ECUT: Energy Conversion and Utilization Technologies program. Heterogeneous catalysis modeling program concept

NASA Technical Reports Server (NTRS)

Voecks, G. E.

1983-01-01

Insufficient theoretical definition of heterogeneous catalysts is the major difficulty confronting industrial suppliers who seek catalyst systems which are more active, selective, and stable than those currently available. In contrast, progress was made in tailoring homogeneous catalysts to specific reactions because more is known about the reaction intermediates promoted and/or stabilized by these catalysts during the course of reaction. However, modeling heterogeneous catalysts on a microscopic scale requires compiling and verifying complex information on reaction intermediates and pathways. This can be achieved by adapting homogeneous catalyzed reaction intermediate species, applying theoretical quantum chemistry and computer technology, and developing a better understanding of heterogeneous catalyst system environments. Research in microscopic reaction modeling is now at a stage where computer modeling, supported by physical experimental verification, could provide information about the dynamics of the reactions that will lead to designing supported catalysts with improved selectivity and stability.

Molecular Dynamics Simulation of the Kinetic Reaction between Ni and Al Nanoparticles

DTIC Science & Technology

2009-01-01

reaction time and temperature for separate nanoparticles has been considered as a model system for a powder metallurgy system. Coated nanoparticles in the...separate nanoparticles has been considered as a model system for a powder metallurgy system. Coated nanoparticles in the form of Ni-coated Al nanoparticles...nanoparticles has been considered as a model system for a powder metallurgy system. Coated nanoparticles in the form of Ni-coated Al nanoparticles

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

Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.

PubMed

Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young

2017-03-14

Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.

Optimization of Maillard Reaction in Model System of Glucosamine and Cysteine Using Response Surface Methodology

PubMed Central

Arachchi, Shanika Jeewantha Thewarapperuma; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Lee, Yang-Bong

2017-01-01

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter’s L, a, and b values. ΔE was consequently set as the fifth response factor. In the statistical analyses, determination coefficients (R2) for their absorbance, Hunter’s L, a, b values, and ΔE were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter’s b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, 111°C reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter’s b value was 2.41 h reaction time, 114°C reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine. PMID:28401086

Optimization of Maillard Reaction in Model System of Glucosamine and Cysteine Using Response Surface Methodology.

PubMed

Arachchi, Shanika Jeewantha Thewarapperuma; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Lee, Yang-Bong

2017-03-01

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter's L, a, and b values. ΔE was consequently set as the fifth response factor. In the statistical analyses, determination coefficients (R 2 ) for their absorbance, Hunter's L, a, b values, and ΔE were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter's b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, 111°C reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter's b value was 2.41 h reaction time, 114°C reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine.

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.

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

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.

Reaction factoring and bipartite update graphs accelerate the Gillespie Algorithm for large-scale biochemical systems.

PubMed

Indurkhya, Sagar; Beal, Jacob

2010-01-06

ODE simulations of chemical systems perform poorly when some of the species have extremely low concentrations. Stochastic simulation methods, which can handle this case, have been impractical for large systems due to computational complexity. We observe, however, that when modeling complex biological systems: (1) a small number of reactions tend to occur a disproportionately large percentage of the time, and (2) a small number of species tend to participate in a disproportionately large percentage of reactions. We exploit these properties in LOLCAT Method, a new implementation of the Gillespie Algorithm. First, factoring reaction propensities allows many propensities dependent on a single species to be updated in a single operation. Second, representing dependencies between reactions with a bipartite graph of reactions and species requires only storage for reactions, rather than the required for a graph that includes only reactions. Together, these improvements allow our implementation of LOLCAT Method to execute orders of magnitude faster than currently existing Gillespie Algorithm variants when simulating several yeast MAPK cascade models.

Reaction Factoring and Bipartite Update Graphs Accelerate the Gillespie Algorithm for Large-Scale Biochemical Systems

PubMed Central

Indurkhya, Sagar; Beal, Jacob

2010-01-01

ODE simulations of chemical systems perform poorly when some of the species have extremely low concentrations. Stochastic simulation methods, which can handle this case, have been impractical for large systems due to computational complexity. We observe, however, that when modeling complex biological systems: (1) a small number of reactions tend to occur a disproportionately large percentage of the time, and (2) a small number of species tend to participate in a disproportionately large percentage of reactions. We exploit these properties in LOLCAT Method, a new implementation of the Gillespie Algorithm. First, factoring reaction propensities allows many propensities dependent on a single species to be updated in a single operation. Second, representing dependencies between reactions with a bipartite graph of reactions and species requires only storage for reactions, rather than the required for a graph that includes only reactions. Together, these improvements allow our implementation of LOLCAT Method to execute orders of magnitude faster than currently existing Gillespie Algorithm variants when simulating several yeast MAPK cascade models. PMID:20066048

Modeling human behaviors and reactions under dangerous environment.

PubMed

Kang, J; Wright, D K; Qin, S F; Zhao, Y

2005-01-01

This paper describes the framework of a real-time simulation system to model human behavior and reactions in dangerous environments. The system utilizes the latest 3D computer animation techniques, combined with artificial intelligence, robotics and psychology, to model human behavior, reactions and decision making under expected/unexpected dangers in real-time in virtual environments. The development of the system includes: classification on the conscious/subconscious behaviors and reactions of different people; capturing different motion postures by the Eagle Digital System; establishing 3D character animation models; establishing 3D models for the scene; planning the scenario and the contents; and programming within Virtools Dev. Programming within Virtools Dev is subdivided into modeling dangerous events, modeling character's perceptions, modeling character's decision making, modeling character's movements, modeling character's interaction with environment and setting up the virtual cameras. The real-time simulation of human reactions in hazardous environments is invaluable in military defense, fire escape, rescue operation planning, traffic safety studies, and safety planning in chemical factories, the design of buildings, airplanes, ships and trains. Currently, human motion modeling can be realized through established technology, whereas to integrate perception and intelligence into virtual human's motion is still a huge undertaking. The challenges here are the synchronization of motion and intelligence, the accurate modeling of human's vision, smell, touch and hearing, the diversity and effects of emotion and personality in decision making. There are three types of software platforms which could be employed to realize the motion and intelligence within one system, and their advantages and disadvantages are discussed.

High-intensity ultrasound production of Maillard reaction flavor compounds in a cysteine-xylose model system.

PubMed

Ong, Olivia X H; Seow, Yi-Xin; Ong, Peter K C; Zhou, Weibiao

2015-09-01

Application of high intensity ultrasound has shown potential in the production of Maillard reaction odor-active flavor compounds in model systems. The impact of initial pH, sonication duration, and ultrasound intensity on the production of Maillard reaction products (MRPs) by ultrasound processing in a cysteine-xylose model system were evaluated using Response Surface Methodology (RSM) with a modified mathematical model. Generation of selected MRPs, 2-methylthiophene and tetramethyl pyrazine, was optimal at an initial pH of 6.00, accompanied with 78.1 min of processing at an ultrasound intensity of 19.8 W cm(-2). However, identification of volatiles using gas chromatography-mass spectrometry (GC/MS) revealed that ultrasound-assisted Maillard reactions generated fewer sulfur-containing volatile flavor compounds as compared to conventional heat treatment of the model system. Likely reasons for this difference in flavor profile include the expulsion of H2S due to ultrasonic degassing and inefficient transmission of ultrasonic energy. Copyright © 2015 Elsevier B.V. All rights reserved.

Hybrid deterministic/stochastic simulation of complex biochemical systems.

PubMed

Lecca, Paola; Bagagiolo, Fabio; Scarpa, Marina

2017-11-21

In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by complex networks of chemical reactions involving genes, proteins, and enzymes. Accurate computational models are indispensable means for understanding the mechanisms behind the evolution of a complex system, not always explored with wet lab experiments. To serve their purpose, computational models, however, should be able to describe and simulate the complexity of a biological system in many of its aspects. Moreover, it should be implemented by efficient algorithms requiring the shortest possible execution time, to avoid enlarging excessively the time elapsing between data analysis and any subsequent experiment. Besides the features of their topological structure, the complexity of biological networks also refers to their dynamics, that is often non-linear and stiff. The stiffness is due to the presence of molecular species whose abundance fluctuates by many orders of magnitude. A fully stochastic simulation of a stiff system is computationally time-expensive. On the other hand, continuous models are less costly, but they fail to capture the stochastic behaviour of small populations of molecular species. We introduce a new efficient hybrid stochastic-deterministic computational model and the software tool MoBioS (MOlecular Biology Simulator) implementing it. The mathematical model of MoBioS uses continuous differential equations to describe the deterministic reactions and a Gillespie-like algorithm to describe the stochastic ones. Unlike the majority of current hybrid methods, the MoBioS algorithm divides the reactions' set into fast reactions, moderate reactions, and slow reactions and implements a hysteresis switching between the stochastic model and the deterministic model. Fast reactions are approximated as continuous-deterministic processes and modelled by deterministic rate equations. Moderate reactions are those whose reaction waiting time is greater than the fast reaction waiting time but smaller than the slow reaction waiting time. A moderate reaction is approximated as a stochastic (deterministic) process if it was classified as a stochastic (deterministic) process at the time at which it crosses the threshold of low (high) waiting time. A Gillespie First Reaction Method is implemented to select and execute the slow reactions. The performances of MoBios were tested on a typical example of hybrid dynamics: that is the DNA transcription regulation. The simulated dynamic profile of the reagents' abundance and the estimate of the error introduced by the fully deterministic approach were used to evaluate the consistency of the computational model and that of the software tool.

System Modeling for Ammonia Synthesis Energy Recovery System

NASA Astrophysics Data System (ADS)

Bran Anleu, Gabriela; Kavehpour, Pirouz; Lavine, Adrienne; Ammonia thermochemical Energy Storage Team

2015-11-01

An ammonia thermochemical energy storage system is an alternative solution to the state-of-the-art molten salt TES system for concentrating solar power. Some of the advantages of this emerging technology include its high energy density, no heat losses during the storage duration, and the possibility of long storage periods. Solar energy powers an endothermic reaction to disassociate ammonia into hydrogen and nitrogen, which can be stored for future use. The reverse reaction is carried out in the energy recovery process; a hydrogen-nitrogen mixture flowing through a catalyst bed undergoes the exothermic ammonia synthesis reaction. The goal is to use the ammonia synthesis reaction to heat supercritical steam to temperatures on the order of 650°C as required for a supercritical steam Rankine cycle. The steam will flow through channels in a combined reactor-heat exchanger. A numerical model has been developed to determine the optimal design to heat supercritical steam while maintaining a stable exothermic reaction. The model consists of a transient one dimensional concentric tube counter-flow reactor-heat exchanger. The numerical model determines the inlet mixture conditions needed to achieve various steam outlet conditions.

Instability of turing patterns in reaction-diffusion-ODE systems.

PubMed

Marciniak-Czochra, Anna; Karch, Grzegorz; Suzuki, Kanako

2017-02-01

The aim of this paper is to contribute to the understanding of the pattern formation phenomenon in reaction-diffusion equations coupled with ordinary differential equations. Such systems of equations arise, for example, from modeling of interactions between cellular processes such as cell growth, differentiation or transformation and diffusing signaling factors. We focus on stability analysis of solutions of a prototype model consisting of a single reaction-diffusion equation coupled to an ordinary differential equation. We show that such systems are very different from classical reaction-diffusion models. They exhibit diffusion-driven instability (turing instability) under a condition of autocatalysis of non-diffusing component. However, the same mechanism which destabilizes constant solutions of such models, destabilizes also all continuous spatially heterogeneous stationary solutions, and consequently, there exist no stable Turing patterns in such reaction-diffusion-ODE systems. We provide a rigorous result on the nonlinear instability, which involves the analysis of a continuous spectrum of a linear operator induced by the lack of diffusion in the destabilizing equation. These results are extended to discontinuous patterns for a class of nonlinearities.

Model reduction of multiscale chemical langevin equations: a numerical case study.

PubMed

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

2009-01-01

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

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 reactive flow model with coupled reaction kinetics for detonation and combustion in non-ideal explosives

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

Miller, P.J.

1996-07-01

A new reactive flow model for highly non-ideal explosives and propellants is presented. These compositions, which contain large amounts of metal, upon explosion have reaction kinetics that are characteristic of both fast detonation and slow metal combustion chemistry. A reaction model for these systems was incorporated into the two-dimensional, finite element, Lagrangian hydrodynamic code, DYNA2D. A description of how to determine the model parameters is given. The use of the model and variations are applied to AP, Al, and nitramine underwater explosive and propellant systems.

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

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.

Reaction Event Counting Statistics of Biopolymer Reaction Systems with Dynamic Heterogeneity.

PubMed

Lim, Yu Rim; Park, Seong Jun; Park, Bo Jung; Cao, Jianshu; Silbey, Robert J; Sung, Jaeyoung

2012-04-10

We investigate the reaction event counting statistics (RECS) of an elementary biopolymer reaction in which the rate coefficient is dependent on states of the biopolymer and the surrounding environment and discover a universal kinetic phase transition in the RECS of the reaction system with dynamic heterogeneity. From an exact analysis for a general model of elementary biopolymer reactions, we find that the variance in the number of reaction events is dependent on the square of the mean number of the reaction events when the size of measurement time is small on the relaxation time scale of rate coefficient fluctuations, which does not conform to renewal statistics. On the other hand, when the size of the measurement time interval is much greater than the relaxation time of rate coefficient fluctuations, the variance becomes linearly proportional to the mean reaction number in accordance with renewal statistics. Gillespie's stochastic simulation method is generalized for the reaction system with a rate coefficient fluctuation. The simulation results confirm the correctness of the analytic results for the time dependent mean and variance of the reaction event number distribution. On the basis of the obtained results, we propose a method of quantitative analysis for the reaction event counting statistics of reaction systems with rate coefficient fluctuations, which enables one to extract information about the magnitude and the relaxation times of the fluctuating reaction rate coefficient, without a bias that can be introduced by assuming a particular kinetic model of conformational dynamics and the conformation dependent reactivity. An exact relationship is established between a higher moment of the reaction event number distribution and the multitime correlation of the reaction rate for the reaction system with a nonequilibrium initial state distribution as well as for the system with the equilibrium initial state distribution.

Link between alginate reaction front propagation and general reaction diffusion theory.

PubMed

Braschler, Thomas; Valero, Ana; Colella, Ludovica; Pataky, Kristopher; Brugger, Jürgen; Renaud, Philippe

2011-03-15

We provide a common theoretical framework reuniting specific models for the Ca(2+)-alginate system and general reaction diffusion theory along with experimental validation on a microfluidic chip. As a starting point, we use a set of nonlinear, partial differential equations that are traditionally solved numerically: the Mikkelsen-Elgsaeter model. Applying the traveling-wave hypothesis as a major simplification, we obtain an analytical solution. The solution indicates that the fundamental properties of the alginate reaction front are governed by a single dimensionless parameter λ. For small λ values, a large depletion zone accompanies the reaction front. For large λ values, the alginate reacts before having the time to diffuse significantly. We show that the λ parameter is of general importance beyond the alginate model system, as it can be used to classify known solutions for second-order reaction diffusion schemes, along with the novel solution presented here. For experimental validation, we develop a microchip model system, in which the alginate gel formation can be carried out in a highly controlled, essentially 1D environment. The use of a filter barrier enables us to rapidly renew the CaCl(2) solution, while maintaining flow speeds lower than 1 μm/s for the alginate compartment. This allows one to impose an exactly known bulk CaCl(2) concentration and diffusion resistance. This experimental model system, taken together with the theoretical development, enables the determination of the entire set of physicochemical parameters governing the alginate reaction front in a single experiment.

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.

Propulsive Reaction Control System Model

NASA Technical Reports Server (NTRS)

Brugarolas, Paul; Phan, Linh H.; Serricchio, Frederick; San Martin, Alejandro M.

2011-01-01

This software models a propulsive reaction control system (RCS) for guidance, navigation, and control simulation purposes. The model includes the drive electronics, the electromechanical valve dynamics, the combustion dynamics, and thrust. This innovation follows the Mars Science Laboratory entry reaction control system design, and has been created to meet the Mars Science Laboratory (MSL) entry, descent, and landing simulation needs. It has been built to be plug-and-play on multiple MSL testbeds [analysis, Monte Carlo, flight software development, hardware-in-the-loop, and ATLO (assembly, test and launch operations) testbeds]. This RCS model is a C language program. It contains two main functions: the RCS electronics model function that models the RCS FPGA (field-programmable-gate-array) processing and commanding of the RCS valve, and the RCS dynamic model function that models the valve and combustion dynamics. In addition, this software provides support functions to initialize the model states, set parameters, access model telemetry, and access calculated thruster forces.

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

Reaction rates for mesoscopic reaction-diffusion kinetics

DOE PAGES

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2015-02-23

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

Reaction rates for mesoscopic reaction-diffusion kinetics

PubMed Central

Hellander, Stefan; Hellander, Andreas; Petzold, Linda

2016-01-01

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

Chemical reaction networks as a model to describe UVC- and radiolytically-induced reactions of simple compounds.

PubMed

Dondi, Daniele; Merli, Daniele; Albini, Angelo; Zeffiro, Alberto; Serpone, Nick

2012-05-01

When a chemical system is submitted to high energy sources (UV, ionizing radiation, plasma sparks, etc.), as is expected to be the case of prebiotic chemistry studies, a plethora of reactive intermediates could form. If oxygen is present in excess, carbon dioxide and water are the major products. More interesting is the case of reducing conditions where synthetic pathways are also possible. This article examines the theoretical modeling of such systems with random-generated chemical networks. Four types of random-generated chemical networks were considered that originated from a combination of two connection topologies (viz., Poisson and scale-free) with reversible and irreversible chemical reactions. The results were analyzed taking into account the number of the most abundant products required for reaching 50% of the total number of moles of compounds at equilibrium, as this may be related to an actual problem of complex mixture analysis. The model accounts for multi-component reaction systems with no a priori knowledge of reacting species and the intermediates involved if system components are sufficiently interconnected. The approach taken is relevant to an earlier study on reactions that may have occurred in prebiotic systems where only a few compounds were detected. A validation of the model was attained on the basis of results of UVC and radiolytic reactions of prebiotic mixtures of low molecular weight compounds likely present on the primeval Earth.

Cox process representation and inference for stochastic reaction-diffusion processes

NASA Astrophysics Data System (ADS)

Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

2016-05-01

Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

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.

Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

NASA Astrophysics Data System (ADS)

Herath, Narmada; Del Vecchio, Domitilla

2018-03-01

Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

The CCONE Code System and its Application to Nuclear Data Evaluation for Fission and Other Reactions

NASA Astrophysics Data System (ADS)

Iwamoto, O.; Iwamoto, N.; Kunieda, S.; Minato, F.; Shibata, K.

2016-01-01

A computer code system, CCONE, was developed for nuclear data evaluation within the JENDL project. The CCONE code system integrates various nuclear reaction models needed to describe nucleon, light charged nuclei up to alpha-particle and photon induced reactions. The code is written in the C++ programming language using an object-oriented technology. At first, it was applied to neutron-induced reaction data on actinides, which were compiled into JENDL Actinide File 2008 and JENDL-4.0. It has been extensively used in various nuclear data evaluations for both actinide and non-actinide nuclei. The CCONE code has been upgraded to nuclear data evaluation at higher incident energies for neutron-, proton-, and photon-induced reactions. It was also used for estimating β-delayed neutron emission. This paper describes the CCONE code system indicating the concept and design of coding and inputs. Details of the formulation for modelings of the direct, pre-equilibrium and compound reactions are presented. Applications to the nuclear data evaluations such as neutron-induced reactions on actinides and medium-heavy nuclei, high-energy nucleon-induced reactions, photonuclear reaction and β-delayed neutron emission are mentioned.

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

Evaluation of an S-system root-finding method for estimating parameters in a metabolic reaction model.

PubMed

Iwata, Michio; Miyawaki-Kuwakado, Atsuko; Yoshida, Erika; Komori, Soichiro; Shiraishi, Fumihide

2018-02-02

In a mathematical model, estimation of parameters from time-series data of metabolic concentrations in cells is a challenging task. However, it seems that a promising approach for such estimation has not yet been established. Biochemical Systems Theory (BST) is a powerful methodology to construct a power-law type model for a given metabolic reaction system and to then characterize it efficiently. In this paper, we discuss the use of an S-system root-finding method (S-system method) to estimate parameters from time-series data of metabolite concentrations. We demonstrate that the S-system method is superior to the Newton-Raphson method in terms of the convergence region and iteration number. We also investigate the usefulness of a translocation technique and a complex-step differentiation method toward the practical application of the S-system method. The results indicate that the S-system method is useful to construct mathematical models for a variety of metabolic reaction networks. Copyright © 2018 Elsevier Inc. All rights reserved.

PHOTOCHEMICAL MODELING APPLIED TO NATURAL WATERS

EPA Science Inventory

The study examines the application of modeling photochemical processes in natural water systems. For many photochemical reactions occurring in natural waters, a simple photochemical model describing reaction rate as a function of intensity, radiation attenuation, reactant absorpt...

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.

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.

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.

Catalytic Chemistry of Hydrocarbon Conversion Reactions on Metallic Single Crystals

NASA Astrophysics Data System (ADS)

Tysoe, Wilfred T.

The ability to be able to follow the chemistry of adsorbates on model catalyst surfaces has, in principle, allowed us to peer inside the “black box” of a catalytic reaction and understand the pathway. Such a strategy is most simply implemented for well-ordered single crystal model catalysts for which the catalytic reaction proceeds in ultrahigh vacuum. Thus, in order to be a good model for the supported catalyst, the single crystal should catalyze the reactions with kinetics identical to those for the supported system. This chapter focuses on catalytic systems that fulfill these criteria, namely alkene and alkyne hydrogenation and acetylene cyclotrimerization on Pd(111). The surface chemistry and geometries of the reactants in ultrahigh vacuum are explored in detail allowing fundamental insights into the catalytic reaction pathways to be obtained.

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.

Moving from Batch to Field Using the RT3D Reactive Transport Modeling System

NASA Astrophysics Data System (ADS)

Clement, T. P.; Gautam, T. R.

