timothy W.; Mohtasham, Mandana; Austin, Nila

2017-01-01

Based on the emotion socialization and bioecological models, the present study examined the contributions of teacher emotion socialization (i.e., teacher reactions to child emotions) on children's social-emotional behaviors, and the moderating effect of child temperamental surgency on these relations in the preschool context. A total of 337…

Detonation Reaction Zones in Condensed Explosives

NASA Astrophysics Data System (ADS)

Tarver, Craig M.

2006-07-01

Experimental measurements using nanosecond time resolved embedded gauges and laser interferometric techniques, combined with Non-Equilibrium Zeldovich - von Neumann - Doling (NEZND) theory and Ignition and Growth reactive flow hydrodynamic modeling, have revealed the average pressure/particle velocity states attained in reaction zones of self-sustaining detonation waves in several solid and liquid explosives. The time durations of these reaction zone processes are discussed for explosives based on pentaerythritol tetranitrate (PETN), nitromethane, octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), triaminitrinitrobenzene(TATB) and trinitrotoluene (TNT).

Thermodynamically based solvent design for enzymatic saccharide acylation with hydroxycinnamic acids in non-conventional media.

PubMed

Zeuner, Birgitte; Kontogeorgis, Georgios M; Riisager, Anders; Meyer, Anne S

2012-02-15

Enzyme-catalyzed synthesis has been widely studied with lipases (EC 3.1.1.3), but feruloyl esterases (FAEs; EC 3.1.1.73) may provide advantages such as higher substrate affinity and regioselectivity in the synthesis of hydroxycinnamate saccharide esters. These compounds are interesting because of their amphiphilicity and antioxidative potential. Synthetic reactions using mono- or disaccharides as one of the substrates may moreover direct new routes for biomass upgrading in the biorefinery. The paper reviews the available data for enzymatic hydroxycinnamate saccharide ester synthesis in organic solvent systems as well as other enzymatic hydroxycinnamate acylations in ionic liquid systems. The choice of solvent system is highly decisive for enzyme stability, selectivity, and reaction yields in these synthesis reactions. To increase the understanding of the reaction environment and to facilitate solvent screening as a crucial part of the reaction design, the review explores the use of activity coefficient models for describing these systems and - more importantly - the use of group contribution model UNIFAC and quantum chemistry based COSMO-RS for thermodynamic predictions and preliminary solvent screening. Surfactant-free microemulsions of a hydrocarbon, a polar alcohol, and water are interesting solvent systems because they accommodate different substrate and product solubilities and maintain enzyme stability. Ionic liquids may provide advantages as solvents in terms of increased substrate and product solubility, higher reactivity and selectivity, as well as tunable physicochemical properties, but their design should be carefully considered in relation to enzyme stability. The treatise shows that thermodynamic modeling tools for solvent design provide a new toolbox to design enzyme-catalyzed synthetic reactions from biomass sources. Copyright © 2011 Elsevier B.V. All rights reserved.

A Uranium Bioremediation Reactive Transport Benchmark

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

Yabusaki, Steven B.; Sengor, Sevinc; Fang, Yilin

A reactive transport benchmark problem set has been developed based on in situ uranium bio-immobilization experiments that have been performed at a former uranium mill tailings site in Rifle, Colorado, USA. Acetate-amended groundwater stimulates indigenous microorganisms to catalyze the reduction of U(VI) to a sparingly soluble U(IV) mineral. The interplay between the flow, acetate loading periods and rates, microbially-mediated and geochemical reactions leads to dynamic behavior in metal- and sulfate-reducing bacteria, pH, alkalinity, and reactive mineral surfaces. The benchmark is based on an 8.5 m long one-dimensional model domain with constant saturated flow and uniform porosity. The 159-day simulation introducesmore » acetate and bromide through the upgradient boundary in 14-day and 85-day pulses separated by a 10 day interruption. Acetate loading is tripled during the second pulse, which is followed by a 50 day recovery period. Terminal electron accepting processes for goethite, phyllosilicate Fe(III), U(VI), and sulfate are modeled using Monod-type rate laws. Major ion geochemistry modeled includes mineral reactions, as well as aqueous and surface complexation reactions for UO2++, Fe++, and H+. In addition to the dynamics imparted by the transport of the acetate pulses, U(VI) behavior involves the interplay between bioreduction, which is dependent on acetate availability, and speciation-controlled surface complexation, which is dependent on pH, alkalinity and available surface complexation sites. The general difficulty of this benchmark is the large number of reactions (74), multiple rate law formulations, a multisite uranium surface complexation model, and the strong interdependency and sensitivity of the reaction processes. Results are presented for three simulators: HYDROGEOCHEM, PHT3D, and PHREEQC.« less

Experimental and Modeling Studies of Crush, Puncture, and Perforation Scenarios in the Steven Impact Test

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

Vandersall, K S; Chidester, S K; Forbes, J W

2002-06-28

The Steven test and associated modeling has greatly increased the fundamental knowledge of practical predictions of impact safety hazards for confined and unconfined explosive charges. Building on a database of initial work, experimental and modeling studies of crush, puncture, and perforation scenarios were investigated using the Steven impact test. The descriptions of crush, puncture, and perforation arose from safety scenarios represented by projectile designs that ''crush'' the energetic material or either ''puncture'' with a pinpoint nose or ''perforate'' the front cover with a transportation hook. As desired, these scenarios offer different aspects of the known mechanisms that control ignition: friction,more » shear and strain. Studies of aged and previously damaged HMX-based high explosives included the use of embedded carbon foil and carbon resistor gauges, high-speed cameras, and blast wave gauges to determine the pressure histories, time required for an explosive reaction, and the relative violence of those reactions, respectively. Various ignition processes were modeled as the initial reaction rate expression in the Ignition and Growth reaction rate equations. Good agreement with measured threshold velocities, pressure histories, and times to reaction was calculated for LX-04 impacted by several projectile geometries using a compression dependent ignition term and an elastic-plastic model with a reasonable yield strength for impact strain rates.« less

Sequence-based Network Completion Reveals the Integrality of Missing Reactions in Metabolic Networks.

PubMed

Krumholz, Elias W; Libourel, Igor G L

2015-07-31

Genome-scale metabolic models are central in connecting genotypes to metabolic phenotypes. However, even for well studied organisms, such as Escherichia coli, draft networks do not contain a complete biochemical network. Missing reactions are referred to as gaps. These gaps need to be filled to enable functional analysis, and gap-filling choices influence model predictions. To investigate whether functional networks existed where all gap-filling reactions were supported by sequence similarity to annotated enzymes, four draft networks were supplemented with all reactions from the Model SEED database for which minimal sequence similarity was found in their genomes. Quadratic programming revealed that the number of reactions that could partake in a gap-filling solution was vast: 3,270 in the case of E. coli, where 72% of the metabolites in the draft network could connect a gap-filling solution. Nonetheless, no network could be completed without the inclusion of orphaned enzymes, suggesting that parts of the biochemistry integral to biomass precursor formation are uncharacterized. However, many gap-filling reactions were well determined, and the resulting networks showed improved prediction of gene essentiality compared with networks generated through canonical gap filling. In addition, gene essentiality predictions that were sensitive to poorly determined gap-filling reactions were of poor quality, suggesting that damage to the network structure resulting from the inclusion of erroneous gap-filling reactions may be predictable. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Efficient approach to include molecular polarizations using charge and atom dipole response kernels to calculate free energy gradients in the QM/MM scheme.

PubMed

Asada, Toshio; Ando, Kanta; Sakurai, Koji; Koseki, Shiro; Nagaoka, Masataka

2015-10-28

An efficient approach to evaluate free energy gradients (FEGs) within the quantum mechanical/molecular mechanical (QM/MM) framework has been proposed to clarify reaction processes on the free energy surface (FES) in molecular assemblies. The method is based on response kernel approximations denoted as the charge and the atom dipole response kernel (CDRK) model that include explicitly induced atom dipoles. The CDRK model was able to reproduce polarization effects for both electrostatic interactions between QM and MM regions and internal energies in the QM region obtained by conventional QM/MM methods. In contrast to charge response kernel (CRK) models, CDRK models could be applied to various kinds of molecules, even linear or planer molecules, without using imaginary interaction sites. Use of the CDRK model enabled us to obtain FEGs on QM atoms in significantly reduced computational time. It was also clearly demonstrated that the time development of QM forces of the solvated propylene carbonate radical cation (PC˙(+)) provided reliable results for 1 ns molecular dynamics (MD) simulation, which were quantitatively in good agreement with expensive QM/MM results. Using FEG and nudged elastic band (NEB) methods, we found two optimized reaction paths on the FES for decomposition reactions to generate CO2 molecules from PC˙(+), whose reaction is known as one of the degradation mechanisms in the lithium-ion battery. Two of these reactions proceed through an identical intermediate structure whose molecular dipole moment is larger than that of the reactant to be stabilized in the solvent, which has a high relative dielectric constant. Thus, in order to prevent decomposition reactions, PC˙(+) should be modified to have a smaller dipole moment along two reaction paths.

Recycling Frank: Spontaneous emergence of homochirality in noncatalytic systems

PubMed Central

Plasson, Raphaël; Bersini, Hugues; Commeyras, Auguste

2004-01-01

In this work, we introduce a prebiotically relevant protometabolic pattern corresponding to an engine of deracemization by using an external energy source. The spontaneous formation of a nonracemic mixture of chiral compounds can be observed in out-of-equilibrium systems via a symmetry-breaking phenomenon. This observation is possible thanks to chirally selective autocatalytic reactions (Frank's model) [Frank, F. C. (1953) Biochim. Biophys. Acta 11, 459–463]. We show that the use of a Frank-like model in a recycled system composed of reversible chemical reactions, rather than the classical irreversible system, allows for the emergence of a synergetic autoinduction from simple reactions, without any autocatalytic or even catalytic reaction. This model is described as a theoretical framework, based on the stereoselective reactivity of preexisting chiral monomeric building blocks (polymerization, epimerization, and depolymerization) maintained out of equilibrium by a continuous energy income, via an activation reaction. It permits the self-conversion of all monomeric subunits into a single chiral configuration. Real prebiotic systems of amino acid derivatives can be described on this basis. They are shown to be able to spontaneously reach a stable nonracemic state in a few centuries. In such systems, the presence of epimerization reactions is no more destructive, but in contrast is the central driving force of the unstabilization of the racemic state. PMID:15548617

Oxygen reduction on a Pt(111) catalyst in HT-PEM fuel cells by density functional theory

NASA Astrophysics Data System (ADS)

Sun, Hong; Li, Jie; Almheiri, Saif; Xiao, Jianyu

2017-08-01

The oxygen reduction reaction plays an important role in the performance of high-temperature proton exchange membrane (HT-PEM) fuel cells. In this study, a molecular dynamics model, which is based on the density functional theory and couples the system's energy, the exchange-correlation energy functional, the charge density distribution function, and the simplified Kohn-Sham equation, was developed to simulate the oxygen reduction reaction on a Pt(111) surface. Additionally, an electrochemical reaction system on the basis of a four-electron reaction mechanism was also developed for this simulation. The reaction path of the oxygen reduction reaction, the product structure of each reaction step and the system's energy were simulated. It is found that the first step reaction of the first hydrogen ion with the oxygen molecule is the controlling step of the overall reaction. Increasing the operating temperature speeds up the first step reaction rate and slightly decreases its reaction energy barrier. Our results provide insight into the working principles of HT-PEM fuel cells.

Formation of MoS2 inorganic fullerenes (IFs) by the reaction of MoO3 nanobelts and S.

PubMed

Li, Xiao Lin; Li, Ya Dong

2003-06-16

The reaction of MoO3 and S at temperatures higher than 300 degrees C in an argon atmosphere provides a convenient and effective method for the synthesis of MoS2 nanocrystalline substances. MoS2 nanotubes and fullerene-like nanoparticles have been obtained by the reaction at 850 degrees C under well-controlled conditions. The influences of reaction temperature and duration were carefully investigated in this paper. All of the nanostructures were characterized by Xray powder diffraction (XRD), transmission electron microscopy (TEM), and high-resolution transmission electron microscopy (HRTEM). A stepwise reaction model and rolling mechanism were proposed based on the experimental results.

Description of alpha-nucleus interaction cross sections for cosmic ray shielding studies

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Townsend, Lawrence W.; Wilson, John W.

1993-01-01

Nuclear interactions of high-energy alpha particles with target nuclei important for cosmic ray studies are discussed. Models for elastic, quasi-elastic, and breakup reactions are presented and compared with experimental data. Energy-dependent interaction cross sections and secondary spectra are presented based on theoretical models and the limited experimental data base.

Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons.

PubMed

Lin, Zhongwei; Tropper, Carl; Mcdougal, Robert A; Patoary, Mohammand Nazrul Ishlam; Lytton, William W; Yao, Yiping; Hines, Michael L

2017-07-01

Cells exhibit stochastic behavior when the number of molecules is small. Hence a stochastic reaction-diffusion simulator capable of working at scale can provide a more accurate view of molecular dynamics within the cell. This paper describes a parallel discrete event simulator, Neuron Time Warp-Multi Thread (NTW-MT), developed for the simulation of reaction diffusion models of neurons. To the best of our knowledge, this is the first parallel discrete event simulator oriented towards stochastic simulation of chemical reactions in a neuron. The simulator was developed as part of the NEURON project. NTW-MT is optimistic and thread-based, which attempts to capitalize on multi-core architectures used in high performance machines. It makes use of a multi-level queue for the pending event set and a single roll-back message in place of individual anti-messages to disperse contention and decrease the overhead of processing rollbacks. Global Virtual Time is computed asynchronously both within and among processes to get rid of the overhead for synchronizing threads. Memory usage is managed in order to avoid locking and unlocking when allocating and de-allocating memory and to maximize cache locality. We verified our simulator on a calcium buffer model. We examined its performance on a calcium wave model, comparing it to the performance of a process based optimistic simulator and a threaded simulator which uses a single priority queue for each thread. Our multi-threaded simulator is shown to achieve superior performance to these simulators. Finally, we demonstrated the scalability of our simulator on a larger CICR model and a more detailed CICR model.

Construction of combustion models for rapeseed methyl ester bio-diesel fuel for internal combustion engine applications.

PubMed

Golovitchev, Valeri I; Yang, Junfeng

2009-01-01

Bio-diesel fuels are non-petroleum-based diesel fuels consisting of long chain alkyl esters produced by the transesterification of vegetable oils, that are intended for use (neat or blended with conventional fuels) in unmodified diesel engines. There have been few reports of studies proposing theoretical models for bio-diesel combustion simulations. In this study, we developed combustion models based on ones developed previously. We compiled the liquid fuel properties, and the existing detailed mechanism of methyl butanoate ester (MB, C(5)H(10)O(2)) oxidation was supplemented by sub-mechanisms for two proposed fuel constituent components, C(7)H(16) and C(7)H(8)O (and then, by mp2d, C(4)H(6)O(2) and propyne, C(3)H(4)) to represent the combustion model for rapeseed methyl ester described by the chemical formula, C(19)H(34)O(2) (or C(19)H(36)O(2)). The main fuel vapor thermal properties were taken as those of methyl palmitate C(19)H(36)O(2) in the NASA polynomial form of the Burcat database. The special global reaction was introduced to "crack" the main fuel into its constituent components. This general reaction included 309 species and 1472 reactions, including soot and NO(x) formation processes. The detailed combustion mechanism was validated using shock-tube ignition-delay data under diesel engine conditions. For constant volume and diesel engine (Volvo D12C) combustion modeling, this mechanism could be reduced to 88 species participating in 363 reactions.

Unifying Theory of Low-Energy Nuclear Reaction and Transmutation Processes in Deuterated/hydrogenated Metals, Acoustic Cavitation, Glow Discharge, and Deuteron Beam Experiments

NASA Astrophysics Data System (ADS)

Kim, Yeong E.; Zubarev, Alexander L.

The most basic theoretical challenge for understanding low-energy nuclear reaction (LENR) and transmutation reaction (LETR) in condensed matters is to find mechanisms by which the large Coulomb barrier between fusing nuclei can be overcome. A unifying theory of LENR and LETR has been developed to provide possible mechanisms for the LENR and LETR processes in matters based on high-density nano-scale and micro-scale quantum plasmas. It is shown that recently developed theoretical models based on Bose-Einstein Fusion (BEF) mechanism and Quantum Plasma Nuclear Fusion (QPNF) mechanism are applicable to the results of many different types of LENR and LETR experiments.

Activation barriers for methylation of DNA bases by dimethyl sulfate

NASA Astrophysics Data System (ADS)

Eichler, Daniel R.; Papadantonakis, George A.

2017-12-01

The SN2 transition states of the methylation reaction of DNA bases with dimethyl sulfate were examined employing DFT/ M06-2X/6-31+G∗ and DFT/B3LYP-D3/6-311+G (2df, 2p) levels of theory. Solvation effects were examined using the conductor-like polarizable continuum model (CPCM). Calculation results and feedback from electrostatic potential maps show that in water, charge separation lowers the activation barriers relative to the gas phase for the reactions at N7 of guanine, N3 of adenine and cytosine. Also, the reaction at the O6 site of guanine is governed by steric interference and exhibits a higher activation barrier in water.

Linking Chemical Electron–Proton Transfer to Proton Pumping in Cytochrome c Oxidase: Broken-Symmetry DFT Exploration of Intermediates along the Catalytic Reaction Pathway of the Iron–Copper Dinuclear Complex

PubMed Central

2015-01-01

After a summary of the problem of coupling electron and proton transfer to proton pumping in cytochrome c oxidase, we present the results of our earlier and recent density functional theory calculations for the dinuclear Fe-a3–CuB reaction center in this enzyme. A specific catalytic reaction wheel diagram is constructed from the calculations, based on the structures and relative energies of the intermediate states of the reaction cycle. A larger family of tautomers/protonation states is generated compared to our earlier work, and a new lowest-energy pathway is proposed. The entire reaction cycle is calculated for the new smaller model (about 185–190 atoms), and two selected arcs of the wheel are chosen for calculations using a larger model (about 205 atoms). We compare the structural and redox energetics and protonation calculations with available experimental data. The reaction cycle map that we have built is positioned for further improvement and testing against experiment. PMID:24960612

Phase transition of traveling waves in bacterial colony pattern

NASA Astrophysics Data System (ADS)

Wakano, Joe Yuichiro; Komoto, Atsushi; Yamaguchi, Yukio

2004-05-01

Depending on the growth condition, bacterial colonies can exhibit different morphologies. Many previous studies have used reaction diffusion equations to reproduce spatial patterns. They have revealed that nonlinear reaction term can produce diverse patterns as well as nonlinear diffusion coefficient. Typical reaction term consists of nutrient consumption, bacterial reproduction, and sporulation. Among them, the functional form of sporulation rate has not been biologically investigated. Here we report experimentally measured sporulation rate. Then, based on the result, a reaction diffusion model is proposed. One-dimensional simulation showed the existence of traveling wave solution. We study the wave form as a function of the initial nutrient concentration and find two distinct types of solution. Moreover, transition between them is very sharp, which is analogous to phase transition. The velocity of traveling wave also shows sharp transition in nonlinear diffusion model, which is consistent with the previous experimental result. The phenomenon can be explained by separatrix in reaction term dynamics. Results of two-dimensional simulation are also shown and discussed.

Full Kinetics from First Principles of the Chlorine Evolution Reaction over a RuO2 (110) Model Electrode.

PubMed

Exner, Kai S; Anton, Josef; Jacob, Timo; Over, Herbert

2016-06-20

Current progress in modern electrocatalysis research is spurred by theory, frequently based on ab initio thermodynamics, where the stable reaction intermediates at the electrode surface are identified, while the actual energy barriers are ignored. This approach is popular in that a simple tool is available for searching for promising electrode materials. However, thermodynamics alone may be misleading to assess the catalytic activity of an electrochemical reaction as we exemplify with the chlorine evolution reaction (CER) over a RuO2 (110) model electrode. The full procedure is introduced, starting from the stable reaction intermediates, computing the energy barriers, and finally performing microkinetic simulations, all performed under the influence of the solvent and the electrode potential. Full kinetics from first-principles allows the rate-determining step in the CER to be identified and the experimentally observed change in the Tafel slope to be explained. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Contribution to an effective design method for stationary reaction-diffusion patterns.

PubMed

Szalai, István; Horváth, Judit; De Kepper, Patrick

2015-06-01

The British mathematician Alan Turing predicted, in his seminal 1952 publication, that stationary reaction-diffusion patterns could spontaneously develop in reacting chemical or biochemical solutions. The first two clear experimental demonstrations of such a phenomenon were not made before the early 1990s when the design of new chemical oscillatory reactions and appropriate open spatial chemical reactors had been invented. Yet, the number of pattern producing reactions had not grown until 2009 when we developed an operational design method, which takes into account the feeding conditions and other specificities of real open spatial reactors. Since then, on the basis of this method, five additional reactions were shown to produce stationary reaction-diffusion patterns. To gain a clearer view on where our methodical approach on the patterning capacity of a reaction stands, numerical studies in conditions that mimic true open spatial reactors were made. In these numerical experiments, we explored the patterning capacity of Rabai's model for pH driven Landolt type reactions as a function of experimentally attainable parameters that control the main time and length scales. Because of the straightforward reversible binding of protons to carboxylate carrying polymer chains, this class of reaction is at the base of the chemistry leading to most of the stationary reaction-diffusion patterns presently observed. We compare our model predictions with experimental observations and comment on agreements and differences.

A prediction model-based algorithm for computer-assisted database screening of adverse drug reactions in the Netherlands.

PubMed

Scholl, Joep H G; van Hunsel, Florence P A M; Hak, Eelko; van Puijenbroek, Eugène P

2018-02-01

The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model-based approach. A logistic regression-based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug-ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations. A total of 25 026 unique drug-ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734-0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%). A prediction model-based approach can be a useful tool to create priority-based listings for signal detection in databases consisting of spontaneous ADRs. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Development of a reactive burn model based on an explicit viscoplastic pore collapse model

NASA Astrophysics Data System (ADS)

Bouton, E.; Lefrançois, A.; Belmas, R.

2017-01-01

The aim of this study is to develop a reactive burn model based upon a microscopic hot spot model to compute the shock-initiation of pressed TATB high explosives. Such a model has been implemented in a lagrangian hydrodynamic code. In our calculations, 8 pore radii, ranging from 40 nm to 0.63 μm, have been taken into account and the porosity fraction associated to each void radius has been deduced from the Ultra-Small-Angle X-ray Scattering measurements (USAXS) for PBX-9502. The last parameter of our model is a burn rate that depends on three variables. The first two are the reaction progress variable and the lead shock pressure, the last one is the chemical reaction site number produced in the flow and calculated by the microscopic model. This burn rate has been calibrated by fitting pressure, velocity profiles and run distances to detonation. As the computed results are in close agreement with the measured ones, this model is able to perform a wide variety of numerical simulations including single, double shock waves and the desensitization phenomenon.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

The additivity model assumed that field-scale reaction properties in a sediment including surface area, reactive site concentration, and reaction rate can be predicted from field-scale grain-size distribution by linearly adding reaction properties estimated in laboratory for individual grain-size fractions. This study evaluated the additivity model in scaling mass transfer-limited, multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of the rate constants for individual grain-size fractions, which were then used to predict rate-limited U(VI) desorption in the composite sediment. The resultmore » indicated that the additivity model with respect to the rate of U(VI) desorption provided a good prediction of U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel-size fraction (2 to 8 mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

Multiscale Informatics for Low-Temperature Propane Oxidation: Further Complexities in Studies of Complex Reactions

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

Burke, Michael P.; Goldsmith, C. Franklin; Klippenstein, Stephen J.