2002-12-01

The public domain reactive transport code RT3D (Clement, 1997) is a general-purpose numerical code for solving coupled, multi-species reactive transport in saturated groundwater systems. The code uses MODFLOW to simulate flow and several modules of MT3DMS to simulate the advection and dispersion processes. RT3D employs the operator-split strategy which allows the code solve the coupled reactive transport problem in a modular fashion. The coupling between reaction and transport is defined through a separate module where the reaction equations are specified. The code supports a versatile user-defined reaction option that allows users to define their own reaction system through a Fortran-90 subroutine, known as the RT3D-reaction package. Further a utility code, known as BATCHRXN, allows the users to independently test and debug their reaction package. To analyze a new reaction system at a batch scale, users should first run BATCHRXN to test the ability of their reaction package to model the batch data. After testing, the reaction package can simply be ported to the RT3D environment to study the model response under 1-, 2-, or 3-dimensional transport conditions. This paper presents example problems that demonstrate the methods for moving from batch to field-scale simulations using BATCHRXN and RT3D codes. The first example describes a simple first-order reaction system for simulating the sequential degradation of Tetrachloroethene (PCE) and its daughter products. The second example uses a relatively complex reaction system for describing the multiple degradation pathways of Tetrachloroethane (PCA) and its daughter products. References 1) Clement, T.P, RT3D - A modular computer code for simulating reactive multi-species transport in 3-Dimensional groundwater aquifers, Battelle Pacific Northwest National Laboratory Research Report, PNNL-SA-28967, September, 1997. Available at: http://bioprocess.pnl.gov/rt3d.htm.

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

Waterhammer Modeling for the Ares I Upper Stage Reaction Control System Cold Flow Development Test Article

NASA Technical Reports Server (NTRS)

Williams, Jonathan H.

2010-01-01

The Upper Stage Reaction Control System provides three-axis attitude control for the Ares I launch vehicle during active Upper Stage flight. The system design must accommodate rapid thruster firing to maintain the proper launch trajectory and thus allow for the possibility to pulse multiple thrusters simultaneously. Rapid thruster valve closure creates an increase in static pressure, known as waterhammer, which propagates throughout the propellant system at pressures exceeding nominal design values. A series of development tests conducted in the fall of 2009 at Marshall Space Flight Center were performed using a water-flow test article to better understand fluid performance characteristics of the Upper Stage Reaction Control System. A subset of the tests examined waterhammer along with the subsequent pressure and frequency response in the flight-representative system and provided data to anchor numerical models. This thesis presents a comparison of waterhammer test results with numerical model and analytical results. An overview of the flight system, test article, modeling and analysis are also provided.

Waterhammer modeling for the Ares I Upper Stage Reaction Control System cold flow development test article

NASA Astrophysics Data System (ADS)

Williams, Jonathan Hunter

The Upper Stage Reaction Control System provides in-flight three-axis attitude control for the Ares I Upper Stage. The system design must accommodate rapid thruster firing to maintain proper launch trajectory and thus allow for the possibility to pulse multiple thrusters simultaneously. Rapid thruster valve closure creates an increase in static pressure, known as waterhammer, which propagates throughout the propellant system at pressures exceeding nominal design values. A series of development tests conducted at Marshall Space Flight Center in 2009 were performed using a water-flow test article to better understand fluid characteristics of the Upper Stage Reaction Control System. A subset of the tests examined the waterhammer pressure and frequency response in the flight-representative system and provided data to anchor numerical models. This thesis presents a comparison of waterhammer test results with numerical model and analytical results. An overview of the flight system, test article, modeling and analysis are also provided.

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.

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.

A study of the tyramine/glucose Maillard reaction: Variables, characterization, cytotoxicity and preliminary application.

PubMed

Jiang, Wei; Chen, Yaxin; He, Xiaoxia; Hu, Shiwei; Li, Shijie; Liu, Yu

2018-01-15

The tyramine/glucose Maillard reaction was proposed as an emerging tool for tyramine reduction in a model system and two commercial soy sauce samples. The model system was composed of tyramine and glucose in buffer solutions with or without NaCl. The results showed that tyramine was reduced in the model system, and the reduction rate was affected by temperature, heating time, initial pH value, NaCl concentration, initial glucose concentration and initial tyramine concentration. Changes in fluorescence intensity and ultraviolet-visible (UV-vis) absorption spectra showed three stages of the Maillard reaction between tyramine and glucose. Cytotoxicity assay demonstrated that tyramine/glucose Maillard reaction products (MRPs) were significantly less toxic than that of tyramine (p<0.05). Moreover, tyramine concentration in soy sauce samples was significantly reduced when heated with the addition of glucose (p<0.05). Experimental results showed that the tyramine/glucose Maillard reaction is a promising method for tyramine reduction in foods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

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.

Thermodynamics and combustion modeling

NASA Technical Reports Server (NTRS)

Zeleznik, Frank J.

1986-01-01

Modeling fluid phase phenomena blends the conservation equations of continuum mechanics with the property equations of thermodynamics. The thermodynamic contribution becomes especially important when the phenomena involve chemical reactions as they do in combustion systems. The successful study of combustion processes requires (1) the availability of accurate thermodynamic properties for both the reactants and the products of reaction and (2) the computational capabilities to use the properties. A discussion is given of some aspects of the problem of estimating accurate thermodynamic properties both for reactants and products of reaction. Also, some examples of the use of thermodynamic properties for modeling chemically reacting systems are presented. These examples include one-dimensional flow systems and the internal combustion engine.

A discrete model to study reaction-diffusion-mechanics systems.

PubMed

Weise, Louis D; Nash, Martyn P; Panfilov, Alexander V

2011-01-01

This article introduces a discrete reaction-diffusion-mechanics (dRDM) model to study the effects of deformation on reaction-diffusion (RD) processes. The dRDM framework employs a FitzHugh-Nagumo type RD model coupled to a mass-lattice model, that undergoes finite deformations. The dRDM model describes a material whose elastic properties are described by a generalized Hooke's law for finite deformations (Seth material). Numerically, the dRDM approach combines a finite difference approach for the RD equations with a Verlet integration scheme for the equations of the mass-lattice system. Using this framework results were reproduced on self-organized pacemaking activity that have been previously found with a continuous RD mechanics model. Mechanisms that determine the period of pacemakers and its dependency on the medium size are identified. Finally it is shown how the drift direction of pacemakers in RDM systems is related to the spatial distribution of deformation and curvature effects.

A Discrete Model to Study Reaction-Diffusion-Mechanics Systems

PubMed Central

Weise, Louis D.; Nash, Martyn P.; Panfilov, Alexander V.

2011-01-01

This article introduces a discrete reaction-diffusion-mechanics (dRDM) model to study the effects of deformation on reaction-diffusion (RD) processes. The dRDM framework employs a FitzHugh-Nagumo type RD model coupled to a mass-lattice model, that undergoes finite deformations. The dRDM model describes a material whose elastic properties are described by a generalized Hooke's law for finite deformations (Seth material). Numerically, the dRDM approach combines a finite difference approach for the RD equations with a Verlet integration scheme for the equations of the mass-lattice system. Using this framework results were reproduced on self-organized pacemaking activity that have been previously found with a continuous RD mechanics model. Mechanisms that determine the period of pacemakers and its dependency on the medium size are identified. Finally it is shown how the drift direction of pacemakers in RDM systems is related to the spatial distribution of deformation and curvature effects. PMID:21804911

Nonlinear stability in reaction-diffusion systems via optimal Lyapunov functions

NASA Astrophysics Data System (ADS)

Lombardo, S.; Mulone, G.; Trovato, M.

2008-06-01

We define optimal Lyapunov functions to study nonlinear stability of constant solutions to reaction-diffusion systems. A computable and finite radius of attraction for the initial data is obtained. Applications are given to the well-known Brusselator model and a three-species model for the spatial spread of rabies among foxes.

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.

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.

Numerical Simulation of a Chemically Reacting Sorbent Bed for LSS Applications

NASA Technical Reports Server (NTRS)

Luna, Bernadette; Mitchell, Reggie; Sheppard, Sheri; DeVincenzi, Donald (Technical Monitor)

2000-01-01

A detailed numerical model of a chemisorption bed has been developed. The model is based on the constant pressure mass transport equation for gaseous flow through a packed bed, and the equation for diffusion and reaction within a spherical particle. Because there is a wealth of data from the NASA and the Navy bodies of literature, the LiOH-H2O-CO2 system is chosen for application of the model and interpretation of results. Prior models of this system from the life support literature are limited. The current model incorporates many of the features of elaborate models developed for investigation of industrial systems or energy applications (e.g., coal, desulphurization): it distinguishes bulk convection and bed dispersion; mass transport to the particle surface, transport within the particle, and reaction. It uses the nonsteady (not pseudo-steady state) form of the equations. The chemistry is modeled as a multi-step, reversible reaction with evolving solid structure. The resulting system of equations is large. The ODEPACK family of solvers is used to integrate the system. Reaction coefficients are determined by experiment. Typical results of the model are illustrated with mission input parameters. Using the model, an explanation is offered for 1) the varied performance results found after pre-breathing (or after simulated pre-breathe conditions), 2) interrupted use and 3) low temperature use. In addition, options for a reusable canister are explored. The computational resource implications of adding energy equations are discussed briefly, as are applicability to other relevant space and undersea systems.

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)

The functional properties of chitosan-glucose-asparagine Maillard reaction products and mitigation of acrylamide formation by chitosans.

PubMed

Sung, Wen-Chieh; Chang, Yu-Wei; Chou, Yu-Hao; Hsiao, Hsin-I

2018-03-15

This research aims to clarify the interactions that occur in a food model system consisting of glucose, asparagine and chitosans. Low molecular weight chitosan exerted a potent inhibitory effect (46.8%) on acrylamide and Maillard reaction products (MRPs) (>52.6%), respectively. Compared to a previous study conducted using the fructose system, the novel findings of this research demonstrate that the formation of acrylamide and Maillard reaction products was lower with glucose than with fructose when they were used as reducing sugars in food model systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

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/

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.

Class of self-limiting growth models in the presence of nonlinear diffusion

NASA Astrophysics Data System (ADS)

Kar, Sandip; Banik, Suman Kumar; Ray, Deb Shankar

2002-06-01

The source term in a reaction-diffusion system, in general, does not involve explicit time dependence. A class of self-limiting growth models dealing with animal and tumor growth and bacterial population in a culture, on the other hand, are described by kinetics with explicit functions of time. We analyze a reaction-diffusion system to study the propagation of spatial front for these models.

Patterns and Oscillations in Reaction-Diffusion Systems with Intrinsic Fluctuations

NASA Astrophysics Data System (ADS)

Giver, Michael; Goldstein, Daniel; Chakraborty, Bulbul

2013-03-01

Intrinsic or demographic noise has been shown to play an important role in the dynamics of a variety of systems including predator-prey populations, biochemical reactions within cells, and oscillatory chemical reaction systems, and is known to give rise to oscillations and pattern formation well outside the parameter range predicted by standard mean-field analysis. Initially motivated by an experimental model of cells and tissues where the cells are represented by chemical reagents isolated in emulsion droplets, we study the stochastic Brusselator, a simple activator-inhibitor chemical reaction model. Our work extends the results of recent studies on the zero and one dimensional systems with the ultimate goals of understanding the role of noise in spatially structured systems and engineering novel patterns and attractors induced by fluctuations. In the zero dimensional system, we observe a noise induced switching between small and large amplitude oscillations when a separation of time scales is present, while the spatially extended system displays a similar switching between a stationary Turing pattern and uniform oscillations.

Variationally optimal selection of slow coordinates and reaction coordinates in macromolecular systems

NASA Astrophysics Data System (ADS)

Noe, Frank

To efficiently simulate and generate understanding from simulations of complex macromolecular systems, the concept of slow collective coordinates or reaction coordinates is of fundamental importance. Here we will introduce variational approaches to approximate the slow coordinates and the reaction coordinates between selected end-states given MD simulations of the macromolecular system and a (possibly large) basis set of candidate coordinates. We will then discuss how to select physically intuitive order paremeters that are good surrogates of this variationally optimal result. These result can be used in order to construct Markov state models or other models of the stationary and kinetics properties, in order to parametrize low-dimensional / coarse-grained model of the dynamics. Deutsche Forschungsgemeinschaft, European Research Council.

Extent of reaction in open systems with multiple heterogeneous reactions

USGS Publications Warehouse

Friedly, John C.

1991-01-01

The familiar batch concept of extent of reaction is reexamined for systems of reactions occurring in open systems. Because species concentrations change as a result of transport processes as well as reactions in open systems, the extent of reaction has been less useful in practice in these applications. It is shown that by defining the extent of the equivalent batch reaction and a second contribution to the extent of reaction due to the transport processes, it is possible to treat the description of the dynamics of flow through porous media accompanied by many chemical reactions in a uniform, concise manner. This approach tends to isolate the reaction terms among themselves and away from the model partial differential equations, thereby enabling treatment of large problems involving both equilibrium and kinetically controlled reactions. Implications on the number of coupled partial differential equations necessary to be solved and on numerical algorithms for solving such problems are discussed. Examples provided illustrate the theory applied to solute transport in groundwater flow.

Kinetics and mechanism of olefin catalytic hydroalumination by organoaluminum compounds

NASA Astrophysics Data System (ADS)

Koledina, K. F.; Gubaidullin, I. M.

2016-05-01

The complex reaction mechanism of α-olefin catalytic hydroalumination by alkylalanes is investigated via mathematical modeling that involves plotting the kinetic models for the individual reactions that make up a complex system and a separate study of their principles. Kinetic parameters of olefin catalytic hydroalumination are estimated. Activation energies of the possible steps of the schemes of complex reaction mechanisms are compared and possible reaction pathways are determined.

Can Drosophila melanogaster represent a model system for the detection of reproductive adverse drug reactions?

PubMed

Avanesian, Agnesa; Semnani, Sahar; Jafari, Mahtab

2009-08-01

Once a molecule is identified as a potential drug, the detection of adverse drug reactions is one of the key components of its development and the FDA approval process. We propose using Drosophila melanogaster to screen for reproductive adverse drug reactions in the early stages of drug development. Compared with other non-mammalian models, D. melanogaster has many similarities to the mammalian reproductive system, including putative sex hormones and conserved proteins involved in genitourinary development. Furthermore, the D. melanogaster model would present significant advantages in time efficiency and cost-effectiveness compared with mammalian models. We present data on methotrexate (MTX) reproductive adverse events in multiple animal models, including fruit flies, as proof-of-concept for the use of the D. melanogaster model.

Modeling the mechanism of glycosylation reactions between ethanol, 1,2-ethanediol and methoxymethanol.

PubMed

Azofra, Luis Miguel; Alkorta, Ibon; Toro-Labbé, Alejandro; Elguero, José

2013-09-07

The mechanism of the S(N)2 model glycosylation reaction between ethanol, 1,2-ethanediol and methoxymethanol has been studied theoretically at the B3LYP/6-311+G(d,p) computational level. Three different types of reactions have been explored: (i) the exchange of hydroxyl groups between these model systems; (ii) the basic catalysis reactions by combination of the substrates as glycosyl donors (neutral species) and acceptors (enolate species); and (iii) the effect on the reaction profile of an explicit H2O molecule in the reactions considered in (ii). The reaction force, the electronic chemical potential and the reaction electronic flux have been characterized for the reaction path in each case. Energy calculations show that methoxymethanol is the worst glycosyl donor model among the ones studied here, while 1,2-ethanediol is the best, having the lowest activation barrier of 74.7 kJ mol(-1) for the reaction between this one and the ethanolate as the glycosyl acceptor model. In general, the presence of direct interactions between the atoms involved in the penta-coordinated TS increases the activation energies of the processes.

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.

Modeling of a Reaction-Distillation-Recycle System to Produce Dimethyl Ether through Methanol Dehydration

NASA Astrophysics Data System (ADS)

Muharam, Y.; Zulkarnain, L. M.; Wirya, A. S.

2018-03-01

The increase in the dimethyl ether yield through methanol dehydration due to a recycle integration to a reaction-distillation system was studied in this research. A one-dimensional phenomenological model of a methanol dehydration reactor and a shortcut model of distillation columns were used to achieve the aim. Simulation results show that 10.7 moles/s of dimethyl ether is produced in a reaction-distillation system with the reactor length being 4 m, the reactor inlet pressure being 18 atm, the reactor inlet temperature being 533 K, the reactor inlet velocity being 0.408 m/s, and the distillation pressure being 8 atm. The methanol conversion is 90% and the dimethyl ether yield is 48%. The integration of the recycle stream to the system increases the dimethyl ether yield by 8%.

The analysis of magnesium oxide hydration in three-phase reaction system

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

Tang, Xiaojia; Guo, Lin; Chen, Chen

In order to investigate the magnesium oxide hydration process in gas–liquid–solid (three-phase) reaction system, magnesium hydroxide was prepared by magnesium oxide hydration in liquid–solid (two-phase) and three-phase reaction systems. A semi-empirical model and the classical shrinking core model were used to fit the experimental data. The fitting result shows that both models describe well the hydration process of three-phase system, while only the semi-empirical model right for the hydration process of two-phase system. The characterization of the hydration product using X-Ray diffraction (XRD) and scanning electron microscope (SEM) was performed. The XRD and SEM show hydration process in the two-phasemore » system follows common dissolution/precipitation mechanism. While in the three-phase system, the hydration process undergo MgO dissolution, Mg(OH){sub 2} precipitation, Mg(OH){sub 2} peeling off from MgO particle and leaving behind fresh MgO surface. - Graphical abstract: There was existence of a peeling-off process in the gas–liquid–solid (three-phase) MgO hydration system. - Highlights: • Magnesium oxide hydration in gas–liquid–solid system was investigated. • The experimental data in three-phase system could be fitted well by two models. • The morphology analysis suggested that there was existence of a peel-off process.« less

Mass Transfer with Chemical Reaction.

ERIC Educational Resources Information Center

DeCoursey, W. J.

1987-01-01

Describes the organization of a graduate course dealing with mass transfer, particularly as it relates to chemical reactions. Discusses the course outline, including mathematics models of mass transfer, enhancement of mass transfer rates by homogeneous chemical reaction, and gas-liquid systems with chemical reaction. (TW)

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.

Kinetics based reaction optimization of enzyme catalyzed reduction of formaldehyde to methanol with synchronous cofactor regeneration.

PubMed

Marpani, Fauziah; Sárossy, Zsuzsa; Pinelo, Manuel; Meyer, Anne S

2017-12-01

Enzymatic reduction of carbon dioxide (CO 2 ) to methanol (CH 3 OH) can be accomplished using a designed set-up of three oxidoreductases utilizing reduced pyridine nucleotide (NADH) as cofactor for the reducing equivalents electron supply. For this enzyme system to function efficiently a balanced regeneration of the reducing equivalents during reaction is required. Herein, we report the optimization of the enzymatic conversion of formaldehyde (CHOH) to CH 3 OH by alcohol dehydrogenase, the final step of the enzymatic redox reaction of CO 2 to CH 3 OH, with kinetically synchronous enzymatic cofactor regeneration using either glucose dehydrogenase (System I) or xylose dehydrogenase (System II). A mathematical model of the enzyme kinetics was employed to identify the best reaction set-up for attaining optimal cofactor recycling rate and enzyme utilization efficiency. Targeted process optimization experiments were conducted to verify the kinetically modeled results. Repetitive reaction cycles were shown to enhance the yield of CH 3 OH, increase the total turnover number (TTN) and the biocatalytic productivity rate (BPR) value for both system I and II whilst minimizing the exposure of the enzymes to high concentrations of CHOH. System II was found to be superior to System I with a yield of 8 mM CH 3 OH, a TTN of 160 and BPR of 24 μmol CH 3 OH/U · h during 6 hr of reaction. The study demonstrates that an optimal reaction set-up could be designed from rational kinetics modeling to maximize the yield of CH 3 OH, whilst simultaneously optimizing cofactor recycling and enzyme utilization efficiency. © 2017 Wiley Periodicals, Inc.

Stochastic simulations on a model of circadian rhythm generation.

PubMed

Miura, Shigehiro; Shimokawa, Tetsuya; Nomura, Taishin

2008-01-01

Biological phenomena are often modeled by differential equations, where states of a model system are described by continuous real values. When we consider concentrations of molecules as dynamical variables for a set of biochemical reactions, we implicitly assume that numbers of the molecules are large enough so that their changes can be regarded as continuous and they are described deterministically. However, for a system with small numbers of molecules, changes in their numbers are apparently discrete and molecular noises become significant. In such cases, models with deterministic differential equations may be inappropriate, and the reactions must be described by stochastic equations. In this study, we focus a clock gene expression for a circadian rhythm generation, which is known as a system involving small numbers of molecules. Thus it is appropriate for the system to be modeled by stochastic equations and analyzed by methodologies of stochastic simulations. The interlocked feedback model proposed by Ueda et al. as a set of deterministic ordinary differential equations provides a basis of our analyses. We apply two stochastic simulation methods, namely Gillespie's direct method and the stochastic differential equation method also by Gillespie, to the interlocked feedback model. To this end, we first reformulated the original differential equations back to elementary chemical reactions. With those reactions, we simulate and analyze the dynamics of the model using two methods in order to compare them with the dynamics obtained from the original deterministic model and to characterize dynamics how they depend on the simulation methodologies.

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

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Fluorescence Correlation Spectroscopy and Nonlinear Stochastic Reaction-Diffusion

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

Del Razo, Mauricio; Pan, Wenxiao; Qian, Hong

2014-05-30

The currently existing theory of fluorescence correlation spectroscopy (FCS) is based on the linear fluctuation theory originally developed by Einstein, Onsager, Lax, and others as a phenomenological approach to equilibrium fluctuations in bulk solutions. For mesoscopic reaction-diffusion systems with nonlinear chemical reactions among a small number of molecules, a situation often encountered in single-cell biochemistry, it is expected that FCS time correlation functions of a reaction-diffusion system can deviate from the classic results of Elson and Magde [Biopolymers (1974) 13:1-27]. We first discuss this nonlinear effect for reaction systems without diffusion. For nonlinear stochastic reaction-diffusion systems there are no closedmore » solutions; therefore, stochastic Monte-Carlo simulations are carried out. We show that the deviation is small for a simple bimolecular reaction; the most significant deviations occur when the number of molecules is small and of the same order. Extending Delbrück-Gillespie’s theory for stochastic nonlinear reactions with rapidly stirring to reaction-diffusion systems provides a mesoscopic model for chemical and biochemical reactions at nanometric and mesoscopic level such as a single biological cell.« less

A Comparison of Deterministic and Stochastic Modeling Approaches for Biochemical Reaction Systems: On Fixed Points, Means, and Modes.