2015-07-16

We have developed a multi-scale approach (Burke, M. P.; Klippenstein, S. J.; Harding, L. B. Proc. Combust. Inst. 2013, 34, 547–555.) to kinetic model formulation that directly incorporates elementary kinetic theories as a means to provide reliable, physics-based extrapolation to unexplored conditions. Here, we extend and generalize the multi-scale modeling strategy to treat systems of considerable complexity – involving multi-well reactions, potentially missing reactions, non-statistical product branching ratios, and non-Boltzmann (i.e. non-thermal) reactant distributions. The methodology is demonstrated here for a subsystem of low-temperature propane oxidation, as a representative system for low-temperature fuel oxidation. A multi-scale model is assembled andmore » informed by a wide variety of targets that include ab initio calculations of molecular properties, rate constant measurements of isolated reactions, and complex systems measurements. Active model parameters are chosen to accommodate both “parametric” and “structural” uncertainties. Theoretical parameters (e.g. barrier heights) are included as active model parameters to account for parametric uncertainties in the theoretical treatment; experimental parameters (e.g. initial temperatures) are included to account for parametric uncertainties in the physical models of the experiments. RMG software is used to assess potential structural uncertainties due to missing reactions. Additionally, branching ratios among product channels are included as active model parameters to account for structural uncertainties related to difficulties in modeling sequences of multiple chemically activated steps. The approach is demonstrated here for interpreting time-resolved measurements of OH, HO2, n-propyl, i-propyl, propene, oxetane, and methyloxirane from photolysis-initiated low-temperature oxidation of propane at pressures from 4 to 60 Torr and temperatures from 300 to 700 K. In particular, the multi-scale informed model provides a consistent quantitative explanation of both ab initio calculations and time-resolved species measurements. The present results show that interpretations of OH measurements are significantly more complicated than previously thought – in addition to barrier heights for key transition states considered previously, OH profiles also depend on additional theoretical parameters for R + O2 reactions, secondary reactions, QOOH + O2 reactions, and treatment of non-Boltzmann reaction sequences. Extraction of physically rigorous information from those measurements may require more sophisticated treatment of all of those model aspects, as well as additional experimental data under more conditions, to discriminate among possible interpretations and ensure model reliability. Keywords: Optimization, Uncertainty quantification, Chemical mechanism, Low-Temperature Oxidation, Non-Boltzmann« less

Versatile Dual Photoresponsive System for Precise Control of Chemical Reactions.

PubMed

Xu, Can; Bing, Wei; Wang, Faming; Ren, Jinsong; Qu, Xiaogang

2017-08-22

A versatile method for photoregulation of chemical reactions was developed through a combination of near-infrared (NIR) and ultraviolet (UV) light sensitive materials. This regulatory effect was achieved through photoresponsive modulation of reaction temperature and pH values, two prominent factors influencing reaction kinetics. Photothermal nanomaterial graphene oxide (GO) and photobase reagent malachite green carbinol base (MGCB) were selected for temperature and pH regulation, respectively. Using nanocatalyst- and enzyme-mediated chemical reactions as model systems, we demonstrated the feasibility and high efficiency of this method. In addition, a photoresponsive, multifunctional "Band-aid"-like hydrogel platform was presented for programmable wound healing. Overall, this simple, efficient, and reversible system was found to be effective for controlling a wide variety of chemical reactions. Our work may provide a method for remote and sustainable control over chemical reactions for industrial and biomedical applications.

Effect of reactivity loss on apparent reaction order of burning char particles

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

Murphy, Jeffrey J.; Shaddix, Christopher R.

Considerable debate still exists in the char combustion community over the expected and observed reaction orders of carbon reacting with oxygen. In particular, very low values of the reaction order (approaching zero) are commonly observed in char combustion experiments. These observations appear to conflict with porous catalyst theory as first expressed by Thiele, which suggests that the apparent reaction order must be greater than 0.5. In this work, we propose that this conflict may be resolved by considering the decrease in char reactivity with burnout due to ash effects, thermal annealing, or other phenomena. Specifically, the influence of ash dilutionmore » of the available surface area on the apparent reaction order is explored. Equations describing the ash dilution effect are combined with a model for particle burnout based on single-film nth-order Arrhenius char combustion and yield an analytical expression for the effective reaction order. When this expression is applied for experimental conditions reflecting combustion of individual pulverized coal particles in an entrained flow reactor, the apparent reaction order is shown to be lower than the inherent char matrix reaction order, even for negligible extents of char conversion. As char conversion proceeds and approaches completion, the apparent reaction order drops precipitously past zero to negative values. Conversely, the inclusion of the ash dilution model has little effect on the char conversion profile or char particle temperature until significant burnout has occurred. Taken together, these results suggest that the common experimental observation of low apparent reaction orders during char combustion is a consequence of the lack of explicit modeling of the decrease in char reactivity with burnout. (author)« less

A density functional theory study on the carbon chain growth of ethanol formation on Cu-Co (111) and (211) surfaces

NASA Astrophysics Data System (ADS)

Ren, Bohua; Dong, Xiuqin; Yu, Yingzhe; Wen, Guobin; Zhang, Minhua

2017-08-01

Calculations based on the first-principle density functional theory were carried out to study the most controversial reactions in ethanol formation from syngas on Cu-Co surfaces: CO dissociation mechanism and the key reactions of carbon chain growth of ethanol formation (HCO insertion reactions) on four model surfaces (Cu-Co (111) and (211) with Cu-rich or Co-rich surfaces) to investigate the synergy of the Cu and Co components since the complete reaction network of ethanol formation from syngas is a huge computational burden to calculate on four Cu-Co surface models. We investigated adsorption of important species involved in these reactions, activation barrier and reaction energy of H-assisted dissociation mechanism, directly dissociation of CO, and HCO insertion reactions (CHx + HCO → CHxCHO (x = 1-3)) on four Cu-Co surface models. It was found that reactions on Cu-rich (111) and (211) surfaces all have lower activation barrier in H-assisted dissociation and HCO insertion reactions, especially CH + HCO → CHCHO reaction. The PDOS of 4d orbitals of surface Cu and Co atoms of all surfaces were studied. Analysis of d-band center of Cu and Co atoms and the activation barrier data suggested the correlation between electronic property and catalytic performance. Cu-Co bimetallic with Cu-rich surface allows Co to have higher catalytic activity through the interaction of Cu and Co atom. Then it will improve the adsorption of CO and catalytic activity of Co. Thus it is more favorable to the carbon chain growth in ethanol formation. Our study revealed the factors influencing the carbon chain growth in ethanol production and explained the internal mechanism from electronic property aspect.

Impact of Temperature and Non-Gaussian Statistics on Electron Transfer in Donor-Bridge-Acceptor Molecules.

PubMed

Waskasi, Morteza M; Newton, Marshall D; Matyushov, Dmitry V

2017-03-30

A combination of experimental data and theoretical analysis provides evidence of a bell-shaped kinetics of electron transfer in the Arrhenius coordinates ln k vs 1/T. This kinetic law is a temperature analogue of the familiar Marcus bell-shaped dependence based on ln k vs the reaction free energy. These results were obtained for reactions of intramolecular charge shift between the donor and acceptor separated by a rigid spacer studied experimentally by Miller and co-workers. The non-Arrhenius kinetic law is a direct consequence of the solvent reorganization energy and reaction driving force changing approximately as hyperbolic functions with temperature. The reorganization energy decreases and the driving force increases when temperature is increased. The point of equality between them marks the maximum of the activationless reaction rate. Reaching the consistency between the kinetic and thermodynamic experimental data requires the non-Gaussian statistics of the donor-acceptor energy gap described by the Q-model of electron transfer. The theoretical formalism combines the vibrational envelope of quantum vibronic transitions with the Q-model describing the classical component of the Franck-Condon factor and a microscopic solvation model of the solvent reorganization energy and the reaction free energy.

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

Waskasi, Morteza M.; Newton, Marshall D.; Matyushov, Dmitry V.

A combination of experimental data and theoretical analysis provides evidence of a bell-shaped kinetics of electron transfer in the Arrhenius coordinates ln k vs 1/T . This kinetic law is a temperature analog of the familiar Marcus bell-shaped dependence based on ln k vs the reaction free energy. These results were obtained for reactions of intramolecular charge shift between the donor and acceptor separated by a rigid spacer studied experimentally by Miller and co-workers. The non-Arrhenius kinetic law is a direct consequence of the solvent reorganization energy and reaction driving force changing approximately as hyperbolic functions with temperature. The reorganizationmore » energy decreases and the driving force increases when temperature is increased. The point of equality between them marks the maximum of the activationless reaction rate. Reaching the consistency between the kinetic and thermodynamic experimental data requires the non-Gaussian statistics of the donor-acceptor energy gap described by the Q-model of electron transfer. Furthermore, the theoretical formalism combines the vibrational envelope of quantum vibronic transitions with the Q-model describing the classical component of the Franck-Condon factor and a microscopic solvation model of the solvent reorganization energy and the reaction free energy.« less

Modelling of The Atmospheric Chemistry of Organic Nitrates

NASA Astrophysics Data System (ADS)

Winsland, N.

Organic nitrates are linked to the formation of tropospheric ozone and the cycling and transport of nitrogen-containing species in the atmosphere. Few laboratory stud- ies have been carried out on the reactions of organic nitrates. Photolysis quantum yield studies and UV absorption spectra have been carried out for the simple alkyl nitrates and PAN. Studies of PAN and ethyl nitrate with other atmospheric components (the hydroxyl radical - OH - and the chlorine atom - Cl) have been carried out to mea- sure their rates of reaction. However, the products and mechanisms of these reactions are poorly understood. We present here the results of modelling the reactions of the C1-C8 alkyl nitrates and PAN with the hydroxyl radical. These models are based on information from current literature and from photochemical reactor studies carried out at the Environment Institute, EU Joint Research Centre, Ispra, Italy. These studies give us a more detailed understanding of the mechanisms and products of the atmospheric loss of organic nitrates due to reaction with the hydroxyl radical. Preliminary studies show that the major products are aldehydes, ketones, nitro-oxy aldehydes, nitro-oxy ketones, NOx and nitric acid.

Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

NASA Astrophysics Data System (ADS)

Gelß, Patrick; Matera, Sebastian; Schütte, Christof

2016-06-01

In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO2(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.

Development of a global pollution model for CO, CH4, and CH2O

NASA Technical Reports Server (NTRS)

Peters, L. K.

1974-01-01

The current status of a global pollution model for carbon monoxide, methane, and formaldehyde is described. The physico-chemical action is considered of these three pollutants in the troposphere. This geographic restriction is convenient since the tropopause provides a natural boundary across which little transport occurs. The data on sources and sinks for these pollutants is based on available information and assumptions relative to the major man-made and natural contributions. The distributions and concentrations of methane, formaldehyde, and carbon monoxide in the atmosphere are interrelated by the chemical reactions in which they participate. A chemical kinetic model based on the pseudo-steady state approximation for the intermediate species was developed to account for these reactions. The numerical procedure used to mathematically describe the pollution transport is a mass conservative scheme employing an integral flux approach.

Semisupervised Gaussian Process for Automated Enzyme Search.

PubMed

Mellor, Joseph; Grigoras, Ioana; Carbonell, Pablo; Faulon, Jean-Loup

2016-06-17

Synthetic biology is today harnessing the design of novel and greener biosynthesis routes for the production of added-value chemicals and natural products. The design of novel pathways often requires a detailed selection of enzyme sequences to import into the chassis at each of the reaction steps. To address such design requirements in an automated way, we present here a tool for exploring the space of enzymatic reactions. Given a reaction and an enzyme the tool provides a probability estimate that the enzyme catalyzes the reaction. Our tool first considers the similarity of a reaction to known biochemical reactions with respect to signatures around their reaction centers. Signatures are defined based on chemical transformation rules by using extended connectivity fingerprint descriptors. A semisupervised Gaussian process model associated with the similar known reactions then provides the probability estimate. The Gaussian process model uses information about both the reaction and the enzyme in providing the estimate. These estimates were validated experimentally by the application of the Gaussian process model to a newly identified metabolite in Escherichia coli in order to search for the enzymes catalyzing its associated reactions. Furthermore, we show with several pathway design examples how such ability to assign probability estimates to enzymatic reactions provides the potential to assist in bioengineering applications, providing experimental validation to our proposed approach. To the best of our knowledge, the proposed approach is the first application of Gaussian processes dealing with biological sequences and chemicals, the use of a semisupervised Gaussian process framework is also novel in the context of machine learning applied to bioinformatics. However, the ability of an enzyme to catalyze a reaction depends on the affinity between the substrates of the reaction and the enzyme. This affinity is generally quantified by the Michaelis constant KM. Therefore, we also demonstrate using Gaussian process regression to predict KM given a substrate-enzyme pair.

Reaction-diffusion pattern in shoot apical meristem of plants.