PubMed

Hahl, Sayuri K; Kremling, Andreas

2016-01-01

In the mathematical modeling of biochemical reactions, a convenient standard approach is to use ordinary differential equations (ODEs) that follow the law of mass action. However, this deterministic ansatz is based on simplifications; in particular, it neglects noise, which is inherent to biological processes. In contrast, the stochasticity of reactions is captured in detail by the discrete chemical master equation (CME). Therefore, the CME is frequently applied to mesoscopic systems, where copy numbers of involved components are small and random fluctuations are thus significant. Here, we compare those two common modeling approaches, aiming at identifying parallels and discrepancies between deterministic variables and possible stochastic counterparts like the mean or modes of the state space probability distribution. To that end, a mathematically flexible reaction scheme of autoregulatory gene expression is translated into the corresponding ODE and CME formulations. We show that in the thermodynamic limit, deterministic stable fixed points usually correspond well to the modes in the stationary probability distribution. However, this connection might be disrupted in small systems. The discrepancies are characterized and systematically traced back to the magnitude of the stoichiometric coefficients and to the presence of nonlinear reactions. These factors are found to synergistically promote large and highly asymmetric fluctuations. As a consequence, bistable but unimodal, and monostable but bimodal systems can emerge. This clearly challenges the role of ODE modeling in the description of cellular signaling and regulation, where some of the involved components usually occur in low copy numbers. Nevertheless, systems whose bimodality originates from deterministic bistability are found to sustain a more robust separation of the two states compared to bimodal, but monostable systems. In regulatory circuits that require precise coordination, ODE modeling is thus still expected to provide relevant indications on the underlying dynamics.

Multi-variable mathematical models for the air-cathode microbial fuel cell system

NASA Astrophysics Data System (ADS)

Ou, Shiqi; Kashima, Hiroyuki; Aaron, Douglas S.; Regan, John M.; Mench, Matthew M.

2016-05-01

This research adopted the version control system into the model construction for the single chamber air-cathode microbial fuel cell (MFC) system, to understand the interrelation of biological, chemical, and electrochemical reactions. The anodic steady state model was used to consider the chemical species diffusion and electric migration influence to the MFC performance. In the cathodic steady state model, the mass transport and reactions in a multi-layer, abiotic cathode and multi-bacteria cathode biofilm were simulated. Transport of hydroxide was assumed for cathodic pH change. This assumption is an alternative to the typical notion of proton consumption during oxygen reduction to explain elevated cathode pH. The cathodic steady state model provided the power density and polarization curve performance results that can be compared to an experimental MFC system. Another aspect considered was the relative contributions of platinum catalyst and microbes on the cathode to the oxygen reduction reaction (ORR). Simulation results showed that the biocatalyst in a cathode that includes a Pt/C catalyst likely plays a minor role in ORR, contributing up to 8% of the total power calculated by the models.

Coupling Fluid Dynamics and Multiphase Disequilibria: Applications to Eutectic and Peritectic Systems

NASA Astrophysics Data System (ADS)

Tweed, L. E. L.; Spiegelman, M. W.; Kelemen, P. B.

2017-12-01

Computational thermodynamics has yielded great insights into petrological processes. However, on its own it cannot capture the inherently dynamic nature of many of these processes which depend on the interaction between time-dependent processes including advection, diffusion and chemical reaction. To understand this interplay, and to move away from a purely equilibrium view, requires the integration of computational thermodynamics and fluid mechanics. A key aspect of doing this is the treatment of chemical reactions as time-dependent, irreversible processes. Such a development is integral to understanding a host of petrological questions from the open system evolution of magma chambers to the dynamics of melt migration beneath mid-ocean ridges and flux melting of the mantle wedge in subduction zones. A simple thermodynamically consistent reactive model is developed that can be integrated with conservation equations for mass, momentum and energy. The model rests on the thermodynamic characterization of an independent set of reactions and has the advantage of being completely general and easily extensible to systems comprising multiple solid and liquid phases. The underlying theory is described in detail in another contribution in this session. Here we apply the framework to experimentally constrained simple systems of petrological interest including the fo-qz binary and the fo-qz-k2o ternary. These systems contain a variety of phase topologies including eutectic and peritectic reactions. As the model allows for the seamless exhaustion and stabilization of phases, we can explore the effect that these discontinuous changes have on the compositional and dynamic evolution of the system. To do this we track how the systems respond to sudden changes in intensive variables that perturb them from equilibrium. Such changes are rife in crustal magmatic systems. Simulations for decompression melting are also run to explore the interplay between reactive and advective fluxes. Buffering between the multiple reactions can result in surprising reaction paths highlighting that micro-mechanics could play a significant role in magmatic evolution. By building up the complexity of the problems gradually, we develop an intuition for the effect of model choices including the kinetic law and the set of reactions used.

Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

PubMed

Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota

2016-01-01

The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

Interpretation of current-voltage relationships for "active" ion transport systems: I. Steady-state reaction-kinetic analysis of class-I mechanisms.

PubMed

Hansen, U P; Gradmann, D; Sanders, D; Slayman, C L

1981-01-01

This paper develops a simple reaction-kinetic model to describe electrogenic pumping and co- (or counter-) transport of ions. It uses the standard steady-state approach for cyclic enzyme- or carrier-mediated transport, but does not assume rate-limitation by any particular reaction step. Voltage-dependence is introduced, after the suggestion of Läuger and Stark (Biochim. Biophys. Acta 211:458-466, 1970), via a symmetric Eyring barrier, in which the charge-transit reaction constants are written as k12 = ko12 exp(zF delta psi/2RT) and k21 = ko21 exp(-zF delta psi/2RT). For interpretation of current-voltage relationships, all voltage-independent reaction steps are lumped together, so the model in its simplest form can be described as a pseudo-2-state model. It is characterized by the two voltage-dependent reaction constants, two lumped voltage-independent reaction constants (k12, k21), and two reserve factors (ri, ro) which formally take account of carrier states that are indistinguishable in the current-voltage (I-V) analysis. The model generates a wide range of I-V relationships, depending on the relative magnitudes of the four reaction constants, sufficient to describe essentially all I-V datas now available on "active" ion-transport systems. Algebraic and numerical analysis of the reserve factors, by means of expanded pseudo-3-, 4-, and 5-state models, shows them to be bounded and not large for most combinations of reaction constants in the lumped pathway. The most important exception to this rule occurs when carrier decharging immediately follows charge transit of the membrane and is very fast relative to other constituent voltage-independent reactions. Such a circumstance generates kinetic equivalence of chemical and electrical gradients, thus providing a consistent definition of ion-motive forces (e.g., proton-motive force, PMF). With appropriate restrictions, it also yields both linear and log-linear relationships between net transport velocity and either membrane potential or PMF. The model thus accommodates many known properties of proton-transport systems, particularly as observed in "chemiosmotic" or energy-coupling membranes.

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...

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

Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.

PubMed

Horne, Gregory P; Donoclift, Thomas A; Sims, Howard E; Orr, Robin M; Pimblott, Simon M

2016-11-17

A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.

A general model for techno-economic analysis of CSP plants with thermochemical energy storage systems

NASA Astrophysics Data System (ADS)

Peng, Xinyue; Maravelias, Christos T.; Root, Thatcher W.

2017-06-01

Thermochemical energy storage (TCES), with high energy density and wide operating temperature range, presents a potential solution for CSP plant energy storage. We develop a general optimization based process model for CSP plants employing a wide range of TCES systems which allows us to assess the plant economic feasibility and energy efficiency. The proposed model is applied to a 100 MW CSP plant employing ammonia or methane TCES systems. The methane TCES system with underground gas storage appears to be the most promising option, achieving a 14% LCOE reduction over the current two-tank molten-salt CSP plants. For general TCES systems, gas storage is identified as the main cost driver, while the main energy driver is the compressor electricity consumption. The impacts of separation and different reaction parameters are also analyzed. This study demonstrates that the realization of TCES systems for CSP plants is contingent upon low storage cost and a reversible reaction with proper reaction properties.

Modeling the transport of chemical warfare agents and simulants in polymeric substrates for reactive decontamination

NASA Astrophysics Data System (ADS)

Pearl, Thomas; Mantooth, Brent; Varady, Mark; Willis, Matthew

2014-03-01

Chemical warfare agent simulants are often used for environmental testing in place of highly toxic agents. This work sets the foundation for modeling decontamination of absorbing polymeric materials with the focus on determining relationships between agents and simulants. The correlations of agents to simulants must consider the three way interactions in the chemical-material-decontaminant system where transport and reaction occur in polymer materials. To this end, diffusion modeling of the subsurface transport of simulants and live chemical warfare agents was conducted for various polymer systems (e.g., paint coatings) with and without reaction pathways with applied decontamination. The models utilized 1D and 2D finite difference diffusion and reaction models to simulate absorption and reaction in the polymers, and subsequent flux of the chemicals out of the polymers. Experimental data including vapor flux measurements and dynamic contact angle measurements were used to determine model input parameters. Through modeling, an understanding of the relationship of simulant to live chemical warfare agent was established, focusing on vapor emission of agents and simulants from materials.

Traveling wave to a reaction-hyperbolic system for axonal transport

NASA Astrophysics Data System (ADS)

Huang, Feimin; Li, Xing; Zhang, Yinglong

2017-07-01

In this paper, we study a class of nonlinear reaction-hyperbolic systems modeling the neuronal signal transfer in neuroscience. This reaction-hyperbolic system can be regarded as n × n (n ≥ 2) hyperbolic system with relaxation. We first prove the existence of traveling wave by Gershgorin circle theorem and mathematically describe the neuronal signal transport. Then for a special case n = 2, we show the traveling wave is nonlinearly stable, and obtain the convergence rate simultaneously by a weighted estimate.

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.

A computational approach to extinction events in chemical reaction networks with discrete state spaces.

PubMed

Johnston, Matthew D

2017-12-01

Recent work of Johnston et al. has produced sufficient conditions on the structure of a chemical reaction network which guarantee that the corresponding discrete state space system exhibits an extinction event. The conditions consist of a series of systems of equalities and inequalities on the edges of a modified reaction network called a domination-expanded reaction network. In this paper, we present a computational implementation of these conditions written in Python and apply the program on examples drawn from the biochemical literature. We also run the program on 458 models from the European Bioinformatics Institute's BioModels Database and report our results. Copyright © 2017 Elsevier Inc. All rights reserved.

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/

Modelling biochemical reaction systems by stochastic differential equations with reflection.

PubMed

Niu, Yuanling; Burrage, Kevin; Chen, Luonan

2016-05-07

In this paper, we gave a new framework for modelling and simulating biochemical reaction systems by stochastic differential equations with reflection not in a heuristic way but in a mathematical way. The model is computationally efficient compared with the discrete-state Markov chain approach, and it ensures that both analytic and numerical solutions remain in a biologically plausible region. Specifically, our model mathematically ensures that species numbers lie in the domain D, which is a physical constraint for biochemical reactions, in contrast to the previous models. The domain D is actually obtained according to the structure of the corresponding chemical Langevin equations, i.e., the boundary is inherent in the biochemical reaction system. A variant of projection method was employed to solve the reflected stochastic differential equation model, and it includes three simple steps, i.e., Euler-Maruyama method was applied to the equations first, and then check whether or not the point lies within the domain D, and if not perform an orthogonal projection. It is found that the projection onto the closure D¯ is the solution to a convex quadratic programming problem. Thus, existing methods for the convex quadratic programming problem can be employed for the orthogonal projection map. Numerical tests on several important problems in biological systems confirmed the efficiency and accuracy of this approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

LSENS, a general chemical kinetics and sensitivity analysis code for gas-phase reactions: User's guide

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Bittker, David A.

1993-01-01

A general chemical kinetics and sensitivity analysis code for complex, homogeneous, gas-phase reactions is described. The main features of the code, LSENS, are its flexibility, efficiency and convenience in treating many different chemical reaction models. The models include static system, steady, one-dimensional, inviscid flow, shock initiated reaction, and a perfectly stirred reactor. In addition, equilibrium computations can be performed for several assigned states. An implicit numerical integration method, which works efficiently for the extremes of very fast and very slow reaction, is used for solving the 'stiff' differential equation systems that arise in chemical kinetics. For static reactions, sensitivity coefficients of all dependent variables and their temporal derivatives with respect to the initial values of dependent variables and/or the rate coefficient parameters can be computed. This paper presents descriptions of the code and its usage, and includes several illustrative example problems.

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.

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.

Development and testing of a compartmentalized reaction network model for redox zones in contaminated aquifers

USGS Publications Warehouse

Abrams , Robert H.; Loague, Keith; Kent, Douglas B.

1998-01-01

The work reported here is the first part of a larger effort focused on efficient numerical simulation of redox zone development in contaminated aquifers. The sequential use of various electron acceptors, which is governed by the energy yield of each reaction, gives rise to redox zones. The large difference in energy yields between the various redox reactions leads to systems of equations that are extremely ill-conditioned. These equations are very difficult to solve, especially in the context of coupled fluid flow, solute transport, and geochemical simulations. We have developed a general, rational method to solve such systems where we focus on the dominant reactions, compartmentalizing them in a manner that is analogous to the redox zones that are often observed in the field. The compartmentalized approach allows us to easily solve a complex geochemical system as a function of time and energy yield, laying the foundation for our ongoing work in which we couple the reaction network, for the development of redox zones, to a model of subsurface fluid flow and solute transport. Our method (1) solves the numerical system without evoking a redox parameter, (2) improves the numerical stability of redox systems by choosing which compartment and thus which reaction network to use based upon the concentration ratios of key constituents, (3) simulates the development of redox zones as a function of time without the use of inhibition factors or switching functions, and (4) can reduce the number of transport equations that need to be solved in space and time. We show through the use of various model performance evaluation statistics that the appropriate compartment choice under different geochemical conditions leads to numerical solutions without significant error. The compartmentalized approach described here facilitates the next phase of this effort where we couple the redox zone reaction network to models of fluid flow and solute transport.

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.

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.

A master equation and moment approach for biochemical systems with creation-time-dependent bimolecular rate functions

PubMed Central

Chevalier, Michael W.; El-Samad, Hana

2014-01-01

Noise and stochasticity are fundamental to biology and derive from the very nature of biochemical reactions where thermal motion of molecules translates into randomness in the sequence and timing of reactions. This randomness leads to cell-to-cell variability even in clonal populations. Stochastic biochemical networks have been traditionally modeled as continuous-time discrete-state Markov processes whose probability density functions evolve according to a chemical master equation (CME). In diffusion reaction systems on membranes, the Markov formalism, which assumes constant reaction propensities is not directly appropriate. This is because the instantaneous propensity for a diffusion reaction to occur depends on the creation times of the molecules involved. In this work, we develop a chemical master equation for systems of this type. While this new CME is computationally intractable, we make rational dimensional reductions to form an approximate equation, whose moments are also derived and are shown to yield efficient, accurate results. This new framework forms a more general approach than the Markov CME and expands upon the realm of possible stochastic biochemical systems that can be efficiently modeled. PMID:25481130

A master equation and moment approach for biochemical systems with creation-time-dependent bimolecular rate functions

NASA Astrophysics Data System (ADS)

Chevalier, Michael W.; El-Samad, Hana

2014-12-01

Noise and stochasticity are fundamental to biology and derive from the very nature of biochemical reactions where thermal motion of molecules translates into randomness in the sequence and timing of reactions. This randomness leads to cell-to-cell variability even in clonal populations. Stochastic biochemical networks have been traditionally modeled as continuous-time discrete-state Markov processes whose probability density functions evolve according to a chemical master equation (CME). In diffusion reaction systems on membranes, the Markov formalism, which assumes constant reaction propensities is not directly appropriate. This is because the instantaneous propensity for a diffusion reaction to occur depends on the creation times of the molecules involved. In this work, we develop a chemical master equation for systems of this type. While this new CME is computationally intractable, we make rational dimensional reductions to form an approximate equation, whose moments are also derived and are shown to yield efficient, accurate results. This new framework forms a more general approach than the Markov CME and expands upon the realm of possible stochastic biochemical systems that can be efficiently modeled.

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.

Roles of different initial Maillard intermediates and pathways in meat flavor formation for cysteine-xylose-glycine model reaction systems.

PubMed

Hou, Li; Xie, Jianchun; Zhao, Jian; Zhao, Mengyao; Fan, Mengdie; Xiao, Qunfei; Liang, Jingjing; Chen, Feng

2017-10-01

To explore initial Maillard reaction pathways and mechanisms for maximal formation of meaty flavors in heated cysteine-xylose-glycine systems, model reactions with synthesized initial Maillard intermediates, Gly-Amadori, TTCA (2-threityl-thiazolidine-4-carboxylic acids) and Cys-Amadori, were investigated. Relative relativities were characterized by spectrophotometrically monitoring the development of colorless degradation intermediates and browning reaction products. Aroma compounds formed were determined by solid-phase microextraction combined with GC-MS and GC-olfactometry. Gly-Amadori showed the fastest reaction followed by Cys-Amadori then TTCA. Free glycine accelerated reaction of TTCA, whereas cysteine inhibited that of Gly-Amadori due to association forming relatively stable thiazolidines. Cys-Amadori/Gly had the highest reactivity in development of both meaty flavors and brown products. TTCA/Gly favored yielding meaty flavors, whereas Gly-Amadori/Cys favored generation of brown products. Conclusively, initial formation of TTCA and pathway involving TTCA with glycine were more applicable to efficiently produce processed-meat flavorings in a cysteine-xylose-glycine system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Water, Energy, and Biogeochemical Model (WEBMOD), user’s manual, version 1

USGS Publications Warehouse

Webb, Richard M.T.; Parkhurst, David L.

2017-02-08

The Water, Energy, and Biogeochemical Model (WEBMOD) uses the framework of the U.S. Geological Survey (USGS) Modular Modeling System to simulate fluxes of water and solutes through watersheds. WEBMOD divides watersheds into model response units (MRU) where fluxes and reactions are simulated for the following eight hillslope reservoir types: canopy; snowpack; ponding on impervious surfaces; O-horizon; two reservoirs in the unsaturated zone, which represent preferential flow and matrix flow; and two reservoirs in the saturated zone, which also represent preferential flow and matrix flow. The reservoir representing ponding on impervious surfaces, currently not functional (2016), will be implemented once the model is applied to urban areas. MRUs discharge to one or more stream reservoirs that flow to the outlet of the watershed. Hydrologic fluxes in the watershed are simulated by modules derived from the USGS Precipitation Runoff Modeling System; the National Weather Service Hydro-17 snow model; and a topography-driven hydrologic model (TOPMODEL). Modifications to the standard TOPMODEL include the addition of heterogeneous vertical infiltration rates; irrigation; lateral and vertical preferential flows through the unsaturated zone; pipe flow draining the saturated zone; gains and losses to regional aquifer systems; and the option to simulate baseflow discharge by using an exponential, parabolic, or linear decrease in transmissivity. PHREEQC, an aqueous geochemical model, is incorporated to simulate chemical reactions as waters evaporate, mix, and react within the various reservoirs of the model. The reactions that can be specified for a reservoir include equilibrium reactions among water; minerals; surfaces; exchangers; and kinetic reactions such as kinetic mineral dissolution or precipitation, biologically mediated reactions, and radioactive decay. WEBMOD also simulates variations in the concentrations of the stable isotopes deuterium and oxygen-18 as a result of varying inputs, mixing, and evaporation. This manual describes the WEBMOD input and output files, along with the algorithms and procedures used to simulate the hydrology and water quality in a watershed. Examples are presented that demonstrate hydrologic processes, weathering reactions, and isotopic evolution in an alpine watershed and the effect of irrigation on water flows and salinity in an intensively farmed agricultural area.

Forward design of a complex enzyme cascade reaction

PubMed Central

Hold, Christoph; Billerbeck, Sonja; Panke, Sven

2016-01-01

Enzymatic reaction networks are unique in that one can operate a large number of reactions under the same set of conditions concomitantly in one pot, but the nonlinear kinetics of the enzymes and the resulting system complexity have so far defeated rational design processes for the construction of such complex cascade reactions. Here we demonstrate the forward design of an in vitro 10-membered system using enzymes from highly regulated biological processes such as glycolysis. For this, we adapt the characterization of the biochemical system to the needs of classical engineering systems theory: we combine online mass spectrometry and continuous system operation to apply standard system theory input functions and to use the detailed dynamic system responses to parameterize a model of sufficient quality for forward design. This allows the facile optimization of a 10-enzyme cascade reaction for fine chemical production purposes. PMID:27677244

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.

Multi-scale modeling of diffusion-controlled reactions in polymers: renormalisation of reactivity parameters.

PubMed

Everaers, Ralf; Rosa, Angelo

2012-01-07

The quantitative description of polymeric systems requires hierarchical modeling schemes, which bridge the gap between the atomic scale, relevant to chemical or biomolecular reactions, and the macromolecular scale, where the longest relaxation modes occur. Here, we use the formalism for diffusion-controlled reactions in polymers developed by Wilemski, Fixman, and Doi to discuss the renormalisation of the reactivity parameters in polymer models with varying spatial resolution. In particular, we show that the adjustments are independent of chain length. As a consequence, it is possible to match reactions times between descriptions with different resolution for relatively short reference chains and to use the coarse-grained model to make quantitative predictions for longer chains. We illustrate our results by a detailed discussion of the classical problem of chain cyclization in the Rouse model, which offers the simplest example of a multi-scale descriptions, if we consider differently discretized Rouse models for the same physical system. Moreover, we are able to explore different combinations of compact and non-compact diffusion in the local and large-scale dynamics by varying the embedding dimension.

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.

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

Coupled alkali feldspar dissolution and secondary mineral precipitation in batch systems: 4. Numerical modeling of kinetic reaction paths

NASA Astrophysics Data System (ADS)

Zhu, Chen; Lu, Peng; Zheng, Zuoping; Ganor, Jiwchar

2010-07-01

This paper explores how dissolution and precipitation reactions are coupled in batch reactor experimental systems at elevated temperatures. This is the fourth paper in our series of "Coupled Alkali Feldspar Dissolution and Secondary Mineral Precipitation in Batch Systems". In our third paper, we demonstrated via speciation-solubility modeling that partial equilibrium between secondary minerals and aqueous solutions was not attained in feldspar hydrolysis batch reactors at 90-300 °C and that a strong coupling between dissolution and precipitation reactions follows as a consequence of the slower precipitation of secondary minerals ( Zhu and Lu, 2009). Here, we develop this concept further by using numerical reaction path models to elucidate how the dissolution and precipitation reactions are coupled. Modeling results show that a quasi-steady state was reached. At the quasi-steady state, dissolution reactions proceeded at rates that are orders of magnitude slower than the rates measured at far from equilibrium. The quasi-steady state is determined by the relative rate constants, and strongly influenced by the function of Gibbs free energy of reaction ( ΔG) in the rate laws. To explore the potential effects of fluid flow rates on the coupling of reactions, we extrapolate a batch system ( Ganor et al., 2007) to open systems and simulated one-dimensional reactive mass transport for oligoclase dissolution and kaolinite precipitation in homogeneous porous media. Different steady states were achieved at different locations along the one-dimensional domain. The time-space distribution and saturation indices (SI) at the steady states were a function of flow rates for a given kinetic model. Regardless of the differences in SI, the ratio between oligoclase dissolution rates and kaolinite precipitation rates remained 1.626, as in the batch system case ( Ganor et al., 2007). Therefore, our simulation results demonstrated coupling among dissolution, precipitation, and flow rates. Results reported in this communication lend support to our hypothesis that slow secondary mineral precipitation explains part of the well-known apparent discrepancy between lab measured and field estimated feldspar dissolution rates ( Zhu et al., 2004). Here we show how the slow secondary mineral precipitation provides a regulator to explain why the systems are held close to equilibrium and show how the most often-quoted "near equilibrium" explanation for an apparent field-lab discrepancy can work quantitatively. The substantiated hypothesis now offers the promise of reconciling part of the apparent field-lab discrepancy.