PubMed

Fujita, Hironori; Toyokura, Koichi; Okada, Kiyotaka; Kawaguchi, Masayoshi

2011-03-29

A fundamental question in developmental biology is how spatial patterns are self-organized from homogeneous structures. In 1952, Turing proposed the reaction-diffusion model in order to explain this issue. Experimental evidence of reaction-diffusion patterns in living organisms was first provided by the pigmentation pattern on the skin of fishes in 1995. However, whether or not this mechanism plays an essential role in developmental events of living organisms remains elusive. Here we show that a reaction-diffusion model can successfully explain the shoot apical meristem (SAM) development of plants. SAM of plants resides in the top of each shoot and consists of a central zone (CZ) and a surrounding peripheral zone (PZ). SAM contains stem cells and continuously produces new organs throughout the lifespan. Molecular genetic studies using Arabidopsis thaliana revealed that the formation and maintenance of the SAM are essentially regulated by the feedback interaction between WUSHCEL (WUS) and CLAVATA (CLV). We developed a mathematical model of the SAM based on a reaction-diffusion dynamics of the WUS-CLV interaction, incorporating cell division and the spatial restriction of the dynamics. Our model explains the various SAM patterns observed in plants, for example, homeostatic control of SAM size in the wild type, enlarged or fasciated SAM in clv mutants, and initiation of ectopic secondary meristems from an initial flattened SAM in wus mutant. In addition, the model is supported by comparing its prediction with the expression pattern of WUS in the wus mutant. Furthermore, the model can account for many experimental results including reorganization processes caused by the CZ ablation and by incision through the meristem center. We thus conclude that the reaction-diffusion dynamics is probably indispensable for the SAM development of plants.

Reaction-Diffusion Pattern in Shoot Apical Meristem of Plants

PubMed Central

Fujita, Hironori; Toyokura, Koichi; Okada, Kiyotaka; Kawaguchi, Masayoshi

2011-01-01

A fundamental question in developmental biology is how spatial patterns are self-organized from homogeneous structures. In 1952, Turing proposed the reaction-diffusion model in order to explain this issue. Experimental evidence of reaction-diffusion patterns in living organisms was first provided by the pigmentation pattern on the skin of fishes in 1995. However, whether or not this mechanism plays an essential role in developmental events of living organisms remains elusive. Here we show that a reaction-diffusion model can successfully explain the shoot apical meristem (SAM) development of plants. SAM of plants resides in the top of each shoot and consists of a central zone (CZ) and a surrounding peripheral zone (PZ). SAM contains stem cells and continuously produces new organs throughout the lifespan. Molecular genetic studies using Arabidopsis thaliana revealed that the formation and maintenance of the SAM are essentially regulated by the feedback interaction between WUSHCEL (WUS) and CLAVATA (CLV). We developed a mathematical model of the SAM based on a reaction-diffusion dynamics of the WUS-CLV interaction, incorporating cell division and the spatial restriction of the dynamics. Our model explains the various SAM patterns observed in plants, for example, homeostatic control of SAM size in the wild type, enlarged or fasciated SAM in clv mutants, and initiation of ectopic secondary meristems from an initial flattened SAM in wus mutant. In addition, the model is supported by comparing its prediction with the expression pattern of WUS in the wus mutant. Furthermore, the model can account for many experimental results including reorganization processes caused by the CZ ablation and by incision through the meristem center. We thus conclude that the reaction-diffusion dynamics is probably indispensable for the SAM development of plants. PMID:21479227

An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data. PMID:23593445

Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column: Original Research Article: Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture

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

Wang, Chao; Xu, Zhijie; Lai, Canhai

A hierarchical model calibration and validation is proposed for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO2) capture is simulated and simulation results are compared to the parallel bench-scale experimental data. Two unit problems with increasing level of complexity are proposed to breakdown the complex physical/chemical processes of solvent-based CO2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e. the CO2 mass transfer across a falling ethanolaminemore » (MEA) film in absence of chemical reaction. This problem is investigated both experimentally and numerically using nitrous oxide (N2O) as a surrogate for CO2. To capture the motion of gas-liquid interface, a volume of fluid method is employed together with a one-fluid formulation to compute the mass transfer between the two phases. Bench-scale parallel experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration. Two important transport parameters, e.g. Henry’s constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as the input for the second unit problem to address the chemical adsorption of CO2 across the MEA falling film, where both mass transfer and chemical reaction are involved.« less

Sample distribution in peak mode isotachophoresis

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

Rubin, Shimon; Schwartz, Ortal; Bercovici, Moran, E-mail: mberco@technion.ac.il

We present an analytical study of peak mode isotachophoresis (ITP), and provide closed form solutions for sample distribution and electric field, as well as for leading-, trailing-, and counter-ion concentration profiles. Importantly, the solution we present is valid not only for the case of fully ionized species, but also for systems of weak electrolytes which better represent real buffer systems and for multivalent analytes such as proteins and DNA. The model reveals two major scales which govern the electric field and buffer distributions, and an additional length scale governing analyte distribution. Using well-controlled experiments, and numerical simulations, we verify andmore » validate the model and highlight its key merits as well as its limitations. We demonstrate the use of the model for determining the peak concentration of focused sample based on known buffer and analyte properties, and show it differs significantly from commonly used approximations based on the interface width alone. We further apply our model for studying reactions between multiple species having different effective mobilities yet co-focused at a single ITP interface. We find a closed form expression for an effective-on rate which depends on reactants distributions, and derive the conditions for optimizing such reactions. Interestingly, the model reveals that maximum reaction rate is not necessarily obtained when the concentration profiles of the reacting species perfectly overlap. In addition to the exact solutions, we derive throughout several closed form engineering approximations which are based on elementary functions and are simple to implement, yet maintain the interplay between the important scales. Both the exact and approximate solutions provide insight into sample focusing and can be used to design and optimize ITP-based assays.« less

[Kinetics modeling and reaction mechanism of ferrate(VI) oxidation of triclosan].

PubMed

Yang, Bin; Ying, Guang-Guo; Zhao, Jian-Liang

2011-09-01

Triclosan (TCS) is a broad-spectrum antibacterial agent widely used in many personal care products. We investigated oxidation of TCS by aqueous ferrate Fe(VI) to determine reaction kinetics, interpreted the reaction mechanism by a linear free-energy relationship, and evaluated the degradation efficiency. Second-order reaction kinetics was used to model Fe (VI) oxidation of TCS, with the apparent second-order rate constant (k(app)) being 531.9 L x (mol x s)(-1) at pH 8.5 and (24 +/- 1) degrees C. The half life (t1/2) is 25.8 s for an Fe( VI) concentration of 10 mg x L(-1). The rate constants of the reaction decrease with increasing pH values. These pH-dependent variations in k(app) could be distributed by considering species-specific reactions between Fe(VI) species and acid-base species of an ionizable TCS. Species-specific second-order reaction rate constants, k, were determined for reaction of HFeO4(-) with each of TCS's acid-base species. The value of k determined for neutral TCS was (4.1 +/- 3.5) x 10(2) L x (mol x s)(-1), while that measured for anionic TCS was (1.8 +/- 0.1) x 10(4) L x (mol x s)(-1). The reaction between HFeO4(-) and the dissociated TCS controls the overall reaction. A linear free-energy relationship illustrated the electrophilic oxidation mechanism. Fe (VI) reacts initially with TCS by electrophilic attack at the latter's phenol moiety. At a n[Fe(VI)]: n(TCS) > 7: 1, complete removal of TCS was achieved. And lower concentration of the humic acid could enhance the k(app) of Fe( VI) with TCS. In conclusion, Fe(VI) oxidation technology appears to be a promising tool for applications of WWTPs effluents and other decontamination processes.

Schiff and pseudo-Schiff reagents: the reactions and reagents of Hugo Schiff, including a classification of various kinds of histochemical reagents used to detect aldehydes.

PubMed

Dapson, R W

2016-11-01

During the 1860's, Hugo Schiff studied many reactions between amines and aldehydes, some of which have been used in histochemistry, at times without credit to Schiff. Much controversy has surrounded the chemical structures and reaction mechanisms of the compounds involved, but modern analytical techniques have clarified the picture. I review these reactions here. I used molecular modeling software to investigate dyes that contain primary amines representing eight chemical families. All dyes were known to perform satisfactorily for detecting aldehydes in tissue sections. The models verified the correct chemical structures at various points in their reactions and also determined how decolorization occurred in those with "leuco" forms. Decolorization in the presence of sulfurous acid can occur by either adduction or reduction depending on the dye. The final condensation product with aldehyde was determined to be either a C-sulfonic acid adduct on the carbonyl carbon atom or an aminal at the same atom. Based on the various outcomes, I have placed the dyes and their reactions into five categories. Because Hugo Schiff studied the reactions between aldehydes and amines with and without various acids or alcohol, it is only proper to call each of them Schiff reactions that used various types of Schiff reagents.

Theoretical study of the kinetics of chlorine atom abstraction from chloromethanes by atomic chlorine.

PubMed

Brudnik, Katarzyna; Twarda, Maria; Sarzyński, Dariusz; Jodkowski, Jerzy T

2013-10-01

Ab initio calculations at the G3 level were used in a theoretical description of the kinetics and mechanism of the chlorine abstraction reactions from mono-, di-, tri- and tetra-chloromethane by chlorine atoms. The calculated profiles of the potential energy surface of the reaction systems show that the mechanism of the studied reactions is complex and the Cl-abstraction proceeds via the formation of intermediate complexes. The multi-step reaction mechanism consists of two elementary steps in the case of CCl4 + Cl, and three for the other reactions. Rate constants were calculated using the theoretical method based on the RRKM theory and the simplified version of the statistical adiabatic channel model. The temperature dependencies of the calculated rate constants can be expressed, in temperature range of 200-3,000 K as [Formula: see text]. The rate constants for the reverse reactions CH3/CH2Cl/CHCl2/CCl3 + Cl2 were calculated via the equilibrium constants derived theoretically. The kinetic equations [Formula: see text] allow a very good description of the reaction kinetics. The derived expressions are a substantial supplement to the kinetic data necessary to describe and model the complex gas-phase reactions of importance in combustion and atmospheric chemistry.

Density functional tight-binding and infrequent metadynamics can capture entropic effects in intramolecular hydrogen transfer reactions

NASA Astrophysics Data System (ADS)

Oliveira, Luiz F. L.; Fu, Christopher D.; Pfaendtner, Jim

2018-04-01

Infrequent metadynamics uses biased simulations to estimate the unbiased kinetics of a system, facilitating the calculation of rates and barriers. Here the method is applied to study intramolecular hydrogen transfer reactions involving peroxy radicals, a class of reactions that is challenging to model due to the entropic contributions of the formation of ring structures in the transition state. Using the self-consistent charge density-functional based tight-binding (DFTB) method, we applied infrequent metadynamics to the study of four intramolecular H-transfer reactions, demonstrating that the method can qualitatively reproduce these high entropic contributions, as observed in experiments and those predicted by transition state theory modeled by higher levels of theory. We also show that infrequent metadynamics and DFTB are successful in describing the relationship between transition state ring size and kinetic coefficients (e.g., activation energies and the pre-exponential factors).

Effect of motion frequency spectrum on subjective comfort response. [modeling passenger reactions to commercial aircraft flights

NASA Technical Reports Server (NTRS)

Jacobson, I. D.; Schoultz, M. B.; Blake, J. C.

1973-01-01

In order to model passenger reaction to present and future aircraft environments, it is necessary to obtain data in several ways. First, of course, is the gathering of environmental and passenger reaction data on commercial aircraft flights. In addition, detailed analyses of particular aspects of human reaction to the environment are best studied in a controllable experimental situation. Thus the use of simulators, both flight and ground based, is suggested. It is shown that there is a reasonably high probability that the low frequency end of the spectrum will not be necessary for simulation purposes. That is, the fidelity of any simulation which omits the very low frequency content will not yield results which differ significantly from the real environment. In addition, there does not appear to be significant differences between the responses obtained in the airborne simulator environment versus those obtained on commercial flights.

Production of heavy neutron-rich nuclei in transfer reactions within the dinuclear system model

NASA Astrophysics Data System (ADS)

Zhu, Long; Feng, Zhao-Qing; Zhang, Feng-Shou

2015-08-01

The dynamics of nucleon transfer processes in heavy-ion collisions is investigated within the dinuclear system model. The production cross sections of nuclei in the reactions 136Xe+208Pb and 238U+248Cm are calculated, and the calculations are in good agreement with the experimental data. The transfer cross sections for the 58Ni+208Pb reaction are calculated and compared with the experimental data. We predict the production cross sections of neutron-rich nuclei 165-168 Eu, 169-173 Tb, 173-178 Ho, and 181-185Yb based on the reaction 176Yb+238U. It can be seen that the production cross sections of the neutron-rich nuclei 165Eu, 169Tb, 173Ho, and 181Yb are 2.84 μb, 6.90 μb, 46.24 μb, and 53.61 μb, respectively, which could be synthesized in experiment.

pH Wave-Front Propagation in the Urea-Urease Reaction

PubMed Central

Wrobel, Magdalena M.; Bánsági, Tamás; Scott, Stephen K.; Taylor, Annette F.; Bounds, Chris O.; Carranza, Arturo; Pojman, John A.