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.

Indistinguishability and identifiability of kinetic models for the MurC reaction in peptidoglycan biosynthesis.

PubMed

Hattersley, J G; Pérez-Velázquez, J; Chappell, M J; Bearup, D; Roper, D; Dowson, C; Bugg, T; Evans, N D

2011-11-01

An important question in Systems Biology is the design of experiments that enable discrimination between two (or more) competing chemical pathway models or biological mechanisms. In this paper analysis is performed between two different models describing the kinetic mechanism of a three-substrate three-product reaction, namely the MurC reaction in the cytoplasmic phase of peptidoglycan biosynthesis. One model involves ordered substrate binding and ordered release of the three products; the competing model also assumes ordered substrate binding, but with fast release of the three products. The two versions are shown to be distinguishable; however, if standard quasi-steady-state assumptions are made distinguishability cannot be determined. Once model structure uniqueness is ensured the experimenter must determine if it is possible to successfully recover rate constant values given the experiment observations, a process known as structural identifiability. Structural identifiability analysis is carried out for both models to determine which of the unknown reaction parameters can be determined uniquely, or otherwise, from the ideal system outputs. This structural analysis forms an integrated step towards the modelling of the full pathway of the cytoplasmic phase of peptidoglycan biosynthesis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Robotic reactions: delay-induced patterns in autonomous vehicle systems.

PubMed

Orosz, Gábor; Moehlis, Jeff; Bullo, Francesco

2010-02-01

Fundamental design principles are presented for vehicle systems governed by autonomous cruise control devices. By analyzing the corresponding delay differential equations, it is shown that for any car-following model short-wavelength oscillations can appear due to robotic reaction times, and that there are tradeoffs between the time delay and the control gains. The analytical findings are demonstrated on an optimal velocity model using numerical continuation and numerical simulation.

Robotic reactions: Delay-induced patterns in autonomous vehicle systems

NASA Astrophysics Data System (ADS)

Orosz, Gábor; Moehlis, Jeff; Bullo, Francesco

2010-02-01

Fundamental design principles are presented for vehicle systems governed by autonomous cruise control devices. By analyzing the corresponding delay differential equations, it is shown that for any car-following model short-wavelength oscillations can appear due to robotic reaction times, and that there are tradeoffs between the time delay and the control gains. The analytical findings are demonstrated on an optimal velocity model using numerical continuation and numerical simulation.

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.

Multi-variable mathematical models for the air-cathode microbial fuel cell system

DOE PAGES

Ou, Shiqi; Kashima, Hiroyuki; Aaron, Douglas S.; ...

2016-03-10

This research adopted the version control system into the model construction for the single chamber air-cathode microbial fuel cell (MFC) system, to understand the interrelation of biological, chemical, and electrochemical reactions. The anodic steady state model was used to consider the chemical species diffusion and electric migration influence to the MFC performance. In the cathodic steady state model, the mass transport and reactions in a multi-layer, abiotic cathode and multi-bacteria cathode biofilm were simulated. Transport of hydroxide was assumed for cathodic pH change. This assumption is an alternative to the typical notion of proton consumption during oxygen reduction to explainmore » elevated cathode pH. The cathodic steady state model provided the power density and polarization curve performance results that can be compared to an experimental MFC system. Another aspect we considered was the relative contributions of platinum catalyst and microbes on the cathode to the oxygen reduction reaction (ORR). We found simulation results showed that the biocatalyst in a cathode that includes a Pt/C catalyst likely plays a minor role in ORR, contributing up to 8% of the total power calculated by the models.« less

Theory of bimolecular reactions in a solution with linear traps: Application to the problem of target search on DNA.

PubMed

Turkin, Alexander; van Oijen, Antoine M; Turkin, Anatoliy A

2015-01-01

One-dimensional sliding along DNA as a means to accelerate protein target search is a well-known phenomenon occurring in various biological systems. Using a biomimetic approach, we have recently demonstrated the practical use of DNA-sliding peptides to speed up bimolecular reactions more than an order of magnitude by allowing the reactants to associate not only in the solution by three-dimensional (3D) diffusion, but also on DNA via one-dimensional (1D) diffusion [A. Turkin et al., Chem. Sci. (2015)]. Here we present a mean-field kinetic model of a bimolecular reaction in a solution with linear extended sinks (e.g., DNA) that can intermittently trap molecules present in a solution. The model consists of chemical rate equations for mean concentrations of reacting species. Our model demonstrates that addition of linear traps to the solution can significantly accelerate reactant association. We show that at optimum concentrations of linear traps the 1D reaction pathway dominates in the kinetics of the bimolecular reaction; i.e., these 1D traps function as an assembly line of the reaction product. Moreover, we show that the association reaction on linear sinks between trapped reactants exhibits a nonclassical third-order behavior. Predictions of the model agree well with our experimental observations. Our model provides a general description of bimolecular reactions that are controlled by a combined 3D+1D mechanism and can be used to quantitatively describe both naturally occurring as well as biomimetic biochemical systems that reduce the dimensionality of search.

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.

Light charged particle multiplicities in fusion and quasifission reactions

NASA Astrophysics Data System (ADS)

Kalandarov, Sh. A.; Adamian, G. G.; Antonenko, N. V.; Lacroix, D.; Wieleczko, J. P.

2018-01-01

The light charged particle evaporation from the compound nucleus and from the complex fragments in the reactions 32S+100Mo, 121Sb+27Al, 40Ar+164Dy, and 40Ar+ nat Ag is studied within the dinuclear system model. The possibility to distinguish the reaction products from different reaction mechanisms is discussed.

Hybrid discrete/continuum algorithms for stochastic reaction networks

DOE PAGES

Safta, Cosmin; Sargsyan, Khachik; Debusschere, Bert; ...

2014-10-22

Direct solutions of the Chemical Master Equation (CME) governing Stochastic Reaction Networks (SRNs) are generally prohibitively expensive due to excessive numbers of possible discrete states in such systems. To enhance computational efficiency we develop a hybrid approach where the evolution of states with low molecule counts is treated with the discrete CME model while that of states with large molecule counts is modeled by the continuum Fokker-Planck equation. The Fokker-Planck equation is discretized using a 2nd order finite volume approach with appropriate treatment of flux components to avoid negative probability values. The numerical construction at the interface between the discretemore » and continuum regions implements the transfer of probability reaction by reaction according to the stoichiometry of the system. As a result, the performance of this novel hybrid approach is explored for a two-species circadian model with computational efficiency gains of about one order of magnitude.« less

Simulations of Living Cell Origins Using a Cellular Automata Model

NASA Astrophysics Data System (ADS)

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Simulations of living cell origins using a cellular automata model.

PubMed

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

PubMed

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

2017-10-03

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Genome scale metabolic reconstruction of Chlorella variabilis for exploring its metabolic potential for biofuels.

PubMed

Juneja, Ankita; Chaplen, Frank W R; Murthy, Ganti S

2016-08-01

A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. This reconstructed metabolic network will serve an important role in systems biology for further exploration of metabolism for specific target metabolites and enable improved characteristics in the strain through metabolic engineering. Copyright © 2016 Elsevier Ltd. All rights reserved.

[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.

Direct Monte Carlo simulation of chemical reaction systems: Simple bimolecular reactions

NASA Astrophysics Data System (ADS)

Piersall, Shannon D.; Anderson, James B.

1991-07-01

In applications to several simple reaction systems we have explored a ``direct simulation'' method for predicting and understanding the behavior of gas phase chemical reaction systems. This Monte Carlo method, originated by Bird, has been found remarkably successful in treating a number of difficult problems in rarefied dynamics. Extension to chemical reactions offers a powerful tool for treating reaction systems with nonthermal distributions, with coupled gas-dynamic and reaction effects, with emission and adsorption of radiation, and with many other effects difficult to treat in any other way. The usual differential equations of chemical kinetics are eliminated. For a bimolecular reaction of the type A+B→C+D with a rate sufficiently low to allow a continued thermal equilibrium of reactants we find that direct simulation reproduces the expected second order kinetics. Simulations for a range of temperatures yield the activation energies expected for the reaction models specified. For faster reactions under conditions leading to a depletion of energetic reactant species, the expected slowing of reaction rates and departures from equilibrium distributions are observed. The minimum sample sizes required for adequate simulations are as low as 1000 molecules for these cases. The calculations are found to be simple and straightforward for the homogeneous systems considered. Although computation requirements may be excessively high for very slow reactions, they are reasonably low for fast reactions, for which nonequilibrium effects are most important.

Simulation of anaerobic digestion processes using stochastic algorithm.

PubMed

Palanichamy, Jegathambal; Palani, Sundarambal

2014-01-01

The Anaerobic Digestion (AD) processes involve numerous complex biological and chemical reactions occurring simultaneously. Appropriate and efficient models are to be developed for simulation of anaerobic digestion systems. Although several models have been developed, mostly they suffer from lack of knowledge on constants, complexity and weak generalization. The basis of the deterministic approach for modelling the physico and bio-chemical reactions occurring in the AD system is the law of mass action, which gives the simple relationship between the reaction rates and the species concentrations. The assumptions made in the deterministic models are not hold true for the reactions involving chemical species of low concentration. The stochastic behaviour of the physicochemical processes can be modeled at mesoscopic level by application of the stochastic algorithms. In this paper a stochastic algorithm (Gillespie Tau Leap Method) developed in MATLAB was applied to predict the concentration of glucose, acids and methane formation at different time intervals. By this the performance of the digester system can be controlled. The processes given by ADM1 (Anaerobic Digestion Model 1) were taken for verification of the model. The proposed model was verified by comparing the results of Gillespie's algorithms with the deterministic solution for conversion of glucose into methane through degraders. At higher value of 'τ' (timestep), the computational time required for reaching the steady state is more since the number of chosen reactions is less. When the simulation time step is reduced, the results are similar to ODE solver. It was concluded that the stochastic algorithm is a suitable approach for the simulation of complex anaerobic digestion processes. The accuracy of the results depends on the optimum selection of tau value.

The Effects of Intrinsic Noise on an Inhomogeneous Lattice of Chemical Oscillators

NASA Astrophysics Data System (ADS)

Giver, Michael; Jabeen, Zahera; Chakraborty, Bulbul

2012-02-01

Intrinsic or demographic noise has been shown to play an important role in the dynamics of a variety of systems including biochemical reactions within cells, predator-prey populations, and oscillatory chemical reaction systems, and is known to give rise to oscillations and pattern formation well outside the parameter range predicted by standard mean-field analysis. Motivated by an experimental model of cells and tissues where the cells are represented by chemical reagents isolated in emulsion droplets, we study the stochastic Brusselator, a simple activator-inhibitor chemical reaction model. Our work extends the results of recent studies on the zero and one dimensional system to the case of a non-uniform one dimensional lattice using a combination of analytical techniques and Monte Carlo simulations.

Spins of complex fragments in binary reactions within a dinuclear system model

NASA Astrophysics Data System (ADS)

Paşca, H.; Kalandarov, Sh. A.; Adamian, G. G.; Antonenko, N. V.

2017-10-01

The average angular momenta and widths of the spin distributions of reaction products are calculated within the dinuclear system model. The thermal excitation of rotational bearing modes is considered in the dinuclear system. The calculated fragment spins (γ multiplicities) and their variances in the reactions 20Ne (166 MeV) + 63Cu, 40Ar (280 MeV) + 58Ni, 20Ne (175 MeV) + natAg, 40Ar (237 MeV) + 89Y, 40Ar (288 and 340 MeV) + Ag,109107, and 16O (100 MeV) + 58Ni are compared with the available experimental data. The influence of the entrance channel charge (mass) asymmetry and bombarding energy on the characteristics of spin distribution is studied.

A hybrid approach to simulation of electron transfer in complex molecular systems

PubMed Central

Kubař, Tomáš; Elstner, Marcus

2013-01-01

Electron transfer (ET) reactions in biomolecular systems represent an important class of processes at the interface of physics, chemistry and biology. The theoretical description of these reactions constitutes a huge challenge because extensive systems require a quantum-mechanical treatment and a broad range of time scales are involved. Thus, only small model systems may be investigated with the modern density functional theory techniques combined with non-adiabatic dynamics algorithms. On the other hand, model calculations based on Marcus's seminal theory describe the ET involving several assumptions that may not always be met. We review a multi-scale method that combines a non-adiabatic propagation scheme and a linear scaling quantum-chemical method with a molecular mechanics force field in such a way that an unbiased description of the dynamics of excess electron is achieved and the number of degrees of freedom is reduced effectively at the same time. ET reactions taking nanoseconds in systems with hundreds of quantum atoms can be simulated, bridging the gap between non-adiabatic ab initio simulations and model approaches such as the Marcus theory. A major recent application is hole transfer in DNA, which represents an archetypal ET reaction in a polarizable medium. Ongoing work focuses on hole transfer in proteins, peptides and organic semi-conductors. PMID:23883952

A parallel reaction-transport model applied to cement hydration and microstructure development

NASA Astrophysics Data System (ADS)

Bullard, Jeffrey W.; Enjolras, Edith; George, William L.; Satterfield, Steven G.; Terrill, Judith E.

2010-03-01

A recently described stochastic reaction-transport model on three-dimensional lattices is parallelized and is used to simulate the time-dependent structural and chemical evolution in multicomponent reactive systems. The model, called HydratiCA, uses probabilistic rules to simulate the kinetics of diffusion, homogeneous reactions and heterogeneous phenomena such as solid nucleation, growth and dissolution in complex three-dimensional systems. The algorithms require information only from each lattice site and its immediate neighbors, and this localization enables the parallelized model to exhibit near-linear scaling up to several hundred processors. Although applicable to a wide range of material systems, including sedimentary rock beds, reacting colloids and biochemical systems, validation is performed here on two minerals that are commonly found in Portland cement paste, calcium hydroxide and ettringite, by comparing their simulated dissolution or precipitation rates far from equilibrium to standard rate equations, and also by comparing simulated equilibrium states to thermodynamic calculations, as a function of temperature and pH. Finally, we demonstrate how HydratiCA can be used to investigate microstructure characteristics, such as spatial correlations between different condensed phases, in more complex microstructures.

Canards and black swans in a model of a 3-D autocatalator

NASA Astrophysics Data System (ADS)

Shchepakina, E.

2005-01-01

The mathematical model of a 3-D autocatalator is studied using the geometric theory of singular perturbations, namely, the black swan and canard techniques. Critical regimes are modeled by canards (one-dimensional stable-unstable slow integral manifolds). The meaning of criticality here is as follows. The critical regime corresponds to a chemical reaction which separates the domain of self-accelerating reactions from the domain of slow reactions. A two-dimensional stable-unstable slow integral manifold (black swan) consisting entirely of canards, which simulate the critical phenomena for different initial data of the dynamical system, is constructed. It is shown that this procedure leads to the phenomenon of auto-oscillations in the chemical system. The geometric approach combined with asymptotic and numerical methods permits us to explain the strong parametric sensitivity and to obtain asymptotic representations of the critical behavior of the chemical system.

Modelling chemical reactions by QM/MM calculations: the case of the tautomerization in fireflies bioluminescent systems

NASA Astrophysics Data System (ADS)

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-04-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modelling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Modeling Chemical Reactions by QM/MM Calculations: The Case of the Tautomerization in Fireflies Bioluminescent Systems

PubMed Central

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-01-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modeling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods. PMID:29719820

Reaction-diffusion systems and external morphogen gradients: the two-dimensional case, with an application to skeletal pattern formation.

PubMed

Glimm, Tilmann; Zhang, Jianying; Shen, Yun-Qiu; Newman, Stuart A

2012-03-01

We investigate a reaction-diffusion system consisting of an activator and an inhibitor in a two-dimensional domain. There is a morphogen gradient in the domain. The production of the activator depends on the concentration of the morphogen. Mathematically, this leads to reaction-diffusion equations with explicitly space-dependent terms. It is well known that in the absence of an external morphogen, the system can produce either spots or stripes via the Turing bifurcation. We derive first-order expansions for the possible patterns in the presence of an external morphogen and show how both stripes and spots are affected. This work generalizes previous one-dimensional results to two dimensions. Specifically, we consider the quasi-one-dimensional case of a thin rectangular domain and the case of a square domain. We apply the results to a model of skeletal pattern formation in vertebrate limbs. In the framework of reaction-diffusion models, our results suggest a simple explanation for some recent experimental findings in the mouse limb which are much harder to explain in positional-information-type models.

Modeling Chemical Reactions by QM/MM Calculations: The Case of the Tautomerization in Fireflies Bioluminescent Systems.

PubMed

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-01-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modeling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Uncovering Oscillations, Complexity, and Chaos in Chemical Kinetics Using Mathematica

NASA Astrophysics Data System (ADS)

Ferreira, M. M. C.; Ferreira, W. C., Jr.; Lino, A. C. S.; Porto, M. E. G.

1999-06-01

Unlike reactions with no peculiar temporal behavior, in oscillatory reactions concentrations can rise and fall spontaneously in a cyclic or disorganized fashion. In this article, the software Mathematica is used for a theoretical study of kinetic mechanisms of oscillating and chaotic reactions. A first simple example is introduced through a three-step reaction, called the Lotka model, which exhibits a temporal behavior characterized by damped oscillations. The phase plane method of dynamic systems theory is introduced for a geometric interpretation of the reaction kinetics without solving the differential rate equations. The equations are later numerically solved using the built-in routine NDSolve and the results are plotted. The next example, still with a very simple mechanism, is the Lotka-Volterra model reaction, which oscillates indefinitely. The kinetic process and rate equations are also represented by a three-step reaction mechanism. The most important difference between this and the former reaction is that the undamped oscillation has two autocatalytic steps instead of one. The periods of oscillations are obtained by using the discrete Fourier transform (DFT)-a well-known tool in spectroscopy, although not so common in this context. In the last section, it is shown how a simple model of biochemical interactions can be useful to understand the complex behavior of important biological systems. The model consists of two allosteric enzymes coupled in series and activated by its own products. This reaction scheme is important for explaining many metabolic mechanisms, such as the glycolytic oscillations in muscles, yeast glycolysis, and the periodic synthesis of cyclic AMP. A few of many possible dynamic behaviors are exemplified through a prototype glycolytic enzymatic reaction proposed by Decroly and Goldbeter. By simply modifying the initial concentrations, limit cycles, chaos, and birhythmicity are computationally obtained and visualized.

Hypothesized diprotomeric enzyme complex supported by stochastic modelling of palytoxin-induced Na/K pump channels

PubMed Central

Vilallonga, Gabriel D.; de Almeida, Antônio-Carlos G.; Ribeiro, Kelison T.; Campos, Sergio V. A.

2018-01-01

The sodium–potassium pump (Na+/K+ pump) is crucial for cell physiology. Despite great advances in the understanding of this ionic pumping system, its mechanism is not completely understood. We propose the use of a statistical model checker to investigate palytoxin (PTX)-induced Na+/K+ pump channels. We modelled a system of reactions representing transitions between the conformational substates of the channel with parameters, concentrations of the substates and reaction rates extracted from simulations reported in the literature, based on electrophysiological recordings in a whole-cell configuration. The model was implemented using the UPPAAL-SMC platform. Comparing simulations and probabilistic queries from stochastic system semantics with experimental data, it was possible to propose additional reactions to reproduce the single-channel dynamic. The probabilistic analyses and simulations suggest that the PTX-induced Na+/K+ pump channel functions as a diprotomeric complex in which protein–protein interactions increase the affinity of the Na+/K+ pump for PTX. PMID:29657808

A Networks Approach to Modeling Enzymatic Reactions.

PubMed

Imhof, P

2016-01-01

Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

Nonlinear electromechanical modelling and dynamical behavior analysis of a satellite reaction wheel

NASA Astrophysics Data System (ADS)

Aghalari, Alireza; Shahravi, Morteza

2017-12-01

The present research addresses the satellite reaction wheel (RW) nonlinear electromechanical coupling dynamics including dynamic eccentricity of brushless dc (BLDC) motor and gyroscopic effects, as well as dry friction of shaft-bearing joints (relative small slip) and bearing friction. In contrast to other studies, the rotational velocity of the flywheel is considered to be controllable, so it is possible to study the reaction wheel dynamical behavior in acceleration stages. The RW is modeled as a three-phases BLDC motor as well as flywheel with unbalances on a rigid shaft and flexible bearings. Improved Lagrangian dynamics for electromechanical systems is used to obtain the mathematical model of the system. The developed model can properly describe electromechanical nonlinear coupled dynamical behavior of the satellite RW. Numerical simulations show the effectiveness of the presented approach.

THE INFLUENCE OF MINERAL REACTIONS ON THE ENVIRONMENTAL FATE OF METALS IN SOILS AND SEDIMENTS

EPA Science Inventory

Significant progress has been made in elucidating sorption reactions that control the partitioning of metals from solution to mineral surfaces in contaminated soil/sediment systems. Surface complexation models have been developed to quantify the forward reaction, however, these ...

Petri Nets - A Mathematical Formalism to Analyze Chemical Reaction Networks.

PubMed

Koch, Ina

2010-12-17

In this review we introduce and discuss Petri nets - a mathematical formalism to describe and analyze chemical reaction networks. Petri nets were developed to describe concurrency in general systems. We find most applications to technical and financial systems, but since about twenty years also in systems biology to model biochemical systems. This review aims to give a short informal introduction to the basic formalism illustrated by a chemical example, and to discuss possible applications to the analysis of chemical reaction networks, including cheminformatics. We give a short overview about qualitative as well as quantitative modeling Petri net techniques useful in systems biology, summarizing the state-of-the-art in that field and providing the main literature references. Finally, we discuss advantages and limitations of Petri nets and give an outlook to further development. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Attitude control study for a large flexible spacecraft using a Solar Electric Propulsion System (SEPS)

NASA Technical Reports Server (NTRS)

Tolivar, A. F.; Key, R. W.

1980-01-01

The attitude control performance of the solar electric propulsion system (SEPS) was evaluated. A thrust vector control system for powered flight control was examined along with a gas jet reaction control system, and a reaction wheel system, both of which have been proposed for nonpowered flight control. Comprehensive computer simulations of each control system were made and evaluated using a 30 mode spacecraft model. Results obtained indicate that thrust vector control and reaction wheel systems offer acceptable smooth proportional control. The gas jet control system is shown to be risky for a flexible structure such as SEPS, and is therefore, not recommended as a primary control method.

Committor of elementary reactions on multistate systems

NASA Astrophysics Data System (ADS)

Király, Péter; Kiss, Dóra Judit; Tóth, Gergely

2018-04-01

In our study, we extend the committor concept on multi-minima systems, where more than one reaction may proceed, but the feasible data evaluation needs the projection onto partial reactions. The elementary reaction committor and the corresponding probability density of the reactive trajectories are defined and calculated on a three-hole two-dimensional model system explored by single-particle Langevin dynamics. We propose a method to visualize more elementary reaction committor functions or probability densities of reactive trajectories on a single plot that helps to identify the most important reaction channels and the nonreactive domains simultaneously. We suggest a weighting for the energy-committor plots that correctly shows the limits of both the minimal energy path and the average energy concepts. The methods also performed well on the analysis of molecular dynamics trajectories of 2-chlorobutane, where an elementary reaction committor, the probability densities, the potential energy/committor, and the free-energy/committor curves are presented.

New Approach for Nuclear Reaction Model in the Combination of Intra-nuclear Cascade and DWBA

NASA Astrophysics Data System (ADS)

Hashimoto, S.; Iwamoto, O.; Iwamoto, Y.; Sato, T.; Niita, K.

2014-04-01

We applied a new nuclear reaction model that is a combination of the intra nuclear cascade model and the distorted wave Born approximation (DWBA) calculation to estimate neutron spectra in reactions induced by protons incident on 7Li and 9Be targets at incident energies below 50 MeV, using the particle and heavy ion transport code system (PHITS). The results obtained by PHITS with the new model reproduce the sharp peaks observed in the experimental double-differential cross sections as a result of taking into account transitions between discrete nuclear states in the DWBA. An excellent agreement was observed between the calculated results obtained using the combination model and experimental data on neutron yields from thick targets in the inclusive (p, xn) reaction.

The general theory of multistage geminate reactions of isolated pairs of reactants. III. Two-stage reversible dissociation in geminate reaction A + A ↔ C ↔ B + B.

PubMed

Kipriyanov, Alexey A; Kipriyanov, Alexander A; Doktorov, Alexander B

2016-04-14

Specific two-stage reversible reaction A + A ↔ C ↔ B + B of the decay of species C reactants by two independent transition channels is considered on the basis of the general theory of multistage reactions of isolated pairs of reactants. It is assumed that at the initial instant of time, the reacting system contains only reactants C. The employed general approach has made it possible to consider, in the general case, the inhomogeneous initial distribution of reactants, and avoid application of model concepts of a reaction system structure (i.e., of the structure of reactants and their molecular mobility). Slowing of multistage reaction kinetics as compared to the kinetics of elementary stages is established and physically interpreted. To test approximations (point approximation) used to develop a universal kinetic law, a widely employed specific model of spherical particles with isotropic reactivity diffusing in solution is applied. With this particular model as an example, ultimate kinetics of chemical conversion of reactants is investigated. The question concerning the depths of chemical transformation at which long-term asymptotes are reached is studied.

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.

EVALUATING THE SENSITIVITY OF A SUBSURFACE MULTICOMPONENT REACTIVE TRANSPORT MODEL WITH RESPECT TO TRANSPORT AND REACTION PARAMETERS

EPA Science Inventory

The input variables for a numerical model of reactive solute transport in groundwater include both transport parameters, such as hydraulic conductivity and infiltration, and reaction parameters that describe the important chemical and biological processes in the system. These pa...

RuleMonkey: software for stochastic simulation of rule-based models

PubMed Central

2010-01-01

Background The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems. Results Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods. Conclusions RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application http://public.tgen.org/rulemonkey. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models. PMID:20673321

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

A master equation and moment approach for biochemical systems with creation-time-dependent bimolecular rate functions

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

Chevalier, Michael W., E-mail: Michael.Chevalier@ucsf.edu; El-Samad, Hana, E-mail: Hana.El-Samad@ucsf.edu

Noise and stochasticity are fundamental to biology and derive from the very nature of biochemical reactions where thermal motion of molecules translates into randomness in the sequence and timing of reactions. This randomness leads to cell-to-cell variability even in clonal populations. Stochastic biochemical networks have been traditionally modeled as continuous-time discrete-state Markov processes whose probability density functions evolve according to a chemical master equation (CME). In diffusion reaction systems on membranes, the Markov formalism, which assumes constant reaction propensities is not directly appropriate. This is because the instantaneous propensity for a diffusion reaction to occur depends on the creation timesmore » of the molecules involved. In this work, we develop a chemical master equation for systems of this type. While this new CME is computationally intractable, we make rational dimensional reductions to form an approximate equation, whose moments are also derived and are shown to yield efficient, accurate results. This new framework forms a more general approach than the Markov CME and expands upon the realm of possible stochastic biochemical systems that can be efficiently modeled.« less

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.

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

Marinov, N.M.; Westbrook, C.K.; Cloutman, L.D.

Work being carried out at LLNL has concentrated on studies of the role of chemical kinetics in a variety of problems related to hydrogen combustion in practical combustion systems, with an emphasis on vehicle propulsion. Use of hydrogen offers significant advantages over fossil fuels, and computer modeling provides advantages when used in concert with experimental studies. Many numerical {open_quotes}experiments{close_quotes} can be carried out quickly and efficiently, reducing the cost and time of system development, and many new and speculative concepts can be screened to identify those with sufficient promise to pursue experimentally. This project uses chemical kinetic and fluid dynamicmore » computational modeling to examine the combustion characteristics of systems burning hydrogen, either as the only fuel or mixed with natural gas. Oxidation kinetics are combined with pollutant formation kinetics, including formation of oxides of nitrogen but also including air toxics in natural gas combustion. We have refined many of the elementary kinetic reaction steps in the detailed reaction mechanism for hydrogen oxidation. To extend the model to pressures characteristic of internal combustion engines, it was necessary to apply theoretical pressure falloff formalisms for several key steps in the reaction mechanism. We have continued development of simplified reaction mechanisms for hydrogen oxidation, we have implemented those mechanisms into multidimensional computational fluid dynamics models, and we have used models of chemistry and fluid dynamics to address selected application problems. At the present time, we are using computed high pressure flame, and auto-ignition data to further refine the simplified kinetics models that are then to be used in multidimensional fluid mechanics models. Detailed kinetics studies have investigated hydrogen flames and ignition of hydrogen behind shock waves, intended to refine the detailed reactions mechanisms.« less

On the deduction of chemical reaction pathways from measurements of time series of concentrations.

PubMed

Samoilov, Michael; Arkin, Adam; Ross, John

2001-03-01

We discuss the deduction of reaction pathways in complex chemical systems from measurements of time series of chemical concentrations of reacting species. First we review a technique called correlation metric construction (CMC) and show the construction of a reaction pathway from measurements on a part of glycolysis. Then we present two new improved methods for the analysis of time series of concentrations, entropy metric construction (EMC), and entropy reduction method (ERM), and illustrate (EMC) with calculations on a model reaction system. (c) 2001 American Institute of Physics.

Turing instability in reaction-diffusion systems with nonlinear diffusion

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

Zemskov, E. P., E-mail: zemskov@ccas.ru

2013-10-15

The Turing instability is studied in two-component reaction-diffusion systems with nonlinear diffusion terms, and the regions in parametric space where Turing patterns can form are determined. The boundaries between super- and subcritical bifurcations are found. Calculations are performed for one-dimensional brusselator and oregonator models.

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

Computational analysis of the roles of biochemical reactions in anomalous diffusion dynamics

NASA Astrophysics Data System (ADS)

Naruemon, Rueangkham; Charin, Modchang

2016-04-01

Most biochemical processes in cells are usually modeled by reaction-diffusion (RD) equations. In these RD models, the diffusive process is assumed to be Gaussian. However, a growing number of studies have noted that intracellular diffusion is anomalous at some or all times, which may result from a crowded environment and chemical kinetics. This work aims to computationally study the effects of chemical reactions on the diffusive dynamics of RD systems by using both stochastic and deterministic algorithms. Numerical method to estimate the mean-square displacement (MSD) from a deterministic algorithm is also investigated. Our computational results show that anomalous diffusion can be solely due to chemical reactions. The chemical reactions alone can cause anomalous sub-diffusion in the RD system at some or all times. The time-dependent anomalous diffusion exponent is found to depend on many parameters, including chemical reaction rates, reaction orders, and chemical concentrations. Project supported by the Thailand Research Fund and Mahidol University (Grant No. TRG5880157), the Thailand Center of Excellence in Physics (ThEP), CHE, Thailand, and the Development Promotion of Science and Technology.

An efficient hybrid method for stochastic reaction-diffusion biochemical systems with delay

NASA Astrophysics Data System (ADS)

Sayyidmousavi, Alireza; Ilie, Silvana

2017-12-01

Many chemical reactions, such as gene transcription and translation in living cells, need a certain time to finish once they are initiated. Simulating stochastic models of reaction-diffusion systems with delay can be computationally expensive. In the present paper, a novel hybrid algorithm is proposed to accelerate the stochastic simulation of delayed reaction-diffusion systems. The delayed reactions may be of consuming or non-consuming delay type. The algorithm is designed for moderately stiff systems in which the events can be partitioned into slow and fast subsets according to their propensities. The proposed algorithm is applied to three benchmark problems and the results are compared with those of the delayed Inhomogeneous Stochastic Simulation Algorithm. The numerical results show that the new hybrid algorithm achieves considerable speed-up in the run time and very good accuracy.

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.

Insect Venom Immunotherapy: Analysis of the Safety and Tolerance of 3 Buildup Protocols Frequently Used in Spain.

PubMed

Gutiérrez Fernández, D; Moreno-Ancillo, A; Fernández Meléndez, S; Domínguez-Noche, C; Gálvez Ruiz, P; Alfaya Arias, T; Carballada González, F; Alonso Llamazares, A; Marques Amat, L; Vega Castro, A; Antolín Amérigo, D; Cruz Granados, S; Ruiz León, B; Sánchez Morillas, L; Fernández Sánchez, J; Soriano Gomis, V; Borja Segade, J; Dalmau Duch, G; Guspi Bori, R; Miranda Páez, A

2016-01-01

Hymenoptera venom immunotherapy (VIT) is an effective treatment but not one devoid of risk, as both local and systemic adverse reactions may occur, especially in the initial phases. We compared the tolerance to 3 VIT buildup protocols and analyzed risk factors associated with adverse reactions during this phase. We enrolled 165 patients divided into 3 groups based on the buildup protocol used (3, 4, and 9 weeks). The severity of systemic reactions was evaluated according to the World Allergy Organization model. Results were analyzed using exploratory descriptive statistics, and variables were compared using analysis of variance. Adverse reactions were recorded in 53 patients (32%) (43 local and 10 systemic). Local reactions were immediate in 27 patients (63%) and delayed in 16 (37%). The severity of the local reaction was slight/moderate in 15 patients and severe in 13. Systemic reactions were grade 1-2. No significant association was found between the treatment modality and the onset of local or systemic adverse reactions or the type of local reaction. We only found a statistically significant association between severity of the local reaction and female gender. As for the risk factors associated with systemic reactions during the buildup phase, we found no significant differences in values depending on the protocol used or the insect responsible. The buildup protocols compared proved to be safe and did not differ significantly from one another. In the population studied, patients undergoing the 9-week schedule presented no systemic reactions. Therefore, this protocol can be considered the safest approach.

Design criteria for extraction with chemical reaction and liquid membrane permeation

NASA Technical Reports Server (NTRS)

Bart, H. J.; Bauer, A.; Lorbach, D.; Marr, R.

1988-01-01

The design criteria for heterogeneous chemical reactions in liquid/liquid systems formally correspond to those of classical physical extraction. More complex models are presented which describe the material exchange at the individual droplets in an extraction with chemical reaction and in liquid membrane permeation.

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 Petri net approach to the study of persistence in chemical reaction networks.

PubMed

Angeli, David; De Leenheer, Patrick; Sontag, Eduardo D

2007-12-01

Persistence is the property, for differential equations in R(n), that solutions starting in the positive orthant do not approach the boundary of the orthant. For chemical reactions and population models, this translates into the non-extinction property: provided that every species is present at the start of the reaction, no species will tend to be eliminated in the course of the reaction. This paper provides checkable conditions for persistence of chemical species in reaction networks, using concepts and tools from Petri net theory, and verifies these conditions on various systems which arise in the modeling of cell signaling pathways.

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.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

PubMed

Kalantzis, Georgios

2009-06-01

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

Modeling Physical Processes at the Nanoscale—Insight into Self-Organization of Small Systems (abstract)

NASA Astrophysics Data System (ADS)

Proykova, Ana

2009-04-01

Essential contributions have been made in the field of finite-size systems of ingredients interacting with potentials of various ranges. Theoretical simulations have revealed peculiar size effects on stability, ground state structure, phases, and phase transformation of systems confined in space and time. Models developed in the field of pure physics (atomic and molecular clusters) have been extended and successfully transferred to finite-size systems that seem very different—small-scale financial markets, autoimmune reactions, and social group reactions to advertisements. The models show that small-scale markets diverge unexpectedly fast as a result of small fluctuations; autoimmune reactions are sequences of two discontinuous phase transitions; and social groups possess critical behavior (social percolation) under the influence of an external field (advertisement). Some predicted size-dependent properties have been experimentally observed. These findings lead to the hypothesis that restrictions on an object's size determine the object's total internal (configuration) and external (environmental) interactions. Since phases are emergent phenomena produced by self-organization of a large number of particles, the occurrence of a phase in a system containing a small number of ingredients is remarkable.

Experimental and modeling studies of small molecule chemistry in expanding spherical flames

NASA Astrophysics Data System (ADS)

Santner, Jeffrey

Accurate models of flame chemistry are required in order to predict emissions and flame properties, such that clean, efficient engines can be designed more easily. There are three primary methods used to improve such combustion chemistry models - theoretical reaction rate calculations, elementary reaction rate experiments, and combustion system experiments. This work contributes to model improvement through the third method - measurements and analysis of the laminar burning velocity at constraining conditions. Modern combustion systems operate at high pressure with strong exhaust gas dilution in order to improve efficiency and reduce emissions. Additionally, flames under these conditions are sensitized to elementary reaction rates such that measurements constrain modeling efforts. Measurement conditions of the present work operate within this intersection between applications and fundamental science. Experiments utilize a new pressure-release, heated spherical combustion chamber with a variety of fuels (high hydrogen content fuels, formaldehyde (via 1,3,5-trioxane), and C2 fuels) at pressures from 0.5--25 atm, often with dilution by water vapor or carbon dioxide to flame temperatures below 2000 K. The constraining ability of these measurements depends on their uncertainty. Thus, the present work includes a novel analytical estimate of the effects of thermal radiative heat loss on burning velocity measurements in spherical flames. For 1,3,5-trioxane experiments, global measurements are sufficiently sensitive to elementary reaction rates that optimization techniques are employed to indirectly measure the reaction rates of HCO consumption. Besides the influence of flame chemistry on propagation, this work also explores the chemistry involved in production of nitric oxide, a harmful pollutant, within flames. We find significant differences among available chemistry models, both in mechanistic structure and quantitative reaction rates. There is a lack of well-defined measurements of nitric oxide formation at high temperatures, contributing to disagreement between chemical models. This work accomplishes several goals. It identifies disagreements in pollutant formation chemistry. It creates a novel database of burning velocity measurements at relevant, sensitive conditions. It presents a simple, conservative estimate of radiation-induced measurement uncertainty in spherical flames. Finally, it utilizes systems-level flame experiments to indirectly measure elementary reaction rates.

Development of a model and computer code to describe solar grade silicon production processes. [phase changes in chemical reactors

NASA Technical Reports Server (NTRS)

Gould, R. K.

1978-01-01

Mechanisms for the SiCl4/Na and SiF4/Na reaction systems were examined. Reaction schemes which include 25 elementary reactions were formulated for each system and run to test the sensitivity of the computed concentration and temperature profiles to the values given estimated rate coefficients. It was found that, for SiCl4/Na, the rate of production of free Si is largely mixing-limited for reasonable rate coefficient estimates. For the SiF4/Na system the results indicate that the endothermicities of many of the reactions involved in producing Si from SiF4/Na cause this system to be chemistry-limited rather than mixing-limited.

New Evaluated Semi-Empirical Formula Using Optical Model for 14-15 MeV ( n, t) Reaction Cross Sections

NASA Astrophysics Data System (ADS)

Tel, E.; Durgu, C.; Aydın, A.; Bölükdemir, M. H.; Kaplan, A.; Okuducu, Ş.

2009-12-01

In the next century the world will face the need for new energy sources. Nuclear fusion can be one of the most attractive sources of energy from the viewpoint of safety and minimal environmental impact. Fusion will not produce CO2 or SO2 and thus will not contribute to global warming or acid rain. Achieving acceptable performance for a fusion power system in the areas of economics, safety and environmental acceptability, is critically dependent on performance of the blanket and diverter systems which are the primary heat recovery, plasma purification, and tritium breeding systems. Tritium self-sufficiency must be maintained for a commercial power plant. The hybrid reactor is a combination of the fusion and fission processes. For self-sustaining (D-T) fusion driver tritium breeding ratio should be greater than 1.05. So working out the systematics of ( n, t) reaction cross-sections are of great importance for the definition of the excitation function character for the given reaction taking place on various nuclei at energies up to 20 MeV. In this study, we have calculated non-elastic cross-sections by using optical model for ( n, t) reactions at 14-15 MeV energy. We have investigated the excitation function character and reaction Q-values depending on the asymmetry term effect for the ( n, t) reaction cross-sections. We have obtained new coefficients for the ( n, t) reaction cross-sections. We have suggested semi-empirical formulas including optical model nonelastic effects by fitting two parameters for the ( n, t) reaction cross-sections at 14-15 MeV. We have discussed the odd-even effect and the pairing effect considering binding energy systematic of the nuclear shell model for the new experimental data and new cross-sections formulas ( n, t) reactions developed by Tel et al. We have determined a different parameter groups by the classification of nuclei into even-even, even-odd and odd-even for ( n, t) reactions cross-sections. The obtained cross-section formulas with new coefficients have been discussed and compared with the available experimental data.

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

Effects of reaction control system jet flow field interactions on the aerodynamic characteristics of a 0.010-scale space shuttle orbiter model in the Langley Research Center 31 inch CFHT (OA85)

NASA Technical Reports Server (NTRS)

Daileda, J. J.; Marroquin, J.

1974-01-01

An experimental investigation was conducted to obtain detailed effects on supersonic vehicle hypersonic aerodynamic and stability and control characteristics of reaction control system jet flow field interactions with the local vehicle flow field. A 0.010-scale model was used. Six-component force data and wing, elevon, and body flap surface pressure data were obtained through an angle-of-attack range of -10 to +35 degrees with 0 deg angle of sideslip. The test was conducted with yaw, pitch and roll jet simulation at a free-stream Mach number of 10.3 and reaction control system plume simulation of flight dynamic pressures of 5, 10 and 20 PSF.

Discovery of Amadori-Type Conjugates in a Peptide Maillard Reaction and Their Corresponding Influence on the Formation of Pyrazines.

PubMed

Zou, Tingting; Liu, Jianbin; Song, Huanlu; Liu, Ye

2018-06-01

Knowledge of the role of peptides in the Maillard reaction is rather limited. In this study, peptide Maillard reaction model systems were established. Volatile and nonvolatile MRPs (Maillard reaction products) were investigated by GC-O-MS and LC-MS. Carbohydrate module labeling (CAMOLA) experiments were performed to elucidate the carbon skeleton of these compounds. Results showed that the peptide reaction system generated more pyrazines than the free amino acid group. Several new Amadori-type conjugates were identified as novel Maillard reaction products that could greatly influence the formation of pyrazines. Our work suggested anew mechanism involving these Amadori-type conjugates and subsequent investigation revealed that the conjugates could be important intermediate products in the reaction between dicarbonyl and dipeptide. Our findings demonstrate anew pyrazine generation mechanism in the dipeptide Maillard reaction. We found that a dipeptide Maillard reaction system generated more pyrazines than a reaction system composed of free amino acids. New cross-linked peptide-sugar compounds were identified and found to impact the formation of pyrazines. The results of this study may help in the preparation of thermal reaction flavors using enzymatically hydrolyzed vegetable/animal proteins, which contain a considerable amount of peptides, as one of the major reactants. © 2018 Institute of Food Technologists®.

Modeling Morphogenesis with Reaction-Diffusion Equations Using Galerkin Spectral Methods

DTIC Science & Technology

2002-05-06

reaction- diffusion equation is a difficult problem in analysis that will not be addressed here. Errors will also arise from numerically approx solutions to...the ODEs. When comparing the approximate solution to actual reaction- diffusion systems found in nature, we must also take into account errors that...

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.

Automatic simplification of systems of reaction-diffusion equations by a posteriori analysis.

PubMed

Maybank, Philip J; Whiteley, Jonathan P

2014-02-01

Many mathematical models in biology and physiology are represented by systems of nonlinear differential equations. In recent years these models have become increasingly complex in order to explain the enormous volume of data now available. A key role of modellers is to determine which components of the model have the greatest effect on a given observed behaviour. An approach for automatically fulfilling this role, based on a posteriori analysis, has recently been developed for nonlinear initial value ordinary differential equations [J.P. Whiteley, Model reduction using a posteriori analysis, Math. Biosci. 225 (2010) 44-52]. In this paper we extend this model reduction technique for application to both steady-state and time-dependent nonlinear reaction-diffusion systems. Exemplar problems drawn from biology are used to demonstrate the applicability of the technique. Copyright © 2014 Elsevier Inc. All rights reserved.

Fundamental Researches on the High-speed and High-efficiency Steelmaking Reaction

NASA Astrophysics Data System (ADS)

Kitamura, Shin-ya; Shibata, Hiroyuki; Maruoka, Nobuhiro

2012-06-01

Traditionally, steelmaking reactions have been analyzed by thermodynamics. Recently, software packages that can be used to calculate the equilibrium conditions have improved greatly. In some cases, information obtained in this software is useful for analyzing the steelmaking reaction. On the other hand, in industrial operation, steelmaking reactions, i.e., decarburization, dephosphorization, desulfurization or nitrogen removal, do not reach the equilibrium condition. Therefore, the kinetic model is very important for gaining a theoretical understanding of the steelmaking reaction. In this paper, the following recent research activities were shown; 1) mass transfer of impurities between solid oxide and liquid slag, 2) simulation model of hot metal dephosphorization by multiphase slag, 3) evaluation of reaction rate at bath surface in gas-liquid reaction system and 4) condition for forming of metal emulsion by bottom bubbling.