2012-01-01

The urease-catalyzed hydrolysis of urea displays feedback that results in a switch from acid (pH ∼3) to base (pH ∼9) after a controllable period of time (from 10 to >5000 s). Here we show that the spatially distributed reaction can support pH wave fronts propagating with a speed of the order of 0.1−1 mm min−1. The experimental results were reproduced qualitatively in reaction-diffusion simulations including a Michaelis-Menten expression for the urease reaction with a bell-shaped rate-pH dependence. However, this model fails to predict that at lower enzyme concentrations, the unstirred reaction does not always support fronts when the well-stirred reaction still rapidly switches to high pH. PMID:22947878

Modeling CH 4 and CO 2 cycling using porewater stable isotopes in a thermokarst bog in Interior Alaska: results from three conceptual reaction networks

DOE PAGES

Neumann, Rebecca B.; Blazewicz, Steven J.; Conaway, Christopher H.; ...

2015-12-16

Quantifying rates of microbial carbon transformation in peatlands is essential for gaining mechanistic understanding of the factors that influence methane emissions from these systems, and for predicting how emissions will respond to climate change and other disturbances. In this study, we used porewater stable isotopes collected from both the edge and center of a thermokarst bog in Interior Alaska to estimate in situ microbial reaction rates. We expected that near the edge of the thaw feature, actively thawing permafrost and greater abundance of sedges would increase carbon, oxygen and nutrient availability, enabling faster microbial rates relative to the center ofmore » the thaw feature. We developed three different conceptual reaction networks that explained the temporal change in porewater CO2, CH4, δ13C-CO2 and δ13C-CH4. All three reaction-network models included methane production, methane oxidation and CO2 production, and two of the models included homoacetogenesis — a reaction not previously included in isotope-based porewater models. All three models fit the data equally well, but rates resulting from the models differed. Most notably, inclusion of homoacetogenesis altered the modeled pathways of methane production when the reaction was directly coupled to methanogenesis, and it decreased gross methane production rates by up to a factor of five when it remained decoupled from methanogenesis. The ability of all three conceptual reaction networks to successfully match the measured data indicate that this technique for estimating in-situ reaction rates requires other data and information from the site to confirm the considered set of microbial reactions. Despite these differences, all models indicated that, as expected, rates were greater at the edge than in the center of the thaw bog, that rates at the edge increased more during the growing season than did rates in the center, and that the ratio of acetoclastic to hydrogenotrophic methanogenesis was greater at the edge than in the center. In both locations, modeled rates (excluding methane oxidation) increased with depth. A puzzling outcome from the effort was that none of the models could fit the porewater dataset without generating “fugitive” carbon (i.e., methane or acetate generated by the models but not detected at the field site), indicating that either our conceptualization of the reactions occurring at the site remains incomplete or our site measurements are missing important carbon transformations and/or carbon fluxes. This model–data discrepancy will motivate and inform future research efforts focused on improving our understanding of carbon cycling in permafrost wetlands.« less

Loss Process for the C2H5 Radical in the Atmospheres of Jupiter and Saturn: First Direct, Absolute Measurement of the Rate Constant for the Reaction H + C2H5 at Low Pressure and Temperature

NASA Astrophysics Data System (ADS)

Stief, L. J.; Pimentel, A. S.; Payne, W. A.; Nesbitt, F. L.; Cody, R. J.

2003-05-01

Photochemical models of the atmospheres of Jupiter and Saturn predict the reaction H + C2H5 to be the most important loss process for C2H5 in these atmospheres. In addition, the reaction channel H + C2H5 -> 2 CH3 is a significant source of the methyl radical. There are only two relatively modern studies of the H + C2H5 reaction, both of which depend on extensive modeling involving eight elementary reactions. The motivation for the present study is the lack of direct, absolute measurements of the rate constant for the H + C2H5 reaction at low pressures and temperatures appropriate for outer planet models. In the present experiments the reactants H and C2H5 are rapidly and simultaneously generated by reaction of F with appropriate mixtures of H2 and C2H6. Using the technique of discharge-flow with collision-free sampling to a mass spectrometer, we monitor the decay of C2H5 in excess H. In contrast to previous studies of this reaction, the primary H + C2H5 reaction is isolated and the radical decays only by reaction with H and by loss at the wall. Secondary reactions such as the self-reaction of C2H5 are negligible. At P = 1 Torr He we measure k (298K) = 1.13 x 10-10 cm3 molecule-1 s-1 and k (202K) = 1.18 x 10-10 cm3 molecule-1 s-1. Experiments at T = 155 K are in progress. The reaction is temperature independent as expected based on studies of other atom-radical reactions. Our result at T = 298 K lies between those of the two relatively modern but complex studies of this reaction. The present total rate constant data and planned product yield studies at low pressures and temperatures will then be available for use in future photochemical models of the atmospheres of the outer planets. The Planetary Atmospheres Program of NASA Headquarters is supporting this research.

Class and Home Problems: Modeling of an Industrial Anaerobic Digester: A Case Study for Undergraduate Students

ERIC Educational Resources Information Center

Durruty, Ignacio; Ayude, María A.

2014-01-01

The case study discussed in this work is used at the chemical reaction engineering course, offered in fifth-year of the chemical engineering undergraduate program at National University of Mar del Plata (UNMdP). A serial-parallel reaction system based on the anaerobic degradation of particulate-containing potato processing wastewater is presented.…

Computational study on UV curing characteristics in nanoimprint lithography: Stochastic simulation

NASA Astrophysics Data System (ADS)

Koyama, Masanori; Shirai, Masamitsu; Kawata, Hiroaki; Hirai, Yoshihiko; Yasuda, Masaaki

2017-06-01

A computational simulation model of UV curing in nanoimprint lithography based on a simplified stochastic approach is proposed. The activated unit reacts with a randomly selected monomer within a critical reaction radius. Cluster units are chained to each other. Then, another monomer is activated and the next chain reaction occurs. This process is repeated until a virgin monomer disappears within the reaction radius or until the activated monomers react with each other. The simulation model well describes the basic UV curing characteristics, such as the molecular weight distributions of the reacted monomers and the effect of the initiator concentration on the conversion ratio. The effects of film thickness on UV curing characteristics are also studied by the simulation.

A minimally-resolved immersed boundary model for reaction-diffusion problems

NASA Astrophysics Data System (ADS)

Pal Singh Bhalla, Amneet; Griffith, Boyce E.; Patankar, Neelesh A.; Donev, Aleksandar

2013-12-01

We develop an immersed boundary approach to modeling reaction-diffusion processes in dispersions of reactive spherical particles, from the diffusion-limited to the reaction-limited setting. We represent each reactive particle with a minimally-resolved "blob" using many fewer degrees of freedom per particle than standard discretization approaches. More complicated or more highly resolved particle shapes can be built out of a collection of reactive blobs. We demonstrate numerically that the blob model can provide an accurate representation at low to moderate packing densities of the reactive particles, at a cost not much larger than solving a Poisson equation in the same domain. Unlike multipole expansion methods, our method does not require analytically computed Green's functions, but rather, computes regularized discrete Green's functions on the fly by using a standard grid-based discretization of the Poisson equation. This allows for great flexibility in implementing different boundary conditions, coupling to fluid flow or thermal transport, and the inclusion of other effects such as temporal evolution and even nonlinearities. We develop multigrid-based preconditioners for solving the linear systems that arise when using implicit temporal discretizations or studying steady states. In the diffusion-limited case the resulting linear system is a saddle-point problem, the efficient solution of which remains a challenge for suspensions of many particles. We validate our method by comparing to published results on reaction-diffusion in ordered and disordered suspensions of reactive spheres.

Astrophysical reaction rates from a symmetry-informed first-principles perspective

NASA Astrophysics Data System (ADS)

Dreyfuss, Alison; Launey, Kristina; Baker, Robert; Draayer, Jerry; Dytrych, Tomas

2017-01-01

With a view toward a new unified formalism for studying bound and continuum states in nuclei, to understand stellar nucleosynthesis from a fully ab initio perspective, we studied the nature of surface α-clustering in 20Ne by considering the overlap of symplectic states with cluster-like states. We compute the spectroscopic amplitudes and factors, α-decay width, and absolute resonance strength - characterizing major contributions to the astrophysical reaction rate through a low-lying 1- resonant state in 20Ne. As a next step, we consider a fully microscopic treatment for the n+4 He system, based on the successful first-principles No-Core Shell Model/Resonating Group Method (NCSM/RGM) for light nuclei, but with the capability to reach intermediate-mass nuclei. The new model takes advantage of the symmetry-based concept central to the Symmetry-Adapted No-Core Shell Model (SA-NCSM) to reduce computational complexity in physically-informed and methodical way, with sights toward first-principles calculations of rates for important astrophysical reactions, such as the 23 Al(p , γ) 24 Si reaction, believed to have a strong influence on X-ray burst light curves. Supported by the U.S. NSF (OCI-0904874, ACI -1516338) and the U.S. DOE (DE-SC0005248), and benefitted from computing resources provided by Blue Waters and the LSU Center for Computation & Technology.

Reaction of Shocked but Undetonated HMX-Based Explosive

NASA Astrophysics Data System (ADS)

Taylor, P.; Salisbury, D. A.; Markland, L. S.; Winter, R. E.; Andrew, M. I.

2002-07-01

Cylindrical samples of the pressed plastic bonded HMX based explosive EDC37, backed by metal discs, were shocked through a stainless steel attenuator by an explosive donor. Reaction of the EDC37 sample was diagnosed with embedded PVDF pressure gauges and a distance to detonation for the geometry was determined. Sample length was then reduced to less than the observed detonation distance and laser interferometry was used to record the free surface velocity of the metal backing disc. The results provide data on the metal driving energy liberated by explosive which is shocked and reacting but not detonated. The results are compared with 2-D Eulerian calculations incorporating a 3-term ignition and growth reactive burn model with desensitisation. It is found that a parameter set for the reaction model which replicates the PVDF pressure profiles before reflection also gives good agreement to the metal disc velocity history at early times. The results show that an appreciable fraction of the metal driving potential of an explosive can be released without detonation being established.

Synthesis of biodiesel from a model waste oil feedstock using a carbon-based solid acid catalyst: reaction and separation.

PubMed

Shu, Qing; Nawaz, Zeeshan; Gao, Jixian; Liao, Yuhui; Zhang, Qiang; Wang, Dezheng; Wang, Jinfu

2010-07-01

A solid acid catalyst that can keep high activity and stability is necessary when low cost feedstocks are utilized for biodiesel synthesis because the reaction medium contains a large amount of water. Three solid acid catalysts were prepared by the sulfonation of carbonized vegetable oil asphalt and petroleum asphalt. The structure of these catalysts was characterized by a variety of techniques. A new process that used the coupling of the reaction and separation was employed, which greatly improved the conversion of cottonseed oil (triglyceride) and free fatty acids (FFA) when a model waste oil feedstock was used. The vegetable oil asphalt-based catalyst showed the highest catalytic activity. This was due to the high density and stability of its acid sites, its loose irregular network, its hydrophobicity that prevented the hydration of -OH species, and large pores that provided more acid sites for the reactants. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

EPA Science Inventory

An explicit dynamic water-quality modeling algorithm is developed for tracking dissolved substances in water-distribution networks. The algorithm is based on a mass-balance relation within pipes that considers both advective transport and reaction kinetics. Complete mixing of m...

The role of correlations in uncertainty quantification of transportation relevant fuel models

DOE PAGES

Fridlyand, Aleksandr; Johnson, Matthew S.; Goldsborough, S. Scott; ...