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

Chemical Continuous Time Random Walks

NASA Astrophysics Data System (ADS)

Aquino, T.; Dentz, M.

2017-12-01

Traditional methods for modeling solute transport through heterogeneous media employ Eulerian schemes to solve for solute concentration. More recently, Lagrangian methods have removed the need for spatial discretization through the use of Monte Carlo implementations of Langevin equations for solute particle motions. While there have been recent advances in modeling chemically reactive transport with recourse to Lagrangian methods, these remain less developed than their Eulerian counterparts, and many open problems such as efficient convergence and reconstruction of the concentration field remain. We explore a different avenue and consider the question: In heterogeneous chemically reactive systems, is it possible to describe the evolution of macroscopic reactant concentrations without explicitly resolving the spatial transport? Traditional Kinetic Monte Carlo methods, such as the Gillespie algorithm, model chemical reactions as random walks in particle number space, without the introduction of spatial coordinates. The inter-reaction times are exponentially distributed under the assumption that the system is well mixed. In real systems, transport limitations lead to incomplete mixing and decreased reaction efficiency. We introduce an arbitrary inter-reaction time distribution, which may account for the impact of incomplete mixing. This process defines an inhomogeneous continuous time random walk in particle number space, from which we derive a generalized chemical Master equation and formulate a generalized Gillespie algorithm. We then determine the modified chemical rate laws for different inter-reaction time distributions. We trace Michaelis-Menten-type kinetics back to finite-mean delay times, and predict time-nonlocal macroscopic reaction kinetics as a consequence of broadly distributed delays. Non-Markovian kinetics exhibit weak ergodicity breaking and show key features of reactions under local non-equilibrium.

A novel simulation theory and model system for multi-field coupling pipe-flow system

NASA Astrophysics Data System (ADS)

Chen, Yang; Jiang, Fan; Cai, Guobiao; Xu, Xu

2017-09-01

Due to the lack of a theoretical basis for multi-field coupling in many system-level models, a novel set of system-level basic equations for flow/heat transfer/combustion coupling is put forward. Then a finite volume model of quasi-1D transient flow field for multi-species compressible variable-cross-section pipe flow is established by discretising the basic equations on spatially staggered grids. Combining with the 2D axisymmetric model for pipe-wall temperature field and specific chemical reaction mechanisms, a finite volume model system is established; a set of specific calculation methods suitable for multi-field coupling system-level research is structured for various parameters in this model; specific modularisation simulation models can be further derived in accordance with specific structures of various typical components in a liquid propulsion system. This novel system can also be used to derive two sub-systems: a flow/heat transfer two-field coupling pipe-flow model system without chemical reaction and species diffusion; and a chemical equilibrium thermodynamic calculation-based multi-field coupling system. The applicability and accuracy of two sub-systems have been verified through a series of dynamic modelling and simulations in earlier studies. The validity of this system is verified in an air-hydrogen combustion sample system. The basic equations and the model system provide a unified universal theory and numerical system for modelling and simulation and even virtual testing of various pipeline systems.

Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways

NASA Astrophysics Data System (ADS)

Mathew, Kiran; Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Arias, T. A.; Hennig, Richard G.

2014-02-01

Solid-liquid interfaces are at the heart of many modern-day technologies and provide a challenge to many materials simulation methods. A realistic first-principles computational study of such systems entails the inclusion of solvent effects. In this work, we implement an implicit solvation model that has a firm theoretical foundation into the widely used density-functional code Vienna ab initio Software Package. The implicit solvation model follows the framework of joint density functional theory. We describe the framework, our algorithm and implementation, and benchmarks for small molecular systems. We apply the solvation model to study the surface energies of different facets of semiconducting and metallic nanocrystals and the SN2 reaction pathway. We find that solvation reduces the surface energies of the nanocrystals, especially for the semiconducting ones and increases the energy barrier of the SN2 reaction.

Free-Propagator Reweighting Integrator for Single-Particle Dynamics in Reaction-Diffusion Models of Heterogeneous Protein-Protein Interaction Systems

PubMed Central

Hummer, Gerhard

2015-01-01

We present a new algorithm for simulating reaction-diffusion equations at single-particle resolution. Our algorithm is designed to be both accurate and simple to implement, and to be applicable to large and heterogeneous systems, including those arising in systems biology applications. We combine the use of the exact Green's function for a pair of reacting particles with the approximate free-diffusion propagator for position updates to particles. Trajectory reweighting in our free-propagator reweighting (FPR) method recovers the exact association rates for a pair of interacting particles at all times. FPR simulations of many-body systems accurately reproduce the theoretically known dynamic behavior for a variety of different reaction types. FPR does not suffer from the loss of efficiency common to other path-reweighting schemes, first, because corrections apply only in the immediate vicinity of reacting particles and, second, because by construction the average weight factor equals one upon leaving this reaction zone. FPR applications include the modeling of pathways and networks of protein-driven processes where reaction rates can vary widely and thousands of proteins may participate in the formation of large assemblies. With a limited amount of bookkeeping necessary to ensure proper association rates for each reactant pair, FPR can account for changes to reaction rates or diffusion constants as a result of reaction events. Importantly, FPR can also be extended to physical descriptions of protein interactions with long-range forces, as we demonstrate here for Coulombic interactions. PMID:26005592

An experimental study of ammonia borane based hydrogen storage systems

NASA Astrophysics Data System (ADS)

Deshpande, Kedaresh A.

2011-12-01

Hydrogen is a promising fuel for the future, capable of meeting the demands of energy storage and low pollutant emission. Chemical hydrides are potential candidates for chemical hydrogen storage, especially for automobile applications. Ammonia borane (AB) is a chemical hydride being investigated widely for its potential to realize the hydrogen economy. In this work, the yield of hydrogen obtained during neat AB thermolysis was quantified using two reactor systems. First, an oil bath heated glass reactor system was used with AB batches of 0.13 gram (+/- 0.001 gram). The rates of hydrogen generation were measured. Based on these experimental data, an electrically heated steel reactor system was designed and constructed to handle up to 2 grams of AB per batch. A majority of components were made of stainless-steel. The system consisted of an AB reservoir and feeder, a heated reactor, a gas processing unit and a system control and monitoring unit. An electronic data acquisition system was used to record experimental data. The performance of the steel reactor system was evaluated experimentally through batch reactions of 30 minutes each, for reaction temperatures in the range from 373 K to 430 K. The experimental data showed exothermic decomposition of AB accompanied by rapid generation of hydrogen during the initial period of the reaction. 90% of the hydrogen was generated during the initial 120 seconds after addition of AB to the reactor. At 430 K, the reaction produced 12 wt.% of hydrogen. The heat diffusion in the reactor system and the process of exothermic decomposition of AB were coupled in a two-dimensional model. Neat AB thermolysis was modeled as a global first order reactions based on Arrhenius theory. The values of equation constants were derived from curve fit of experimental data. The pre-exponential constant and the activation energy were estimated to be 4 s-1 (+/- 0.4 s-1) and 13000 J mol -1 s-1 (+/- 1050 J mol-1 s -1) respectively. The model was solved in COMSOL Multiphysics. The model was capable of simulating the transient response of the system and captured the observed trends such as the decrease in reactor temperature upon addition of AB and exothermic decomposition.

NETPATH-WIN: an interactive user version of the mass-balance model, NETPATH

USGS Publications Warehouse

El-Kadi, A. I.; Plummer, Niel; Aggarwal, P.

2011-01-01

NETPATH-WIN is an interactive user version of NETPATH, an inverse geochemical modeling code used to find mass-balance reaction models that are consistent with the observed chemical and isotopic composition of waters from aquatic systems. NETPATH-WIN was constructed to migrate NETPATH applications into the Microsoft WINDOWS® environment. The new version facilitates model utilization by eliminating difficulties in data preparation and results analysis of the DOS version of NETPATH, while preserving all of the capabilities of the original version. Through example applications, the note describes some of the features of NETPATH-WIN as applied to adjustment of radiocarbon data for geochemical reactions in groundwater systems.

Catalytic combustion of hydrogen-air mixtures in stagnation flows

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

Ikeda, H.; Libby, P.A.; Williams, F.A.

1993-04-01

The interaction between heterogeneous and homogeneous reactions arising when a mixture of hydrogen and air impinges on a platinum plate at elevated temperature is studied. A reasonably complete description of the kinetic mechanism for homogeneous reactions is employed along with a simplified model for heterogeneous reactions. Four regimes are identified depending on the temperature of the plate, on the rate of strain imposed on the flow adjacent to the plate and on the composition and temperature of the reactant stream: (1) surface reaction alone; (2) surface reaction inhibiting homogeneous reaction; (3) homogeneous reaction inhibiting surface reaction; and (4) homogeneous reactionmore » alone. These regimes are related to those found earlier for other chemical systems and form the basis of future experimental investigation of the chemical system considered in the present study.« less

Multiresponse kinetic modelling of Maillard reaction and caramelisation in a heated glucose/wheat flour system.

PubMed

Kocadağlı, Tolgahan; Gökmen, Vural

2016-11-15

The study describes the kinetics of the formation and degradation of α-dicarbonyl compounds in glucose/wheat flour system heated under low moisture conditions. Changes in the concentrations of glucose, fructose, individual free amino acids, lysine and arginine residues, glucosone, 1-deoxyglucosone, 3-deoxyglucosone, 3,4-dideoxyglucosone, 5-hydroxymethyl-2-furfural, glyoxal, methylglyoxal and diacetyl concentrations were determined to form a multiresponse kinetic model for isomerisation and degradation reactions of glucose. Degradation of Amadori product mainly produced 1-deoxyglucosone. Formation of 3-deoxyglucosone proceeded directly from glucose and also Amadori product degradation. Glyoxal formation was predominant from glucosone while methylglyoxal and diacetyl originated from 1-deoxyglucosone. Formation of 5-hydroxymethyl-2-furfural from fructose was found to be a key step. Multi-response kinetic modelling of Maillard reaction and caramelisation simultaneously indicated quantitatively predominant parallel and consecutive pathways and rate limiting steps by estimating the reaction rate constants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Parameter Selection Methods in Inverse Problem Formulation

DTIC Science & Technology

2010-11-03

clinical data and used for prediction and a model for the reaction of the cardiovascular system to an ergometric workload. Key Words: Parameter selection...model for HIV dynamics which has been successfully validated with clinical data and used for prediction and a model for the reaction of the...recently developed in-host model for HIV dynamics which has been successfully validated with clinical data and used for prediction [4, 8]; b) a global

Complete integrability of information processing by biochemical reactions

PubMed Central

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

2016-01-01

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

Complete integrability of information processing by biochemical reactions

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Complete integrability of information processing by biochemical reactions.

PubMed

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

2016-11-04

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

System-level modeling of acetone-butanol-ethanol fermentation.

PubMed

Liao, Chen; Seo, Seung-Oh; Lu, Ting

2016-05-01

Acetone-butanol-ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modeling transport kinetics in clinoptilolite-phosphate rock systems

NASA Technical Reports Server (NTRS)

Allen, E. R.; Ming, D. W.; Hossner, L. R.; Henninger, D. L.

1995-01-01

Nutrient release in clinoptilolite-phosphate rock (Cp-PR) systems occurs through dissolution and cation-exchange reactions. Investigating the kinetics of these reactions expands our understanding of nutrient release processes. Research was conducted to model transport kinetics of nutrient release in Cp-PR systems. The objectives were to identify empirical models that best describe NH4, K, and P release and define diffusion-controlling processes. Materials included a Texas clinoptilolite (Cp) and North Carolina phosphate rock (PR). A continuous-flow thin-disk technique was used. Models evaluated included zero order, first order, second order, parabolic diffusion, simplified Elovich, Elovich, and power function. The power-function, Elovich, and parabolic-diffusion models adequately described NH4, K, and P release. The power-function model was preferred because of its simplicity. Models indicated nutrient release was diffusion controlled. Primary transport processes controlling nutrient release for the time span observed were probably the result of a combination of several interacting transport mechanisms.

PumpKin: A tool to find principal pathways in plasma chemical models

NASA Astrophysics Data System (ADS)

Markosyan, A. H.; Luque, A.; Gordillo-Vázquez, F. J.; Ebert, U.

2014-10-01

PumpKin is a software package to find all principal pathways, i.e. the dominant reaction sequences, in chemical reaction systems. Although many tools are available to integrate numerically arbitrarily complex chemical reaction systems, few tools exist in order to analyze the results and interpret them in relatively simple terms. In particular, due to the large disparity in the lifetimes of the interacting components, it is often useful to group reactions into pathways that recycle the fastest species. This allows a researcher to focus on the slow chemical dynamics, eliminating the shortest timescales. Based on the algorithm described by Lehmann (2004), PumpKin automates the process of finding such pathways, allowing the user to analyze complex kinetics and to understand the consumption and production of a certain species of interest. We designed PumpKin with an emphasis on plasma chemical systems but it can also be applied to atmospheric modeling and to industrial applications such as plasma medicine and plasma-assisted combustion.

The influence of emulsion structure on the Maillard reaction of ghee.

PubMed

Newton, Angela E; Fairbanks, Antony J; Golding, Matt; Andrewes, Paul; Gerrard, Juliet A

2015-04-15

Food systems, such as cream and butter, have an emulsion or emulsion-like structure. When these food emulsions are heated to high temperatures to make products such as ghee, the Maillard reaction forms a range of volatile flavour compounds. The objective of this paper was to unravel the specific influence of emulsion structure on the Maillard reaction pathways that occur during the cooking of ghee using model systems. Switching the dispersed phase from oil to water provided a means of altering the ratios of volatile compounds produced in the cooked samples. The oil-in-water emulsion generated a volatile compound profile similar to that of the fat containing two phase model matrix, whereas the water-in-oil emulsion produced a different ratio of these compounds. The ability to generate different volatile compound profiles through the use of inverted emulsion structures could point to a new avenue for control of the Maillard reaction in high temperature food systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

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/.

Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations

NASA Technical Reports Server (NTRS)

Shapiro, Bruce E.; Levchenko, Andre; Meyerowitz, Elliot M.; Wold, Barbara J.; Mjolsness, Eric D.

2003-01-01

Cellerator describes single and multi-cellular signal transduction networks (STN) with a compact, optionally palette-driven, arrow-based notation to represent biochemical reactions and transcriptional activation. Multi-compartment systems are represented as graphs with STNs embedded in each node. Interactions include mass-action, enzymatic, allosteric and connectionist models. Reactions are translated into differential equations and can be solved numerically to generate predictive time courses or output as systems of equations that can be read by other programs. Cellerator simulations are fully extensible and portable to any operating system that supports Mathematica, and can be indefinitely nested within larger data structures to produce highly scaleable models.

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.

On the possibility of negative activation energies in bimolecular reactions

NASA Technical Reports Server (NTRS)

Jaffe, R. L.

1978-01-01

The temperature dependence of the rate constants for model reacting systems was studied to understand some recent experimental measurements which imply the existence of negative activation energies. A collision theory model and classical trajectory calculations are used to demonstrate that the reaction probability can vary inversely with collision energy for bimolecular reactions occurring on attractive potential energy surfaces. However, this is not a sufficient condition to ensure that the rate constant has a negative temperature dependence. On the basis of these calculations, it seems unlikely that a true bimolecular reaction between neutral molecules will have a negative activation energy.

Mutagenicity of heated sugar-casein systems: effect of the Maillard reaction.

PubMed

Brands, C M; Alink, G M; van Boekel, M A; Jongen, W M

2000-06-01

The formation of mutagens after the heating of sugar-casein model systems at 120 degrees C was examined by the Ames test, using Salmonella typhimurium strain TA100. Several sugars (glucose, fructose, galactose, tagatose, lactose, and lactulose) were compared in their mutagenicities. Mutagenicity could be fully ascribed to Maillard reaction products and strongly varied with the kind of sugar. The differences in mutagenicity among the sugar-casein systems were caused by a difference in reaction rate and a difference in reaction mechanism. Sugars with a comparable reaction mechanism (glucose and galactose) showed a higher mutagenic activity corresponding with a higher Maillard reactivity. Disaccharides showed no mutagenic activity (lactose) or a lower mutagenic activity (lactulose) than their corresponding monosaccharides. Ketose sugars (fructose and tagatose) showed a remarkably higher mutagenicity compared with their aldose isomers (glucose and galactose), which was due to a difference in reaction mechanism.

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.

Discovering operating modes in telemetry data from the Shuttle Reaction Control System

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug; Kulkarni, Deepak

1994-01-01

This paper addresses the problem of detecting and diagnosing faults in physical systems, for which suitable system models are not available. An architecture is proposed that integrates the on-line acquisition and exploitation of monitoring and diagnostic knowledge. The focus is on the component of the architecture that discovers classes of behaviors with similar characteristics by observing a system in operation. A characterization of behaviors based on best fitting approximation models is investigated. An experimental prototype has been implemented to test it. Preliminary results in diagnosing faults of the reaction control system of the space shuttle are presented. The merits and limitations of the approach are identified and directions for future work are set.

Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction.

PubMed

Sadowski, Peter; Fooshee, David; Subrahmanya, Niranjan; Baldi, Pierre

2016-11-28

Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source-sink pairs. This addresses a bottleneck of QM calculations by providing a prioritized list of mechanistic reaction steps. QM modeling can then be used to compute the transition states and activation energies of the top-ranked reactions, providing additional or improved examples of ranked source-sink pairs. Retraining the ML model closes the loop, producing more accurate predictions from a larger training set. The approach is demonstrated in detail using a small set of organic radical reactions.

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.

Computational singular perturbation analysis of stochastic chemical systems with stiffness

NASA Astrophysics Data System (ADS)

Wang, Lijin; Han, Xiaoying; Cao, Yanzhao; Najm, Habib N.

2017-04-01

Computational singular perturbation (CSP) is a useful method for analysis, reduction, and time integration of stiff ordinary differential equation systems. It has found dominant utility, in particular, in chemical reaction systems with a large range of time scales at continuum and deterministic level. On the other hand, CSP is not directly applicable to chemical reaction systems at micro or meso-scale, where stochasticity plays an non-negligible role and thus has to be taken into account. In this work we develop a novel stochastic computational singular perturbation (SCSP) analysis and time integration framework, and associated algorithm, that can be used to not only construct accurately and efficiently the numerical solutions to stiff stochastic chemical reaction systems, but also analyze the dynamics of the reduced stochastic reaction systems. The algorithm is illustrated by an application to a benchmark stochastic differential equation model, and numerical experiments are carried out to demonstrate the effectiveness of the construction.

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

Modeling reactive transport with particle tracking and kernel estimators

NASA Astrophysics Data System (ADS)

Rahbaralam, Maryam; Fernandez-Garcia, Daniel; Sanchez-Vila, Xavier

2015-04-01

Groundwater reactive transport models are useful to assess and quantify the fate and transport of contaminants in subsurface media and are an essential tool for the analysis of coupled physical, chemical, and biological processes in Earth Systems. Particle Tracking Method (PTM) provides a computationally efficient and adaptable approach to solve the solute transport partial differential equation. On a molecular level, chemical reactions are the result of collisions, combinations, and/or decay of different species. For a well-mixed system, the chem- ical reactions are controlled by the classical thermodynamic rate coefficient. Each of these actions occurs with some probability that is a function of solute concentrations. PTM is based on considering that each particle actually represents a group of molecules. To properly simulate this system, an infinite number of particles is required, which is computationally unfeasible. On the other hand, a finite number of particles lead to a poor-mixed system which is limited by diffusion. Recent works have used this effect to actually model incomplete mix- ing in naturally occurring porous media. In this work, we demonstrate that this effect in most cases should be attributed to a defficient estimation of the concentrations and not to the occurrence of true incomplete mixing processes in porous media. To illustrate this, we show that a Kernel Density Estimation (KDE) of the concentrations can approach the well-mixed solution with a limited number of particles. KDEs provide weighting functions of each particle mass that expands its region of influence, hence providing a wider region for chemical reactions with time. Simulation results show that KDEs are powerful tools to improve state-of-the-art simulations of chemical reactions and indicates that incomplete mixing in diluted systems should be modeled based on alternative conceptual models and not on a limited number of particles.

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.

An Analytical Framework for Studying Small-Number Effects in Catalytic Reaction Networks: A Probability Generating Function Approach to Chemical Master Equations

PubMed Central

Nakagawa, Masaki; Togashi, Yuichi

2016-01-01

Cell activities primarily depend on chemical reactions, especially those mediated by enzymes, and this has led to these activities being modeled as catalytic reaction networks. Although deterministic ordinary differential equations of concentrations (rate equations) have been widely used for modeling purposes in the field of systems biology, it has been pointed out that these catalytic reaction networks may behave in a way that is qualitatively different from such deterministic representation when the number of molecules for certain chemical species in the system is small. Apart from this, representing these phenomena by simple binary (on/off) systems that omit the quantities would also not be feasible. As recent experiments have revealed the existence of rare chemical species in cells, the importance of being able to model potential small-number phenomena is being recognized. However, most preceding studies were based on numerical simulations, and theoretical frameworks to analyze these phenomena have not been sufficiently developed. Motivated by the small-number issue, this work aimed to develop an analytical framework for the chemical master equation describing the distributional behavior of catalytic reaction networks. For simplicity, we considered networks consisting of two-body catalytic reactions. We used the probability generating function method to obtain the steady-state solutions of the chemical master equation without specifying the parameters. We obtained the time evolution equations of the first- and second-order moments of concentrations, and the steady-state analytical solution of the chemical master equation under certain conditions. These results led to the rank conservation law, the connecting state to the winner-takes-all state, and analysis of 2-molecules M-species systems. A possible interpretation of the theoretical conclusion for actual biochemical pathways is also discussed. PMID:27047384

Atmospheric reaction systems as null-models to identify structural traces of evolution in metabolism.

PubMed

Holme, Petter; Huss, Mikael; Lee, Sang Hoon

2011-05-06

The metabolism is the motor behind the biological complexity of an organism. One problem of characterizing its large-scale structure is that it is hard to know what to compare it to. All chemical reaction systems are shaped by the same physics that gives molecules their stability and affinity to react. These fundamental factors cannot be captured by standard null-models based on randomization. The unique property of organismal metabolism is that it is controlled, to some extent, by an enzymatic machinery that is subject to evolution. In this paper, we explore the possibility that reaction systems of planetary atmospheres can serve as a null-model against which we can define metabolic structure and trace the influence of evolution. We find that the two types of data can be distinguished by their respective degree distributions. This is especially clear when looking at the degree distribution of the reaction network (of reaction connected to each other if they involve the same molecular species). For the Earth's atmospheric network and the human metabolic network, we look into more detail for an underlying explanation of this deviation. However, we cannot pinpoint a single cause of the difference, rather there are several concurrent factors. By examining quantities relating to the modular-functional organization of the metabolism, we confirm that metabolic networks have a more complex modular organization than the atmospheric networks, but not much more. We interpret the more variegated modular arrangement of metabolism as a trace of evolved functionality. On the other hand, it is quite remarkable how similar the structures of these two types of networks are, which emphasizes that the constraints from the chemical properties of the molecules has a larger influence in shaping the reaction system than does natural selection.

A study of 36Cl production in the early Solar System

NASA Astrophysics Data System (ADS)

Bowers, Matthew R.

Short-lived radionuclides (SLRs) with lifetimes tau < 100 Ma are known to have been extant when the Solar System formed 4.568 billion years ago from meteoritic studies of their decay products. Identifying the origins of SLRs can provide insight into the origins and timescales of our Solar System and the processes that shaped it. There are two proposed production scenarios for the origins of SLRs with tau < 5 Ma. Freshly synthesized material could be incorporated in the Solar System by a nearby stellar source (e.g., supernova, AGB star, Wolf-Rayet star), or SLRs could have also been produced by the bombardment of gas and dust by solar energetic particles (SEP) emitted by our young Sun. The origin of extinct 36Cl (t1/2 = 0.301 Ma) in the early Solar System is thought to have been produced by local particle irradiation. However the models that attempt to recreate the production of 36Cl in the early Solar System lack experimental data for the nuclear reactions considered. The first measurement of the 33S(alpha,p) 36Cl reaction, an important reaction in the production of 36Cl , was performed. The cross section measurement was performed by bombarding a target and collecting the recoiled 36Cl atoms produced in the reaction, chemically processing the samples, and measuring the 36Cl/Cl concentration of the samples with accelerator mass spectrometry (AMS). The cross section was measured at six energies that ranged from 0.70 up to 2.42 MeV/A, within the SEP energy spectrum. The experimental results were found to be systematically higher than the predicted cross sections. However, the deviations lead to < 7 % increase in total production of 36Cl under the x-wind model. From the experimental measurement and a study of the other reactions' contributions to 36Cl production, 36Cl could have been produced close to the protoSun by reactions on Ca targets using the x-wind model, or in a late-stage irradiation event on a volatile-rich reservoir by 3He and alpha reactions on S targets.

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.

Control of transversal instabilities in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Totz, Sonja; Löber, Jakob; Totz, Jan Frederik; Engel, Harald

2018-05-01

In two-dimensional reaction-diffusion systems, local curvature perturbations on traveling waves are typically damped out and vanish. However, if the inhibitor diffuses much faster than the activator, transversal instabilities can arise, leading from flat to folded, spatio-temporally modulated waves and to spreading spiral turbulence. Here, we propose a scheme to induce or inhibit these instabilities via a spatio-temporal feedback loop. In a piecewise-linear version of the FitzHugh–Nagumo model, transversal instabilities and spiral turbulence in the uncontrolled system are shown to be suppressed in the presence of control, thereby stabilizing plane wave propagation. Conversely, in numerical simulations with the modified Oregonator model for the photosensitive Belousov–Zhabotinsky reaction, which does not exhibit transversal instabilities on its own, we demonstrate the feasibility of inducing transversal instabilities and study the emerging wave patterns in a well-controlled manner.

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

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Elucidation of the molecular mechanisms underlying adverse reactions associated with a kinase inhibitor using systems toxicology

PubMed Central

Amemiya, Takahiro; Honma, Masashi; Kariya, Yoshiaki; Ghosh, Samik; Kitano, Hiroaki; Kurachi, Yoshihisa; Fujita, Ken-ichi; Sasaki, Yasutsuna; Homma, Yukio; Abernethy, Darrel R; Kume, Haruki; Suzuki, Hiroshi

2015-01-01

Background/Objectives: Targeted kinase inhibitors are an important class of agents in anticancer therapeutics, but their limited tolerability hampers their clinical performance. Identification of the molecular mechanisms underlying the development of adverse reactions will be helpful in establishing a rational method for the management of clinically adverse reactions. Here, we selected sunitinib as a model and demonstrated that the molecular mechanisms underlying the adverse reactions associated with kinase inhibitors can efficiently be identified using a systems toxicological approach. Methods: First, toxicological target candidates were short-listed by comparing the human kinase occupancy profiles of sunitinib and sorafenib, and the molecular mechanisms underlying adverse reactions were predicted by sequential simulations using publicly available mathematical models. Next, to evaluate the probability of these predictions, a clinical observation study was conducted in six patients treated with sunitinib. Finally, mouse experiments were performed for detailed confirmation of the hypothesized molecular mechanisms and to evaluate the efficacy of a proposed countermeasure against adverse reactions to sunitinib. Results: In silico simulations indicated the possibility that sunitinib-mediated off-target inhibition of phosphorylase kinase leads to the generation of oxidative stress in various tissues. Clinical observations of patients and mouse experiments confirmed the validity of this prediction. The simulation further suggested that concomitant use of an antioxidant may prevent sunitinib-mediated adverse reactions, which was confirmed in mouse experiments. Conclusions: A systems toxicological approach successfully predicted the molecular mechanisms underlying clinically adverse reactions associated with sunitinib and was used to plan a rational method for the management of these adverse reactions. PMID:28725458

Reachability bounds for chemical reaction networks and strand displacement systems.

PubMed

Condon, Anne; Kirkpatrick, Bonnie; Maňuch, Ján

2014-01-01

Chemical reaction networks (CRNs) and DNA strand displacement systems (DSDs) are widely-studied and useful models of molecular programming. However, in order for some DSDs in the literature to behave in an expected manner, the initial number of copies of some reagents is required to be fixed. In this paper we show that, when multiple copies of all initial molecules are present, general types of CRNs and DSDs fail to work correctly if the length of the shortest sequence of reactions needed to produce any given molecule exceeds a threshold that grows polynomially with attributes of the system.

The general theory of multistage geminate reactions of isolated pairs of reactants. III. Two-stage reversible dissociation in geminate reaction A + A↔C↔B + B

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

Kipriyanov, Alexey A.; Kipriyanov, Alexander A.; Doktorov, Alexander B.

2016-04-14

Specific two-stage reversible reaction A + A↔C↔B + B of the decay of species C reactants by two independent transition channels is considered on the basis of the general theory of multistage reactions of isolated pairs of reactants. It is assumed that at the initial instant of time, the reacting system contains only reactants C. The employed general approach has made it possible to consider, in the general case, the inhomogeneous initial distribution of reactants, and avoid application of model concepts of a reaction system structure (i.e., of the structure of reactants and their molecular mobility). Slowing of multistage reactionmore » kinetics as compared to the kinetics of elementary stages is established and physically interpreted. To test approximations (point approximation) used to develop a universal kinetic law, a widely employed specific model of spherical particles with isotropic reactivity diffusing in solution is applied. With this particular model as an example, ultimate kinetics of chemical conversion of reactants is investigated. The question concerning the depths of chemical transformation at which long-term asymptotes are reached is studied.« less

Transfer functions for protein signal transduction: application to a model of striatal neural plasticity.

PubMed

Scheler, Gabriele

2013-01-01

We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of "source" species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the "target" species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.

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.

Microbial respiration and dissolution precipitation reactions of minerals: thermo-kinetics and reactive transport modelling

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Accelerating Calculations of Reaction Dissipative Particle Dynamics in LAMMPS

DTIC Science & Technology

2017-05-17

order reaction mechanism, the best acceleration was 6.1 times. For a larger, more chemically detailed mechanism, the best acceleration exceeded 60 times...simulations at previously inaccessible scales. A principle feature of DPD-RX is its ability to model chemical reactions within each CG particle. The...change in composition due to chemical reactions is described by a system of ordinary differential equations (ODEs) that are evaluated at each DPD time

Thermally multiplexed polymerase chain reaction.

PubMed

Phaneuf, Christopher R; Pak, Nikita; Saunders, D Curtis; Holst, Gregory L; Birjiniuk, Joav; Nagpal, Nikita; Culpepper, Stephen; Popler, Emily; Shane, Andi L; Jerris, Robert; Forest, Craig R

2015-07-01

Amplification of multiple unique genetic targets using the polymerase chain reaction (PCR) is commonly required in molecular biology laboratories. Such reactions are typically performed either serially or by multiplex PCR. Serial reactions are time consuming, and multiplex PCR, while powerful and widely used, can be prone to amplification bias, PCR drift, and primer-primer interactions. We present a new thermocycling method, termed thermal multiplexing, in which a single heat source is uniformly distributed and selectively modulated for independent temperature control of an array of PCR reactions. Thermal multiplexing allows amplification of multiple targets simultaneously-each reaction segregated and performed at optimal conditions. We demonstrate the method using a microfluidic system consisting of an infrared laser thermocycler, a polymer microchip featuring 1 μl, oil-encapsulated reactions, and closed-loop pulse-width modulation control. Heat transfer modeling is used to characterize thermal performance limitations of the system. We validate the model and perform two reactions simultaneously with widely varying annealing temperatures (48 °C and 68 °C), demonstrating excellent amplification. In addition, to demonstrate microfluidic infrared PCR using clinical specimens, we successfully amplified and detected both influenza A and B from human nasopharyngeal swabs. Thermal multiplexing is scalable and applicable to challenges such as pathogen detection where patients presenting non-specific symptoms need to be efficiently screened across a viral or bacterial panel.

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.

Quantum Entanglement and Chemical Reactivity.

PubMed

Molina-Espíritu, M; Esquivel, R O; López-Rosa, S; Dehesa, J S

2015-11-10

The water molecule and a hydrogenic abstraction reaction are used to explore in detail some quantum entanglement features of chemical interest. We illustrate that the energetic and quantum-information approaches are necessary for a full understanding of both the geometry of the quantum probability density of molecular systems and the evolution of a chemical reaction. The energy and entanglement hypersurfaces and contour maps of these two models show different phenomena. The energy ones reveal the well-known stable geometry of the models, whereas the entanglement ones grasp the chemical capability to transform from one state system to a new one. In the water molecule the chemical reactivity is witnessed through quantum entanglement as a local minimum indicating the bond cleavage in the dissociation process of the molecule. Finally, quantum entanglement is also useful as a chemical reactivity descriptor by detecting the transition state along the intrinsic reaction path in the hypersurface of the hydrogenic abstraction reaction corresponding to a maximally entangled state.

Quantitative analysis of microbial biomass yield in aerobic bioreactor.

PubMed

Watanabe, Osamu; Isoda, Satoru

2013-12-01

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Time-ordered product expansions for computational stochastic system biology.

PubMed

Mjolsness, Eric

2013-06-01

The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie's stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems.

STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python

PubMed Central

Wils, Stefan; Schutter, Erik De

2008-01-01

We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. PMID:19623245

Atomistic Simulations of Detonation Instabilities in Condensed Phase Systems

NASA Astrophysics Data System (ADS)

Kober, Edward; Heim, Andrew; Germann, Timothy; Jensen, Niels

2007-06-01

We report the results of simulations of condensed phase detonation phenomena using a model diatomic system: 2AB -> A2 + B2. The initial set of parameters for this system corresponded to the Model 0 set of C. White et al, which exhibits a steady, Chapman-Jouget (CJ) detonation structure with a reaction zone length of 30-100 å. This has a highly compressed CJ state (V/V0˜0.5) that does not consist of discrete molecular species. The potential form was modified so that a more molecular CJ state resulted, consistent with the models for conventional organic explosives. The new system has a less dense CJ state (V/V0˜0.8), and the reaction zone was substantially extended. The reaction rate fits Arrhenius-type kinetics with an activation energy of ˜2 eV, with a minor density dependence. In contrast, the original Model 0 system had a lower activation energy (˜1 eV) with a stronger density dependence. The new system exhibits quite marked two dimensional instability structures with well-defined wavelengths similar to what has been observed for gas-phase detonations and for nitromethane. Depending on the exothermicity and the width of the periodic simulations, these instabilities can result in either detonation failure or quasi-steady propagation. The observed propagation velocities are several per cent higher than CJ values derived from thermodynamic analyses.

The effects of collision orientation and energy dependence in multinucleon transfer reactions

NASA Astrophysics Data System (ADS)

Li, Jingjing; Li, Cheng; Wen, Peiwei; Zhang, Feng-Shou

2018-05-01

Multinucleon transfer (MNT) reaction 136Xe+208Pb near Coulomb barrier energies are investigated within the dinuclear system (DNS) model. It is found that the collision orientation has an important influence on the mass distributions attributed to the depth of pocket in the driving potential. The calculation results of the isotopic production show that the energy dependence in neutron-deficient side is more sensitive than that in neutron-rich side. The production of the N = 126 isotones are calculated by GRAZING model, DNS+GEMINI model, and ImQMD+GEMINI model, respectively. It demonstrates that MNT reaction is a promising way to produce neutron-rich isotopes in the region of the neutron shell closure N = 126.

Multi-purpose wind tunnel reaction control model block

NASA Technical Reports Server (NTRS)

Dresser, H. S.; Daileda, J. J. (Inventor)

1978-01-01

A reaction control system nozzle block is provided for testing the response characteristics of space vehicles to a variety of reaction control thruster configurations. A pressurized air system is connected with the supply lines which lead to the individual jet nozzles. Each supply line terminates in a compact cylindrical plenum volume, axially perpendicular and adjacent to the throat of the jet nozzle. The volume of the cylindrical plenum is sized to provide uniform thrust characteristics from each jet nozzle irrespective of the angle of approach of the supply line to the plenum. Each supply line may be plugged or capped to stop the air supply to selected jet nozzles, thereby enabling a variety of nozzle configurations to be obtained from a single model nozzle block.

Clustering and optimal arrangement of enzymes in reaction-diffusion systems.

PubMed

Buchner, Alexander; Tostevin, Filipe; Gerland, Ulrich

2013-05-17

Enzymes within biochemical pathways are often colocalized, yet the consequences of specific spatial enzyme arrangements remain poorly understood. We study the impact of enzyme arrangement on reaction efficiency within a reaction-diffusion model. The optimal arrangement transitions from a cluster to a distributed profile as a single parameter, which controls the probability of reaction versus diffusive loss of pathway intermediates, is varied. We introduce the concept of enzyme exposure to explain how this transition arises from the stochastic nature of molecular reactions and diffusion.

Multiscale Modeling of Diffusion in a Crowded Environment.

PubMed

Meinecke, Lina

2017-11-01

We present a multiscale approach to model diffusion in a crowded environment and its effect on the reaction rates. Diffusion in biological systems is often modeled by a discrete space jump process in order to capture the inherent noise of biological systems, which becomes important in the low copy number regime. To model diffusion in the crowded cell environment efficiently, we compute the jump rates in this mesoscopic model from local first exit times, which account for the microscopic positions of the crowding molecules, while the diffusing molecules jump on a coarser Cartesian grid. We then extract a macroscopic description from the resulting jump rates, where the excluded volume effect is modeled by a diffusion equation with space-dependent diffusion coefficient. The crowding molecules can be of arbitrary shape and size, and numerical experiments demonstrate that those factors together with the size of the diffusing molecule play a crucial role on the magnitude of the decrease in diffusive motion. When correcting the reaction rates for the altered diffusion we can show that molecular crowding either enhances or inhibits chemical reactions depending on local fluctuations of the obstacle density.

Chemical-Reaction-Controlled Phase Separated Drops: Formation, Size Selection, and Coarsening

NASA Astrophysics Data System (ADS)

Wurtz, Jean David; Lee, Chiu Fan

2018-02-01

Phase separation under nonequilibrium conditions is exploited by biological cells to organize their cytoplasm but remains poorly understood as a physical phenomenon. Here, we study a ternary fluid model in which phase-separating molecules can be converted into soluble molecules, and vice versa, via chemical reactions. We elucidate using analytical and simulation methods how drop size, formation, and coarsening can be controlled by the chemical reaction rates, and categorize the qualitative behavior of the system into distinct regimes. Ostwald ripening arrest occurs above critical reaction rates, demonstrating that this transition belongs entirely to the nonequilibrium regime. Our model is a minimal representation of the cell cytoplasm.

Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling

DOE PAGES

Garcia, Andres; Wang, Jing; Windus, Theresa L.; ...

2016-05-20

Statistical mechanical modeling is developed to describe a catalytic conversion reaction A → B c or B t with concentration-dependent selectivity of the products, B c or B t, where reaction occurs inside catalytic particles traversed by narrow linear nanopores. The associated restricted diffusive transport, which in the extreme case is described by single-file diffusion, naturally induces strong concentration gradients. Hence, by comparing kinetic Monte Carlo simulation results with analytic treatments, selectivity is shown to be impacted by strong spatial correlations induced by restricted diffusivity in the presence of reaction and also by a subtle clustering of reactants, A.

The mineralogic evolution of the Martian surface through time: Implications from chemical reaction path modeling studies

NASA Technical Reports Server (NTRS)

Plumlee, G. S.; Ridley, W. I.; Debraal, J. D.; Reed, M. H.

1993-01-01

Chemical reaction path calculations were used to model the minerals that might have formed at or near the Martian surface as a result of volcano or meteorite impact driven hydrothermal systems; weathering at the Martian surface during an early warm, wet climate; and near-zero or sub-zero C brine-regolith reactions in the current cold climate. Although the chemical reaction path calculations carried out do not define the exact mineralogical evolution of the Martian surface over time, they do place valuable geochemical constraints on the types of minerals that formed from an aqueous phase under various surficial and geochemically complex conditions.

Study of the Kinetics of an S[subscript N]1 Reaction by Conductivity Measurement

ERIC Educational Resources Information Center

Marzluff, Elaine M.; Crawford, Mary A.; Reynolds, Helen

2011-01-01

Substitution reactions, a central part of organic chemistry, provide a model system in physical chemistry to study reaction rates and mechanisms. Here, the use of inexpensive and readily available commercial conductivity probes coupled with computer data acquisition for the study of the temperature and solvent dependence of the solvolysis of…

Charge-dependent non-bonded interaction methods for use in quantum mechanical modeling of condensed phase reactions

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.

Molecular modeling and computer simulation techniques can provide detailed insight into biochemical phenomena. This dissertation describes the development, implementation and parameterization of two methods for the accurate modeling of chemical reactions in aqueous environments, with a concerted scientific effort towards the inclusion of charge-dependent non-bonded non-electrostatic interactions into currently used computational frameworks. The first of these models, QXD, modifies interactions in a hybrid quantum mechanical/molecular (QM/MM) mechanical framework to overcome the current limitations of 'atom typing' QM atoms; an inaccurate and non-intuitive practice for chemically active species as these static atom types are dictated by the local bonding and electrostatic environment of the atoms they represent, which will change over the course of the simulation. The efficacy QXD model is demonstrated using a specific reaction parameterization (SRP) of the Austin Model 1 (AM1) Hamiltonian by simultaneously capturing the reaction barrier for chloride ion attack on methylchloride in solution and the solvation free energies of a series of compounds including the reagents of the reaction. The second, VRSCOSMO, is an implicit solvation model for use with the DFTB3/3OB Hamiltonian for biochemical reactions; allowing for accurate modeling of ionic compound solvation properties while overcoming the discontinuous nature of conventional PCM models when chemical reaction coordinates. The VRSCOSMO model is shown to accurately model the solvation properties of over 200 chemical compounds while also providing smooth, continuous reaction surfaces for a series of biologically motivated phosphoryl transesterification reactions. Both of these methods incorporate charge-dependent behavior into the non-bonded interactions variationally, allowing the 'size' of atoms to change in meaningful ways with respect to changes in local charge state, as to provide an accurate, predictive and transferable models for the interactions between the quantum mechanical system and their solvated surroundings.

Bromamine Decomposition Revisited: A Holistic Approach for Analyzing Acid and Base Catalysis Kinetics.

PubMed

Wahman, David G; Speitel, Gerald E; Katz, Lynn E

2017-11-21

Chloramine chemistry is complex, with a variety of reactions occurring in series and parallel and many that are acid or base catalyzed, resulting in numerous rate constants. Bromide presence increases system complexity even further with possible bromamine and bromochloramine formation. Therefore, techniques for parameter estimation must address this complexity through thoughtful experimental design and robust data analysis approaches. The current research outlines a rational basis for constrained data fitting using Brønsted theory, application of the microscopic reversibility principle to reversible acid or base catalyzed reactions, and characterization of the relative significance of parallel reactions using fictive product tracking. This holistic approach was used on a comprehensive and well-documented data set for bromamine decomposition, allowing new interpretations of existing data by revealing that a previously published reaction scheme was not robust; it was not able to describe monobromamine or dibromamine decay outside of the conditions for which it was calibrated. The current research's simplified model (3 reactions, 17 constants) represented the experimental data better than the previously published model (4 reactions, 28 constants). A final model evaluation was conducted based on representative drinking water conditions to determine a minimal model (3 reactions, 8 constants) applicable for drinking water conditions.

Dynamic control and information processing in chemical reaction systems by tuning self-organization behavior

NASA Astrophysics Data System (ADS)

Lebiedz, Dirk; Brandt-Pollmann, Ulrich

2004-09-01

Specific external control of chemical reaction systems and both dynamic control and signal processing as central functions in biochemical reaction systems are important issues of modern nonlinear science. For example nonlinear input-output behavior and its regulation are crucial for the maintainance of the life process that requires extensive communication between cells and their environment. An important question is how the dynamical behavior of biochemical systems is controlled and how they process information transmitted by incoming signals. But also from a general point of view external forcing of complex chemical reaction processes is important in many application areas ranging from chemical engineering to biomedicine. In order to study such control issues numerically, here, we choose a well characterized chemical system, the CO oxidation on Pt(110), which is interesting per se as an externally forced chemical oscillator model. We show numerically that tuning of temporal self-organization by input signals in this simple nonlinear chemical reaction exhibiting oscillatory behavior can in principle be exploited for both specific external control of dynamical system behavior and processing of complex information.

Unimolecular decomposition reactions at low-pressure: A comparison of competitive methods

NASA Technical Reports Server (NTRS)

Adams, G. F.

1980-01-01

The lack of a simple rate coefficient expression to describe the pressure and temperature dependence hampers chemical modeling of flame systems. Recently developed simplified models to describe unimolecular processes include the calculation of rate constants for thermal unimolecular reactions and recombinations at the low pressure limit, at the high pressure limit and in the intermediate fall-off region. Comparison between two different applications of Troe's simplified model and a comparison between the simplified model and the classic RRKM theory are described.