2017-02-03

Large reaction mechanisms are often used to describe the combustion behavior of transportation-relevant fuels like gasoline, where these are typically represented by surrogate blends, e.g., n-heptane/iso-octane/toluene. We describe efforts to quantify the uncertainty in the predictions of such mechanisms at realistic engine conditions, seeking to better understand the robustness of the model as well as the important reaction pathways and their impacts on combustion behavior. In this work, we examine the importance of taking into account correlations among reactions that utilize the same rate rules and those with multiple product channels on forward propagation of uncertainty by Monte Carlo simulations.more » Automated means are developed to generate the uncertainty factor assignment for a detailed chemical kinetic mechanism, by first uniquely identifying each reacting species, then sorting each of the reactions based on the rate rule utilized. Simulation results reveal that in the low temperature combustion regime for iso-octane, the majority of the uncertainty in the model predictions can be attributed to low temperature reactions of the fuel sub-mechanism. The foundational, or small-molecule chemistry (C 0-C 4) only contributes significantly to uncertainties in the predictions at the highest temperatures (Tc=900 K). Accounting for correlations between important reactions is shown to produce non-negligible differences in the estimates of uncertainty. Including correlations among reactions that use the same rate rules increases uncertainty in the model predictions, while accounting for correlations among reactions with multiple branches decreases uncertainty in some cases. Significant non-linear response is observed in the model predictions depending on how the probability distributions of the uncertain rate constants are defined.Finally, we concluded that care must be exercised in defining these probability distributions in order to reduce bias, and physically unrealistic estimates in the forward propagation of uncertainty for a range of UQ activities.« less

A multiscale, model-based analysis of the multi-tissue interplay underlying blood glucose regulation in type I diabetes.

PubMed

Wadehn, Federico; Schaller, Stephan; Eissing, Thomas; Krauss, Markus; Kupfer, Lars

2016-08-01

A multiscale model for blood glucose regulation in diabetes type I patients is constructed by integrating detailed metabolic network models for fat, liver and muscle cells into a whole body physiologically-based pharmacokinetic/pharmacodynamic (pBPK/PD) model. The blood glucose regulation PBPK/PD model simulates the distribution and metabolization of glucose, insulin and glucagon on an organ and whole body level. The genome-scale metabolic networks in contrast describe intracellular reactions. The developed multiscale model is fitted to insulin, glucagon and glucose measurements of a 48h clinical trial featuring 6 subjects and is subsequently used to simulate (in silico) the influence of geneknockouts and drug-induced enzyme inhibitions on whole body blood glucose levels. Simulations of diabetes associated gene knockouts and impaired cellular glucose metabolism, resulted in elevated whole body blood-glucose levels, but also in a metabolic shift within the cell's reaction network. Such multiscale models have the potential to be employed in the exploration of novel drug-targets or to be integrated into control algorithms for artificial pancreas systems.

First-Principles Approach to Model Electrochemical Reactions: Understanding the Fundamental Mechanisms behind Mg Corrosion

NASA Astrophysics Data System (ADS)

Surendralal, Sudarsan; Todorova, Mira; Finnis, Michael W.; Neugebauer, Jörg

2018-06-01

Combining concepts of semiconductor physics and corrosion science, we develop a novel approach that allows us to perform ab initio calculations under controlled potentiostat conditions for electrochemical systems. The proposed approach can be straightforwardly applied in standard density functional theory codes. To demonstrate the performance and the opportunities opened by this approach, we study the chemical reactions that take place during initial corrosion at the water-Mg interface under anodic polarization. Based on this insight, we derive an atomistic model that explains the origin of the anodic hydrogen evolution.

Biodegradation of coal-related model compounds. [C. versicolor

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

Campbell, J.A.; Stewart, D.L.; McCulloch, M.

1988-01-01

The details of the specific reactions of lignin biodegradation, and the biochemistry involved, have been primarily based on the use of low molecular weight compounds representing specific substructures rather than the complex, polymeric lignin material. The authors have studied the reactions of model compounds having coal-related functionalities (ester linkages, ether linkages, PAH) with the intact organisms, cell-free filtrate, and cell-free enzyme of C. versicolor to better understand the process of biosolubilization. Many of the degradation products have been identified by gas chromatography/mass spectrometry (GC/MS). Results are discussed.

Intra-particle migration of mercury in granular polysulfide-rubber-coated activated carbon (PSR-AC)

PubMed Central

Kim, Eun-Ah; Masue-Slowey, Yoko; Fendorf, Scott; Luthy, Richard G.

2011-01-01

The depth profile of mercuric ion after the reaction with polysulfide-rubber-coated activated carbon (PSR-AC) was investigated using micro-x-ray fluorescence (μ-XRF) imaging techniques and mathematical modeling. The μ-XRF results revealed that mercury was concentrated at 0~100 μm from the exterior of the particle after three months of treatment with PSR-AC in 10 ppm HgCl2 aqueous solution. The μ-X-ray absorption near edge spectroscopic (μ-XANES) analyses indicated HgS as a major mercury species, and suggested that the intra-particle mercury transport involved a chemical reaction with PSR polymer. An intra-particle mass transfer model was developed based on either a Langmuir sorption isotherm with liquid phase diffusion (Langmuir model) or a kinetic sorption with surface diffusion (kinetic sorption model). The Langmuir model predicted the general trend of mercury diffusion, although at a slower rate than observed from the μ-XRF map. A kinetic sorption model suggested faster mercury transport, which overestimated the movement of mercuric ions through an exchange reaction between the fast and slow reaction sites. Both μ-XRF and mathematical modeling results suggest mercury removal occurs not only at the outer surface of the PSR-AC particle but also at some interior regions due to a large PSR surface area within an AC particle. PMID:22133913

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

Development and test of different methods to improve the description and NO{sub x} emissions in staged combustion

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

Brink, A.; Kilpinen, P.; Hupa, M.

1996-01-01

Two methods to improve the modeling of NO{sub x} emissions in numerical flow simulation of combustion are investigated. The models used are a reduced mechanism for nitrogen chemistry in methane combustion and a new model based on regression analysis of perfectly stirred reactor simulations using detailed comprehensive reaction kinetics. The applicability of the methods to numerical flow simulation of practical furnaces, especially in the near burner region, is tested against experimental data from a pulverized coal fired single burner furnace. The results are also compared to those obtained using a commonly used description for the overall reaction rate of NO.

[Preliminary study on evaluation system of mental workers strain based on primary and middle school teachers].

PubMed

Lian, Yulong; Liu, Jiwen; Zhang, Chen; Yuan, Fang

2010-09-01

To use primary and middle schools teacher as samples to preliminarily build the mental work stress effect evaluation system, providing the methological platform for the research on the stress effect mechanism and mental workers interference measures. 851 teachers in primary and middle schools were selected with randomly stratified cluster methods. Use ISTA 6.0 and Life Events Evaluation Table to measure the stress factors, and use Work Tension Reaction Questionnaire, Symptom Self-Evaluation Table Questionnaire, and General Happiness Sensing Table to measure psychological stress reaction, blood sugar and blood fat, blood cortical, ACTH, nerve behavior function, for measuring physiological stress reaction. The Comprehensive Working Ability Index Table to measure working ability. And then use the mathematical model to build the mental workers stress effect evaluation system. And apply the simple random sampling method to select 400 environmental protection workers to perform cross effect validation. The model fits relatively well (RMSEA = 0.100, GFI = 0.93, NNFI = 1.00, CFI = 1.00) and conforms with the theory, reflecting the loads of the indice, such as, working stress reaction, psychological stress reaction, physiological stress reaction and working ability, are relatively high. At the same time, the stress reaction of those 4 dimensions can fit the 2-grade factor (stress effect) very well. The physiological stress reaction is negatively correlated (P < 0.05) with the working stress reaction, psychological stress reaction, working ability decrease, while is positively correlated (P < 0.05) with the working stress, psychological stress reaction, physiological stress reaction and working ability decrease. The social support is the protection factor for working stress, psychological stress reaction, physiological stress reaction and working ability decrease (gamma(s) are -0.55, -0.77, 0.73, -0.79, respectively, P < 0.05). While working stress factors, social life stress factors and dangerous individual characters are the risk factors (P < 0.05) for working stress, psychological stress reaction, physiological stress reaction increase and the working ability decrease. The utilization of the environment protection workers further validates this model. It conforms with the theory to evaluate the mental workers stress effects from the 4 dimensions, working stress, psychological stress reaction, physiological stress reaction, and working ability. And these 4 dimensions influence each other, and also are mutually different. The working and social life stress factors influence the stress effects with certain degrees. This evaluation model can tentatively be the methodological basis for the mental workers occupational stress evaluation.

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Baudin, Catherine; Iwasaki, Yumi; Nayak, Pandurang; Tanaka, Kazuo

1990-01-01

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

Astrophysical S-factor for destructive reactions of lithium-7 in big bang nucleosynthesis

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

Komatsubara, Tetsuro; Kwon, YoungKwan; Moon, JunYoung

One of the most prominent success with the Big Bang models is the precise reproduction of mass abundance ratio for {sup 4}He. In spite of the success, abundances of lithium isotopes are still inconsistent between observations and their calculated results, which is known as lithium abundance problem. Since the calculations were based on the experimental reaction data together with theoretical estimations, more precise experimental measurements may improve the knowledge of the Big Bang nucleosynthesis. As one of the destruction process of lithium-7, we have performed measurements for the reaction cross sections of the {sup 7}L({sup 3}He,p){sup 9}Be reaction.

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Neuman systems model-based research: an integrative review project.

PubMed

Fawcett, J; Giangrande, S K

2001-07-01

The project integrated Neuman systems model-based research literature. Two hundred published studies were located. This article is limited to the 59 full journal articles and 3 book chapters identified. A total of 37% focused on prevention interventions; 21% on perception of stressors; and 10% on stressor reactions. Only 50% of the reports explicitly linked the model with the study variables, and 61% did not include conclusions regarding model utility or credibility. No programs of research were identified. Academic courses and continuing education workshops are needed to help researchers design programs of Neuman systems model-based research and better explicate linkages between the model and the research.

Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads

PubMed Central

Reynolds, Christopher R; Muggleton, Stephen H; Sternberg, Michael J E

2015-01-01

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×1012 potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs. PMID:26583052

A KDE-Based Random Walk Method for Modeling Reactive Transport With Complex Kinetics in Porous Media

NASA Astrophysics Data System (ADS)

Sole-Mari, Guillem; Fernà ndez-Garcia, Daniel; Rodríguez-Escales, Paula; Sanchez-Vila, Xavier

2017-11-01

In recent years, a large body of the literature has been devoted to study reactive transport of solutes in porous media based on pure Lagrangian formulations. Such approaches have also been extended to accommodate second-order bimolecular reactions, in which the reaction rate is proportional to the concentrations of the reactants. Rather, in some cases, chemical reactions involving two reactants follow more complicated rate laws. Some examples are (1) reaction rate laws written in terms of powers of concentrations, (2) redox reactions incorporating a limiting term (e.g., Michaelis-Menten), or (3) any reaction where the activity coefficients vary with the concentration of the reactants, just to name a few. We provide a methodology to account for complex kinetic bimolecular reactions in a fully Lagrangian framework where each particle represents a fraction of the total mass of a specific solute. The method, built as an extension to the second-order case, is based on the concept of optimal Kernel Density Estimator, which allows the concentrations to be written in terms of particle locations, hence transferring the concept of reaction rate to that of particle location distribution. By doing so, we can update the probability of particles reacting without the need to fully reconstruct the concentration maps. The performance and convergence of the method is tested for several illustrative examples that simulate the Advection-Dispersion-Reaction Equation in a 1-D homogeneous column. Finally, a 2-D application example is presented evaluating the need of fully describing non-bilinear chemical kinetics in a randomly heterogeneous porous medium.

Electrochemical models for the radical annihilation reactions in organic light-emitting diodes

NASA Astrophysics Data System (ADS)

Armstrong, Neal R.; Anderson, Jeffrey D.; Lee, Paul A.; McDonald, Erin; Wightman, R. M.; Hall, Hank K.; Hopkins, Tracy; Padias, Anne; Thayumanavan, Sankaran; Barlow, Stephen; Marder, Seth R.

1998-12-01

Bilayer organic light emitting diodes (OLEDs), based upon vacuum deposited molecules, or single layer OLEDs, based upon spin-cast polymeric materials, doped with these same molecules, produce light from emissive states of the lumophores which are created through annihilation reactions of radical species, which can be modeled through solution electrochemistry. Difference seen in solution reduction and oxidation potentials of molecular components of OLEDs are a lower limit estimate to the differences in energy of these same radical species in the condensed phase environmental. The light emitted from an aluminum quinolate (Alq3)/triarylamine (TPD)-based OLED, or an Alq3/PVK single layers OLED, can be reproduce from solution cross reactions of Alq3/TPD+. The efficiency of this process increases as the oxidation potential of the TPD increases, due to added substituents. Radical cations and anions of solubilized version of quinacridone dopants (DIQA) which have been used to enhance efficiencies in these OLEDs, are shown to be electrochemically more stable than Alq3 and Alq3, and DIQA radical annihilation reactions produce the same emissive state as in the quinacridone-doped OLEDs. Electrochemical studies demonstrate the ways in which other dopants might enhance the efficiency and shift the color output of OLEDs, across the entire visible and near-IR spectrum. Chemical degradation pathways of these same molecular components, which they may undergo during OLED operation, are also revealed by these electrochemical studies.

Competition between the compound and the pre-compound emission processes in α-induced reactions at near astrophysical energy to well above it

NASA Astrophysics Data System (ADS)

Sharma, Manoj Kumar; Sharma, Vijay Raj; Yadav, Abhiskek; Singh, Pushpendra P.; Singh, B. P.; Prasad, R.

2016-04-01

The study of pre-compound emission in α-induced reactions, particularly at the low incident energies, is of considerable interest as the pre-compound emission is more likely to occur at higher energies. With a view to study the competition between the compound and the pre-compound emission processes in α-induced reactions at different energies and with different targets, a systematics for neutron emission channels in targets 51V, 55Mn, 93Nb, 121, 123Sb and 141Pr at energy ranging from astrophysical interest to well above it, has been developed. The off-line γ-ray-spectrometry based activation technique has been adopted to measure the excitation functions. The experimental excitation functions have been analysed within the framework of the compound nucleus mechanism based on the Weisskopf-Ewing model and the pre-compound emission calculations based on the geometry dependent hybrid model. The analysis of the data shows that experimental excitation functions could be reproduced only when the pre-compound emission, simulated theoretically, is taken into account. The strength of pre-compound emission process for each system has been obtained by deducing the pre-compound fraction. Analysis of data indicates that in α-induced reactions, the pre-compound emission process plays an important role, particularly at the low incident energies, where the pure compound nucleus process is likely to dominate.

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).

Adsorption and diffusion of fructose in zeolite HZSM-5: selection of models and methods for computational studies.

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

Cheng, L.; Curtiss, L. A.; Assary, R. S.

The adsorption and protonation of fructose in HZSM-5 have been studied for the assessment of models for accurate reaction energy calculations and the evaluation of molecular diffusivity. The adsorption and protonation were calculated using 2T, 5T, and 46T clusters as well as a periodic model. The results indicate that the reaction thermodynamics cannot be predicted correctly using small cluster models, such as 2T or 5T, because these small cluster models fail to represent the electrostatic effect of a zeolite cage, which provides additional stabilization to the ion pair formed upon the protonation of fructose. Structural parameters optimized using the 46Tmore » cluster model agree well with those of the full periodic model; however, the calculated reaction energies are in significant error due to the poor account of dispersion effects by density functional theory. The dispersion effects contribute -30.5 kcal/mol to the binding energy of fructose in the zeolite pore based on periodic model calculations that include dispersion interactions. The protonation of the fructose ternary carbon hydroxyl group was calculated to be exothermic by 5.5 kcal/mol with a reaction barrier of 2.9 kcal/mol using the periodic model with dispersion effects. Our results suggest that the internal diffusion of fructose in HZSM-5 is very likely to be energetically limited and only occurs at high temperature due to the large size of the molecule.« less

Adsorption and Diffusion of Fructose in Zeolite HZSM-5: Selection of Models and Methods for Computational Studies

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

Cheng, Lei; Curtiss, Larry A.; Assary, Rajeev S.

The adsorption and protonation of fructose inHZSM-5 have been studied for the assessment of models for accurate reaction energy calculations and the evaluation of molecular diffusivity. The adsorption and protonation were calculated using 2T, 5T, and 46T clusters as well as a periodic model. The results indicate that the reaction thermodynamics cannot be predicted correctly using small cluster models, such as 2T or 5T, because these small cluster models fail to represent the electrostatic effect of a zeolite cage, which provides additional stabilization to the ion pair formed upon the protonation of fructose. Structural parameters optimized using the 46T clustermore » model agree well with those of the full periodic model; however, the calculated reaction energies are in significant error due to the poor account of dispersion effects by density functional theory. The dispersion effects contribute -30.5 kcal/mol to the binding energy of fructose in the zeolite pore based on periodic model calculations that include dispersion interactions. The protonation of the fructose ternary carbon hydroxyl group was calculated to be exothermic by 5.5 kcal/mol with a reaction barrier of 2.9 kcal/mol using the periodic model with dispersion effects. Our results suggest that the internal diffusion of fructose in HZSM-5 is very likely to be energetically limited and only occurs at high temperature due to the large size of the molecule.« less

Probing the Structure of {sup 74}Ge Nucleus with Coupled-channels Analysis of {sup 74}Ge+{sup 74}Ge Fusion Reaction

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

Zamrun F, Muhammad; Jurusan Fisika FMIPA, Universitas Haluoleo, Kendari, Sulawesi Tenggara, 93232; Kasim, Hasan Abu

2010-12-23

We study the fusion reaction of the {sup 74}Ge+{sup 74}Ge system in term of the full order coupled-channels formalism. We especially calculated the fusion cross section as well as the fusion barrier distribution of this reaction using transition matrix suggested by recent Coulomb excitation experiment. We compare the results with the one obtained by coupling matrix based on pure vibrational and rotational models. The present coupled-channels calculations for the barrier distributions obtained using experiment coupling matrix is in good agreement with the one obtained with vibrational model, in contrast to the rotational model. This is indicates that {sup 74}Ge nucleusmore » favor a spherical shape than a deformed shape in its ground state. Our results will resolve the debates concerning the structure of this nucleus.« less

Multi-scale modeling of irradiation effects in spallation neutron source materials

NASA Astrophysics Data System (ADS)

Yoshiie, T.; Ito, T.; Iwase, H.; Kaneko, Y.; Kawai, M.; Kishida, I.; Kunieda, S.; Sato, K.; Shimakawa, S.; Shimizu, F.; Hashimoto, S.; Hashimoto, N.; Fukahori, T.; Watanabe, Y.; Xu, Q.; Ishino, S.

2011-07-01

Changes in mechanical property of Ni under irradiation by 3 GeV protons were estimated by multi-scale modeling. The code consisted of four parts. The first part was based on the Particle and Heavy-Ion Transport code System (PHITS) code for nuclear reactions, and modeled the interactions between high energy protons and nuclei in the target. The second part covered atomic collisions by particles without nuclear reactions. Because the energy of the particles was high, subcascade analysis was employed. The direct formation of clusters and the number of mobile defects were estimated using molecular dynamics (MD) and kinetic Monte-Carlo (kMC) methods in each subcascade. The third part considered damage structural evolutions estimated by reaction kinetic analysis. The fourth part involved the estimation of mechanical property change using three-dimensional discrete dislocation dynamics (DDD). Using the above four part code, stress-strain curves for high energy proton irradiated Ni were obtained.

Uncertainty in measurements of the photorespiratory CO2 compensation point and its impact on models of leaf photosynthesis

USDA-ARS?s Scientific Manuscript database

Rates of carbon dioxide assimilation through photosynthesis are readily modeled through the Farquhar, von Caemmerer and Berry (FvCB) model based on the biochemistry of the initial Rubisco-catalyzed reaction of net C3 carbon assimilation. As models of CO2 assimilation are used more broadly for simula...

Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

PubMed Central

2011-01-01

Background Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i) naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii) can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis). Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications. Results We present the first genome-scale metabolic model (iCM925) for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test). Inhibition of the hydrogenase reaction was found to have a strong effect on butanol formation--as experimentally observed. Conclusions Microbial production of butanol by C. beijerinckii offers a promising, sustainable, method for generation of this important chemical and potential biofuel. iCM925 is a predictive model that can accurately reproduce physiological behavior and provide insight into the underlying mechanisms of microbial butanol production. As such, the model will be instrumental in efforts to better understand, and metabolically engineer, this microorganism for improved butanol production. PMID:21846360

Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

PubMed

Kiparissides, A; Hatzimanikatis, V

2017-01-01

The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

EMPIRE: Nuclear Reaction Model Code System for Data Evaluation

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

Herman, M.; Capote, R.; Carlson, B.V.

EMPIRE is a modular system of nuclear reaction codes, comprising various nuclear models, and designed for calculations over a broad range of energies and incident particles. A projectile can be a neutron, proton, any ion (including heavy-ions) or a photon. The energy range extends from the beginning of the unresolved resonance region for neutron-induced reactions ({approx} keV) and goes up to several hundred MeV for heavy-ion induced reactions. The code accounts for the major nuclear reaction mechanisms, including direct, pre-equilibrium and compound nucleus ones. Direct reactions are described by a generalized optical model (ECIS03) or by the simplified coupled-channels approachmore » (CCFUS). The pre-equilibrium mechanism can be treated by a deformation dependent multi-step direct (ORION + TRISTAN) model, by a NVWY multi-step compound one or by either a pre-equilibrium exciton model with cluster emission (PCROSS) or by another with full angular momentum coupling (DEGAS). Finally, the compound nucleus decay is described by the full featured Hauser-Feshbach model with {gamma}-cascade and width-fluctuations. Advanced treatment of the fission channel takes into account transmission through a multiple-humped fission barrier with absorption in the wells. The fission probability is derived in the WKB approximation within the optical model of fission. Several options for nuclear level densities include the EMPIRE-specific approach, which accounts for the effects of the dynamic deformation of a fast rotating nucleus, the classical Gilbert-Cameron approach and pre-calculated tables obtained with a microscopic model based on HFB single-particle level schemes with collective enhancement. A comprehensive library of input parameters covers nuclear masses, optical model parameters, ground state deformations, discrete levels and decay schemes, level densities, fission barriers, moments of inertia and {gamma}-ray strength functions. The results can be converted into ENDF-6 formatted files using the accompanying code EMPEND and completed with neutron resonances extracted from the existing evaluations. The package contains the full EXFOR (CSISRS) library of experimental reaction data that are automatically retrieved during the calculations. Publication quality graphs can be obtained using the powerful and flexible plotting package ZVView. The graphic user interface, written in Tcl/Tk, provides for easy operation of the system. This paper describes the capabilities of the code, outlines physical models and indicates parameter libraries used by EMPIRE to predict reaction cross sections and spectra, mainly for nucleon-induced reactions. Selected applications of EMPIRE are discussed, the most important being an extensive use of the code in evaluations of neutron reactions for the new US library ENDF/B-VII.0. Future extensions of the system are outlined, including neutron resonance module as well as capabilities of generating covariances, using both KALMAN and Monte-Carlo methods, that are still being advanced and refined.« less

Oxidation of Carbon Fibers in a Cracked Ceramic Matrix Composite Modeled as a Function of Temperature

NASA Technical Reports Server (NTRS)

Halbig, Michael C.; Cawley, James D.; Eckel, Andrew J.

2003-01-01

The oxidation model simulates the oxidation of the reinforcing carbon fibers within a ceramic matrix composite material containing as-fabricated microcracks. The physics-based oxidation model uses theoretically and experimentally determined variables as input for the model. The model simulates the ingress of oxygen through microcracks into a two-dimensional plane within the composite material. Model input includes temperature, oxygen concentration, the reaction rate constant, the diffusion coefficient, and the crack opening width as a function of the mechanical and thermal loads. The model is run in an iterative process for a two-dimensional grid system in which oxygen diffuses through the porous and cracked regions of the material and reacts with carbon in short time steps. The model allows the local oxygen concentrations and carbon volumes from the edge to the interior of the composite to be determined over time. Oxidation damage predicted by the model was compared with that observed from microstructural analysis of experimentally tested composite material to validate the model for two temperatures of interest. When the model is run for low-temperature conditions, the kinetics are reaction controlled. Carbon and oxygen reactions occur relatively slowly. Therefore, oxygen can bypass the carbon near the outer edge and diffuse into the interior so that it saturates the entire composite at relatively high concentrations. The kinetics are limited by the reaction rate between carbon and oxygen. This results in an interior that has high local concentrations of oxygen and a similar amount of consumed carbon throughout the cross section. When the model is run for high-temperature conditions, the kinetics are diffusion controlled. Carbon and oxygen reactions occur very quickly. The carbon consumes oxygen as soon as it is supplied. The kinetics are limited by the relatively slow rate at which oxygen is supplied in comparison to the relatively fast rate at which carbon and oxygen reactions occur. This results in a sharp gradient in oxygen concentration from the edge where it is supplied to the nearest source of carbon, which is where the oxygen is quickly consumed. A moving reaction front is seen in which the outlaying carbon is consumed before the next inner layer of carbon begins to react.

New insight into the ZnO sulfidation reaction: mechanism and kinetics modeling of the ZnS outward growth.

PubMed

Neveux, Laure; Chiche, David; Pérez-Pellitero, Javier; Favergeon, Loïc; Gay, Anne-Sophie; Pijolat, Michèle

2013-02-07

Zinc oxide based materials are commonly used for the final desulfurization of synthesis gas in Fischer-Tropsch based XTL processes. Although the ZnO sulfidation reaction has been widely studied, little is known about the transformation at the crystal scale, its detailed mechanism and kinetics. A model ZnO material with well-determined characteristics (particle size and shape) has been synthesized to perform this study. Characterizations of sulfided samples (using XRD, TEM and electron diffraction) have shown the formation of oriented polycrystalline ZnS nanoparticles with a predominant hexagonal form (wurtzite phase). TEM observations also have evidenced an outward development of the ZnS phase, showing zinc and oxygen diffusion from the ZnO-ZnS internal interface to the surface of the ZnS particle. The kinetics of ZnO sulfidation by H(2)S has been investigated using isothermal and isobaric thermogravimetry. Kinetic tests have been performed that show that nucleation of ZnS is instantaneous compared to the growth process. A reaction mechanism composed of eight elementary steps has been proposed to account for these results, and various possible rate laws have been determined upon approximation of the rate-determining step. Thermogravimetry experiments performed in a wide range of H(2)S and H(2)O partial pressures have shown that the ZnO sulfidation reaction rate has a nonlinear variation with H(2)S partial pressure at the same time no significant influence of water vapor on reaction kinetics has been observed. From these observations, a mixed kinetics of external interface reaction with water desorption and oxygen diffusion has been determined to control the reaction kinetics and the proposed mechanism has been validated. However, the formation of voids at the ZnO-ZnS internal interface, characterized by TEM and electron tomography, strongly slows down the reaction rate. Therefore, the impact of the decreasing ZnO-ZnS internal interface on reaction kinetics has been taken into account in the reaction rate expression. In this way the void formation at the interface has been modeled considering a random nucleation followed by an isotropic growth of cavities. Very good agreement has been observed between both experimental and calculated rates after taking into account the decrease in the ZnO-ZnS internal interface.

Heavy residues from very mass asymmetric heavy ion reactions

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

Hanold, Karl Alan

1994-08-01

The isotopic production cross sections and momenta of all residues with nuclear charge (Z) greater than 39 from the reaction of 26, 40, and 50 MeV/nucleon 129Xe + Be, C, and Al were measured. The isotopic cross sections, the momentum distribution for each isotope, and the cross section as a function of nuclear charge and momentum are presented here. The new cross sections are consistent with previous measurements of the cross sections from similar reaction systems. The shape of the cross section distribution, when considered as a function of Z and velocity, was found to be qualitatively consistent with thatmore » expected from an incomplete fusion reaction mechanism. An incomplete fusion model coupled to a statistical decay model is able to reproduce many features of these reactions: the shapes of the elemental cross section distributions, the emission velocity distributions for the intermediate mass fragments, and the Z versus velocity distributions. This model gives a less satisfactory prediction of the momentum distribution for each isotope. A very different model based on the Boltzman-Nordheim-Vlasov equation and which was also coupled to a statistical decay model reproduces many features of these reactions: the shapes of the elemental cross section distributions, the intermediate mass fragment emission velocity distributions, and the Z versus momentum distributions. Both model calculations over-estimate the average mass for each element by two mass units and underestimate the isotopic and isobaric widths of the experimental distributions. It is shown that the predicted average mass for each element can be brought into agreement with the data by small, but systematic, variation of the particle emission barriers used in the statistical model. The predicted isotopic and isobaric widths of the cross section distributions can not be brought into agreement with the experimental data using reasonable parameters for the statistical model.« less

Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

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

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong

2014-12-10

Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverifiedmore » reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.« less

Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

PubMed Central

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R.; Jijakli, Kenan; Salehi-Ashtiani, Kourosh

2014-01-01

Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates. PMID:25540776

Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling.

PubMed

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R; Jijakli, Kenan; Salehi-Ashtiani, Kourosh

2014-01-01

Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

Temperature influence on the malonic acid decomposition in the Belousov-Zhabotinsky reaction

NASA Astrophysics Data System (ADS)

Blagojević, S. M.; Anić, S. R.; Čupić, Ž. D.; Pejić, N. D.; Kolar-Anić, Lj. Z.

2009-09-01

The kinetic investigations of the malonic acid decomposition (8.00 × 10-3 mol dm-3 ≤ [CH2(COOH)2]0 ≤ 4.30 × 10-2 mol dm-3) in the Belousov-Zhabotinsky (BZ) system in the presence of bromate, bromide, sulfuric acid and cerium sulfate, were performed in the isothermal closed well stirred reactor at different temperatures (25.0°C ≤ T ≤ 45.0°C). The formal kinetics of the overall BZ reaction, and particularly kinetics in characteristic periods of BZ reaction, based on the analyses of the bromide oscillograms, was accomplished. The evolution as well as the rate constants and the apparent activation energies of the reactions, which exist in the preoscillatory and oscillatory periods, are also successfully calculated by numerical simulations. Simulations are based on the model including the Br2O species.

Ionic Liquid Droplet Microreactor for Catalysis Reactions Not at Equilibrium.

PubMed

Zhang, Ming; Ettelaie, Rammile; Yan, Tao; Zhang, Suojiang; Cheng, Fangqin; Binks, Bernard P; Yang, Hengquan

2017-12-06

We develop a novel strategy to more effectively and controllably process continuous enzymatic or homogeneous catalysis reactions based on nonaqueous Pickering emulsions. A key element of this strategy is "bottom-up" construction of a macroscale continuous flow reaction system through packing catalyst-containing micron-sized ionic liquid (IL) droplet in oil in a column reactor. Due to the continuous influx of reactants into the droplet microreactors and the continuous release of products from the droplet microreactors, catalysis reactions in such a system can take place without limitations arising from establishment of the reaction equilibrium and catalyst separation, inherent in conventional batch reactions. As proof of the concept, enzymatic enantioselective trans-esterification and CuI-catalyzed cycloaddition reactions using this IL droplet-based flow system both exhibit 8 to 25-fold enhancement in catalysis efficiency compared to their batch counterparts, and a durability of at least 4000 h for the enantioselective trans-esterification of 1-phenylethyl alcohol, otherwise unattainable in their batch counterparts. We further establish a theoretical model for such a catalysis system working under nonequilibrium conditions, which not only supports the experimental results but also helps to predict reaction progress at a microscale level. Being operationally simple, efficient, and adaptive, this strategy provides an unprecedented platform for practical applications of enzymes and homogeneous catalysts even at a controllable level.

On-the-Fly Kinetic Monte Carlo Simulation of Aqueous Phase Advanced Oxidation Processes.

PubMed

Guo, Xin; Minakata, Daisuke; Crittenden, John

2015-08-04

We have developed an on-the-fly kinetic Monte Carlo (KMC) model to predict the degradation mechanisms and fates of intermediates and byproducts that are produced during aqueous-phase advanced oxidation processes (AOPs). The on-the-fly KMC model is composed of a reaction pathway generator, a reaction rate constant estimator, a mechanistic reduction module, and a KMC solver. The novelty of this work is that we develop the pathway as we march forward in time rather than developing the pathway before we use the KMC method to solve the equations. As a result, we have fewer reactions to consider, and we have greater computational efficiency. We have verified this on-the-fly KMC model for the degradation of polyacrylamide (PAM) using UV light and titanium dioxide (i.e., UV/TiO2). Using the on-the-fly KMC model, we were able to predict the time-dependent profiles of the average molecular weight for PAM. The model provided detailed and quantitative insights into the time evolution of the molecular weight distribution and reaction mechanism. We also verified our on-the-fly KMC model for the destruction of (1) acetone, (2) trichloroethylene (TCE), and (3) polyethylene glycol (PEG) for the ultraviolet light and hydrogen peroxide AOP. We demonstrated that the on-the-fly KMC model can achieve the same accuracy as the computer-based first-principles KMC (CF-KMC) model, which has already been validated in our earlier work. The on-the-fly KMC is particularly suitable for molecules with large molecular weights (e.g., polymers) because the degradation mechanisms for large molecules can result in hundreds of thousands to even millions of reactions. The ordinary differential equations (ODEs) that describe the degradation pathways cannot be solved using traditional numerical methods, but the KMC can solve these equations.

Constraining a hybrid volatility basis-set model for aging of wood-burning emissions using smog chamber experiments: a box-model study based on the VBS scheme of the CAMx model (v5.40)

NASA Astrophysics Data System (ADS)

Ciarelli, Giancarlo; El Haddad, Imad; Bruns, Emily; Aksoyoglu, Sebnem; Möhler, Ottmar; Baltensperger, Urs; Prévôt, André S. H.

2017-06-01

In this study, novel wood combustion aging experiments performed at different temperatures (263 and 288 K) in a ˜ 7 m3 smog chamber were modelled using a hybrid volatility basis set (VBS) box model, representing the emission partitioning and their oxidation against OH. We combine aerosol-chemistry box-model simulations with unprecedented measurements of non-traditional volatile organic compounds (NTVOCs) from a high-resolution proton transfer reaction mass spectrometer (PTR-MS) and with organic aerosol measurements from an aerosol mass spectrometer (AMS). Due to this, we are able to observationally constrain the amounts of different NTVOC aerosol precursors (in the model) relative to low volatility and semi-volatile primary organic material (OMsv), which is partitioned based on current published volatility distribution data. By comparing the NTVOC / OMsv ratios at different temperatures, we determine the enthalpies of vaporization of primary biomass-burning organic aerosols. Further, the developed model allows for evaluating the evolution of oxidation products of the semi-volatile and volatile precursors with aging. More than 30 000 box-model simulations were performed to retrieve the combination of parameters that best fit the observed organic aerosol mass and O : C ratios. The parameters investigated include the NTVOC reaction rates and yields as well as enthalpies of vaporization and the O : C of secondary organic aerosol surrogates. Our results suggest an average ratio of NTVOCs to the sum of non-volatile and semi-volatile organic compounds of ˜ 4.75. The mass yields of these compounds determined for a wide range of atmospherically relevant temperatures and organic aerosol (OA) concentrations were predicted to vary between 8 and 30 % after 5 h of continuous aging. Based on the reaction scheme used, reaction rates of the NTVOC mixture range from 3.0 × 10-11 to 4. 0 × 10-11 cm3 molec-1 s-1. The average enthalpy of vaporization of secondary organic aerosol (SOA) surrogates was determined to be between 55 000 and 35 000 J mol-1, which implies a yield increase of 0.03-0.06 % K-1 with decreasing temperature. The improved VBS scheme is suitable for implementation into chemical transport models to predict the burden and oxidation state of primary and secondary biomass-burning aerosols.

Reactive Transport Modeling of Microbe-mediated Fe (II) Oxidation for Enhanced Oil Recovery

NASA Astrophysics Data System (ADS)

Surasani, V.; Li, L.

2011-12-01

Microbially Enhanced Oil Recovery (MEOR) aims to improve the recovery of entrapped heavy oil in depleted reservoirs using microbe-based technology. Reservoir ecosystems often contain diverse microbial communities those can interact with subsurface fluids and minerals through a network of nutrients and energy fluxes. Microbe-mediated reactions products include gases, biosurfactants, biopolymers those can alter the properties of oil and interfacial interactions between oil, brine, and rocks. In addition, the produced biomass and mineral precipitates can change the reservoir permeability profile and increase sweeping efficiency. Under subsurface conditions, the injection of nitrate and Fe (II) as the electron acceptor and donor allows bacteria to grow. The reaction products include minerals such as Fe(OH)3 and nitrogen containing gases. These reaction products can have large impact on oil and reservoir properties and can enhance the recovery of trapped oil. This work aims to understand the Fe(II) oxidation by nitrate under conditions relevant to MEOR. Reactive transport modeling is used to simulate the fluid flow, transport, and reactions involved in this process. Here we developed a complex reactive network for microbial mediated nitrate-dependent Fe (II) oxidation that involves both thermodynamic controlled aqueous reactions and kinetic controlled Fe (II) mineral reaction. Reactive transport modeling is used to understand and quantify the coupling between flow, transport, and reaction processes. Our results identify key parameter controls those are important for the alteration of permeability profile under field conditions.