Incorporation of the statistical multi-fragmentation model in PHITS and its application for simulation of fragmentation by heavy ions and protons

NASA Astrophysics Data System (ADS)

Ogawa, Tatsuhiko; Sato, Tatsuhiko; Hashimoto, Shintaro; Niita, Koji

2014-06-01

The fragmentation reactions of relativistic-energy nucleus-nucleus and proton-nucleus collisions were simulated using the Statistical Multi-fragmentation Model (SMM) incorporated with the Particle and Heavy Ion Transport code System (PHITS). The comparisons of calculated cross-sections with literature data showed that PHITS-SMM predicts the fragmentation cross-sections of heavy nuclei up to two orders of magnitude more accurately than PHITS for heavy-ion-induced reactions. For proton-induced reactions, noticeable improvements are observed for interactions of the heavy target with protons at an energy greater than 1 GeV. Therefore, consideration for multi-fragmentation reactions is necessary for the accurate simulation of energetic fragmentation reactions of heavy nuclei.

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

Garcia, Andres

Transport and reaction in zeolites and other porous materials, such as mesoporous silica particles, has been a focus of interest in recent years. This is in part due to the possibility of anomalous transport effects (e.g. single-file diffusion) and its impact in the reaction yield in catalytic processes. Computational simulations are often used to study these complex nonequilibrium systems. Computer simulations using Molecular Dynamics (MD) techniques are prohibitive, so instead coarse grained one-dimensional models with the aid of Kinetic Monte Carlo (KMC) simulations are used. Both techniques can be computationally expensive, both time and resource wise. These coarse-grained systems canmore » be exactly described by a set of coupled stochastic master equations, that describe the reaction-diffusion kinetics of the system. The equations can be written exactly, however, coupling between the equations and terms within the equations make it impossible to solve them exactly; approximations must be made. One of the most common methods to obtain approximate solutions is to use Mean Field (MF) theory. MF treatments yield reasonable results at high ratios of reaction rate k to hop rate h of the particles, but fail completely at low k=h due to the over-estimation of fluxes of particles within the pore. We develop a method to estimate fluxes and intrapore diffusivity in simple one- dimensional reaction-diffusion models at high and low k=h, where the pores are coupled to an equilibrated three-dimensional fluid. We thus successfully describe analytically these simple reaction-diffusion one-dimensional systems. Extensions to models considering behavior with long range steric interactions and wider pores require determination of multiple boundary conditions. We give a prescription to estimate the required parameters for these simulations. For one dimensional systems, if single-file diffusion is relaxed, additional parameters to describe particle exchange have to be introduced. We use Langevin Molecular Dynamics (MD) simulations to assess these parameters.« less

Studying Zeolite Catalysts with a 2D Model System

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

Boscoboinik, Anibal

2016-12-07

Anibal Boscoboinik, a materials scientist at Brookhaven’s Center for Functional Nanomaterials, discusses the surface-science tools and 2D model system he uses to study catalysis in nanoporous zeolites, which catalyze reactions in many industrial processes.

Development of the Monolith Froth Reactor for Catalytic Wet Oxidation of CELSS Model Wastes

NASA Technical Reports Server (NTRS)

Fisher, John W.; Abraham, Martin

1993-01-01

The aqueous phase oxidation of acetic acid, used as a model compound for the treatment of CELSS (Controlled Ecological Life Support System) waste, was carried out in the monolith froth reactor which utilizes two-phase flow in the monolith channels. The catalytic oxidation of acetic acid was carried out over a Pt/Al2O3 catalyst at temperatures and pressures below the critical point of water. The effect of externally controllable parameters (temperature, liquid flow rate, distributor plate orifice size, pitch, and catalyst distance from the distributor plate) on the rate of acetic acid oxidation was investigated. Results indicate reaction rate increased with increasing temperature and exhibited a maximum with respect to liquid flow rate. The apparent activation energy calculated from reaction rate data was 99.7 kJ/mol. This value is similar to values reported for the oxidation of acetic acid in other systems and is comparable to intrinsic values calculated for oxidation reactions. The kinetic data were modeled using simple power law kinetics. The effect of "froth" feed system characteristics was also investigated. Results indicate that the reaction rate exhibits a maximum with respect to distributor plate orifice size, pitch, and catalyst distance from the distributor plate. Fundamental results obtained were used to extrapolate where the complete removal of acetic acid would be obtained and for the design and operation of a full scale CELSS treatment system.

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.

Models in the Design and Validation of Eddy Current Inspection for Cracking in the Shuttle Reaction Control System Thruster

NASA Technical Reports Server (NTRS)

Aldrin, John C.; Williams, Phillip A.; Wincheski, Russell (Buzz) A.

2008-01-01

A case study is presented for using models in eddy current NDE design for crack detection in Shuttle Reaction Control System thruster components. Numerical methods were used to address the complex geometry of the part and perform parametric studies of potential transducer designs. Simulations were found to show agreement with experimental results. Accurate representation of the coherent noise associated with the measurement and part geometry was found to be critical to properly evaluate the best probe designs.

Valence-bond study of the /H2, D2/ exchange reaction mechanism.

NASA Technical Reports Server (NTRS)

Freihaut, B.; Raff, L. M.

1973-01-01

The exchange reaction of H2 with D2 to form 2 HD is important in that it is fundamentally the simplest four-body exchange reaction and should therefore represent a model system on which various theories of reactions dynamics might be tested. A number of theoretical and experimental investigations carried out on this system are reviewed. It is concluded that a Y yields T yields Y mechanism for the (H2, D2) exchange is not a low energy pathway that would make theory compatible with the shock-tube experiments of Bauer and Ossa (1966) and of Burcat and Lifshits (1967).

Nonlinear Systems.

ERIC Educational Resources Information Center

Seider, Warren D.; Ungar, Lyle H.

1987-01-01

Describes a course in nonlinear mathematics courses offered at the University of Pennsylvania which provides an opportunity for students to examine the complex solution spaces that chemical engineers encounter. Topics include modeling many chemical processes, especially those involving reaction and diffusion, auto catalytic reactions, phase…

Bee and bee products allergy in Turkish beekeepers: determination of risk factors for systemic reactions.

PubMed

Celikel, S; Karakaya, G; Yurtsever, N; Sorkun, K; Kalyoncu, A F

2006-01-01

The prevalence of allergic reactions due to bee stings in beekeepers varies in different regions of the world. The aim of this study was to evaluate the characteristics of sting reactions and the risk factors for developing systemic reactions in Turkish beekeepers. A self-administered questionnaire was distributed to 1250 beekeepers to be completed in seven different cities of Turkey. A total of 494 (39.6 %) questionnaires were returned. There were 444 subjects (89.9 %) with a history of sting exposure in the previous 12 months. Systemic reactions were present in 29 subjects (6.5 %) and nine (2 %) reactions were anaphylactic. Fifty-five percent of beekeepers reported more than 100 bee stings in the previous year. When systemic reactions were controlled by age and duration of beekeeping in a logistic regression model, seasonal rhinitis (OR: 4.4, 95 % CI: 1.2-11.5), perennial rhinitis (OR: 4.6, 95 % CI: 1.2-18.2), food allergy (OR:7.0, 95 % CI: 2.0-25.0), physician-diagnosed asthma (OR: 8.0, 95 % CI: 2.5-25.6), having an atopic disease of any type (OR: 3.3, 95 % CI: 1.2-8.7) and having two or more atopic diseases (OR: 10.9, 95 % CI: 3.5-33.8) were significantly associated with systemic reactions due to bee sting in the previous 12 months. The incidence of systemic reactions in Turkish beekeepers is low, which might be due to the protective effect of a high frequency of bee stings. The risk of systemic reactions increases approximately three-fold when one atopic disease is present and eleven-fold when two or more concurrent atopic diseases are present with respect to no atopic disease.

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

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.

Stochastic Analysis of Reaction–Diffusion Processes

PubMed Central

Hu, Jifeng; Kang, Hye-Won

2013-01-01

Reaction and diffusion processes are used to model chemical and biological processes over a wide range of spatial and temporal scales. Several routes to the diffusion process at various levels of description in time and space are discussed and the master equation for spatially discretized systems involving reaction and diffusion is developed. We discuss an estimator for the appropriate compartment size for simulating reaction–diffusion systems and introduce a measure of fluctuations in a discretized system. We then describe a new computational algorithm for implementing a modified Gillespie method for compartmental systems in which reactions are aggregated into equivalence classes and computational cells are searched via an optimized tree structure. Finally, we discuss several examples that illustrate the issues that have to be addressed in general systems. PMID:23719732

Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics.

PubMed

Hanel, Rudolf; Pöchacker, Manfred; Thurner, Stefan

2010-12-28

Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems, their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network, and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.

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

Reply to 'Comments on upscaling geochemical reaction rates usingpore-scale network modeling' by Peter C. Lichtner and Qinjun Kang

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

Li, Li; Peters, Catherine A.; Celia, Michael A.

2006-05-03

Our paper "Upscaling geochemical reaction rates usingpore-scale network modeling" presents a novel application of pore-scalenetwork modeling to upscale mineral dissolution and precipitationreaction rates from the pore scale to the continuum scale, anddemonstrates the methodology by analyzing the scaling behavior ofanorthite and kaolinite reaction kinetics under conditions related to CO2sequestration. We conclude that under highly acidic conditions relevantto CO2 sequestration, the traditional continuum-based methodology may notcapture the spatial variation in concentrations from pore to pore, andscaling tools may be important in correctly modeling reactive transportprocesses in such systems. This work addresses the important butdifficult question of scaling mineral dissolution and precipitationreactionmore » kinetics, which is often ignored in fields such as geochemistry,water resources, and contaminant hydrology. Although scaling of physicalprocesses has been studied for almost three decades, very few studieshave examined the scaling issues related to chemical processes, despitetheir importance in governing the transport and fate of contaminants insubsurface systems.« less

The mechanism distinguishability problem in biochemical kinetics: the single-enzyme, single-substrate reaction as a case study.

PubMed

Schnell, Santiago; Chappell, Michael J; Evans, Neil D; Roussel, Marc R

2006-01-01

A theoretical analysis of the distinguishability problem of two rival models of the single enzyme-single substrate reaction, the Michaelis-Menten and Henri mechanisms, is presented. We also outline a general approach for analysing the structural indistinguishability between two mechanisms. The approach involves constructing, if possible, a smooth mapping between the two candidate models. Evans et al. [N.D. Evans, M.J. Chappell, M.J. Chapman, K.R. Godfrey, Structural indistinguishability between uncontrolled (autonomous) nonlinear analytic systems, Automatica 40 (2004) 1947-1953] have shown that if, in addition, either of the mechanisms satisfies a particular criterion then such a transformation always exists when the models are indistinguishable from their experimentally observable outputs. The approach is applied to the single enzyme-single substrate reaction mechanism. In principle, mechanisms can be distinguished using this analysis, but we show that our ability to distinguish mechanistic models depends both on the precise measurements made, and on our knowledge of the system prior to performing the kinetics experiments.

Space shuttle orbiter rear mounted reaction control system jet interaction study. [hypersonic wind tunnel tests

NASA Technical Reports Server (NTRS)

Rausch, J. R.

1977-01-01

The effect of interaction between the reaction control system (RCS) jets and the flow over the space shuttle orbiter in the atmosphere was investigated in the NASA Langley 31-inch continuous flow hypersonic tunnel at a nominal Mach number of 10.3 and in the AEDC continuous flow hypersonic tunnel B at a nominal Mach number of 6, using 0.01 and .0125 scale force models with aft RCS nozzles mounted both on the model and on the sting of the force model balance. The data show that RCS nozzle exit momentum ratio is the primary correlating parameter for effects where the plume impinges on an adjacent surface and mass flow ratio is the parameter when the plume interaction is primarily with the external stream. An analytic model of aft mounted RCS units was developed in which the total reaction control moments are the sum of thrust, impingement, interaction, and cross-coupling terms.

Prediction of adverse drug reactions using decision tree modeling.

PubMed

Hammann, F; Gutmann, H; Vogt, N; Helma, C; Drewe, J

2010-07-01

Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.

Bimolecular interaction of argpyrimidine (a Maillard reaction product) in in vitro non-enzymatic protein glycation model and its potential role as an antiglycating agent.

PubMed

Bhattacherjee, Abhishek; Dhara, Kaliprasanna; Chakraborti, Abhay Sankar

2017-09-01

Non- enzymatic glycation, also known as Maillard reaction, is one of the most important and investigated reactions in biochemistry. Maillard reaction products (MRPs) like protein-derived advanced glycation end products (AGEs) are often referred to cause pathophysiological complications in human systems. On contrary, several MRPs are exogenously used as antioxidant, antimicrobial and flavouring agents. In the preset study, we have shown that argpyrimidine, a well-established AGE, interacts with bovine serum albumin (BSA) and glucose individually in standard BSA-glucose model system and successfully inhibits glycation of the protein. Bimolecular interaction of argpyrimidine with glucose or BSA has been studied independently. Chromatographic purification, different spectroscopic studies and molecular modeling have been used to evaluate the nature and pattern of interactions. Binding of argpyrimidine with BSA prevents incorporation of glucose inside the native protein. Argpyrimidine can also directly entrap glucose. Both these interactions may be associated with the antiglycation potential of argpyrimidine, indicating a beneficial function of an AGE. Copyright © 2017 Elsevier B.V. All rights reserved.

A mathematical model for the generation and control of a pH gradient in an immobilized enzyme system involving acid generation.

PubMed

Chen, G; Fournier, R L; Varanasi, S

1998-02-20

An optimal pH control technique has been developed for multistep enzymatic synthesis reactions where the optimal pH differs by several units for each step. This technique separates an acidic environment from a basic environment by the hydrolysis of urea within a thin layer of immobilized urease. With this technique, a two-step enzymatic reaction can take place simultaneously, in proximity to each other, and at their respective optimal pH. Because a reaction system involving an acid generation represents a more challenging test of this pH control technique, a number of factors that affect the generation of such a pH gradient are considered in this study. The mathematical model proposed is based on several simplifying assumptions and represents a first attempt to provide an analysis of this complex problem. The results show that, by choosing appropriate parameters, the pH control technique still can generate the desired pH gradient even if there is an acid-generating reaction in the system. Copyright 1998 John Wiley & Sons, Inc.

Reaction of long-lived radicals and vitamin C in γ-irradiated mammalian cells and their model system at 295 K. Tunneling reaction in biological system

NASA Astrophysics Data System (ADS)

Matsumoto, Takuro; Miyazaki, Tetsuo; Kosugi, Yoshio; Kumada, Takayuki; Koyama, Sinji; Kodama, Seiji; Watanabe, Masami

1997-05-01

When golden hamster embryo (GHE) cells or concentrated albumin solution (0.1 kg dm -3) that is a model system of cells is irradiated with γ-rays at 295 K, organic radicals produced can be observed by ESR. The organic radicals survive at both 295 and 310 K for such a long time as 20 h. The long-lived radicals in GHE cells and the albumin solution react with vitamin C by the rate constants of 0.007 dm 3 mol -1 s -1 and 0.014 dm 3 mol -1 s -1, respectively. The long-lived radicals in human cells cause gene mutation, which is suppressed by addition of vitamin C. The isotope effect on the rate constant ( k) for the reaction of the long-lived radicals and vitamin C has been studied in the albumin solution by use of protonated vitamin C and deuterated vitamin C. The isotope effect ( kH/ kD) was more than 20 ≈ 50 and was interpreted in terms of tunneling reaction.

Rapid neutral-neutral reactions at low temperatures: a new network and first results for TMC-1

NASA Astrophysics Data System (ADS)

Smith, Ian W. M.; Herbst, Eric; Chang, Qiang

2004-05-01

There is now ample evidence from an assortment of experiments, especially those involving the CRESU (Cinétique de Réaction en Ecoulement Supersonique Uniforme) technique, that a variety of neutral-neutral reactions possess no activation energy barrier and are quite rapid at very low temperatures. These reactions include both radical-radical systems and, more surprisingly, systems involving an atom or a radical and one `stable' species. Generalizing from the small but growing number of systems studied in the laboratory, we estimate reaction rate coefficients for a larger number of such reactions and include these estimates in a new network of gas-phase reactions for use in low-temperature interstellar chemistry. Designated osu.2003, the new network is available on the World Wide Web and will be continually updated. A table of new results for molecular abundances in the dark cloud TMC-1 (CP) is provided and compared with results from an older (new standard model; nsm) network.

Effect of gravity field on the nonequilibrium/nonlinear chemical oscillation reactions

NASA Astrophysics Data System (ADS)

Fujieda, S.; Mori, Y.; Nakazawa, A.; Mogami, Y.

2001-01-01

Biological systems have evolved for a long time under the normal gravity. The Belousov-Zhabotinsky (BZ) reaction is a nonlinear chemical system far from the equilibrium that may be considered as a simplified chemical model of the biological systems so as to study the effect of gravity. The reaction solution is comprised of bromate in sulfuric acid as an oxidizing agent, 1,4-cyclohexanedione as an organic substrate, and ferroin as a metal catalyst. Chemical waves in the BZ reaction-diffusion system are visualized as blue and red patterns of ferriin and ferroin, respectively. After an improvement to the tubular reaction vessels in the experimental setup, the traveling velocity of chemical waves in aqueous solutions was measured in time series under normal gravity, microgravity, hyper-gravity, and normal gravity using the free-fall facility of JAMIC (Japan Microgravity Center), Hokkaido, Japan. Chemical patterns were collected as image data via CCD camera and analyzed by the software of NIH image after digitization. The estimated traveling velocity increased with increasing gravity as expected. It was clear experimentally that the traveling velocity of target patterns in reaction diffusion system was influenced by the effect of convection and correlated closely with the gravity field.

Studying Zeolite Catalysts with a 2D Model System

ScienceCinema

Boscoboinik, Anibal

2018-06-13

Anibal Boscoboinik, a materials scientist at Brookhaven’s Center for Functional Nanomaterials, discusses the surface-science tools and 2D model system he uses to study catalysis in nanoporous zeolites, which catalyze reactions in many industrial processes.

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.

Modeling the benefits of an artificial gravity countermeasure coupled with exercise and vibration

NASA Astrophysics Data System (ADS)

Goel, Rahul; Kaderka, Justin; Newman, Dava

2012-01-01

The current, system-specific countermeasures to space deconditioning have limited success with the musculoskeletal system in long duration missions. Artificial gravity (AG) that is produced by short radius centrifugation has been hypothesized as an effective countermeasure because it reintroduces an acceleration field in space; however, AG alone might not be enough stimuli to preserve the musculoskeletal system. A novel combination of AG coupled with one-legged squats on a vibrating platform may preserve muscle and bone in the lower limbs to a greater extent than the current exercise paradigm. The benefits of the proposed countermeasure have been analyzed through the development of a simulation platform. Ground reaction force data and motion data were collected using a motion capture system while performing one-legged and two-legged squats in 1-G. The motion was modeled in OpenSim, an open-source software, and inverse dynamics were applied in order to determine the muscle and reaction forces of lower limb joints. Vibration stimulus was modeled by adding a 20 Hz sinusoidal force of 0.5 body weight to the force plate data. From the numerical model in a 1-G acceleration field, muscle forces for quadriceps femoris, plantar flexors and glutei increased substantially for one-legged squats with vibration compared to one- or two-legged squats without vibration. Additionally, joint reaction forces for one-legged squats with vibration also increased significantly compared to two-legged squats with or without vibration. Higher muscle forces and joint reaction forces might help to stimulate muscle activation and bone modeling and thus might reduce musculoskeletal deconditioning. These results indicate that the proposed countermeasure might surpass the performance of the current space countermeasures and should be further studied as a method of mitigating musculoskeletal deconditioning.

Seamount Hydrothermal Systems as Analogies for Ocean Worlds: Reaction Paths Throughout the Lo'ihi Seamount (Hawaii Archipelago)

NASA Astrophysics Data System (ADS)

Milesi, V.; Shock, E.

2018-05-01

Thermodynamic modeling is performed to investigate the possible reaction paths of sea water throughout the Lo'ihi seamount and the associated geochemical supplies of energy that can support autotrophic microbial communities.

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.

Mixing and reactions in multiphase flow through porous media

NASA Astrophysics Data System (ADS)

Jimenez-Martinez, J.; Le Borgne, T.; Meheust, Y.; Porter, M. L.; De Anna, P.; Hyman, J.; Tabuteau, H.; Turuban, R.; Carey, J. W.; Viswanathan, H. S.

2016-12-01

The understanding and quantification of flow and transport processes in multiphase systems remains a grand scientific and engineering challenge in natural and industrial systems (e.g., soils and vadose zone, CO2 sequestration, unconventional oil and gas extraction, enhanced oil recovery). Beyond the kinetic of the chemical reactions, mixing processes in porous media play a key role in controlling both fluid-fluid and fluid-solid reactions. However, conventional continuum-scale models and theories oversimplify and/or ignore many important pore-scale processes. Multiphase flows, with the creation of highly heterogeneous fluid velocity fields (i.e., low velocities regions or stagnation zones, and high velocity regions or preferential paths), makes conservative and reactive transport more complex. We present recent multi-scale experimental developments and theoretical approaches to quantify transport, mixing, and reaction and their coupling with multiphase flows. We discuss our main findings: i) the sustained concentration gradients and enhanced reactivity in a two-phase system for a continuous injection, and the comparison with a pulse line injection; ii) the enhanced mixing by a third mobile-immiscible phase; and iii) the role that capillary forces play in the localization of the fluid-solid reactions. These experimental results are for highly-idealized geometries, however, the proposed models are related to basic porous media and unsaturated flow properties, and could be tested on more complex systems.

Induction Curing of Thiol-acrylate and Thiolene Composite Systems

PubMed Central

Ye, Sheng; Cramer, Neil B.; Stevens, Blake E.; Sani, Robert L.; Bowman, Christopher N.

2011-01-01

Induction curing is demonstrated as a novel type of in situ radiation curing that maintains most of the advantages of photocuring while eliminating the restriction of light accessibility. Induction curing is utilized to polymerize opaque composites comprised of thiol-acrylate and thiol-ene resins, nanoscale magnetic particles, and carbon nanotubes. Nanoscale magnetic particles are dispersed in the resin and upon exposure to the magnetic field, these particles lead to induction heating that rapidly initiates the polymerization. Heat transfer profiles and reaction kinetics of the samples are modeled during the reactions with varying induction heater power, species concentration, species type and sample thickness, and the model is compared with the experimental results. Thiol-ene polymerizations achieved full conversion between 1.5 minutes and 1 hour, depending on the field intensity and the composition, with the maximum reaction temperature decreasing from 146 – 87 °C when the induction heater power was decreased from 8 – 3 kW. The polymerization reactions of the thiol-acrylate system were demonstrated to achieve full conversion between 0.6 and 30 minutes with maximum temperatures from 139 to 86 °C. The experimental behavior was characterized and the temperature profile modeled for the thiol-acrylate composite comprised of sub100nm nickel particles and induction heater power in the range of 32 to 20 kW. A 9°C average deviation was observed between the modeling and experimental results for the maximum temperature rise. The model also was utilized to predict reaction temperatures and kinetics for systems with varying thermal initiator concentration, initiator half-life, monomer molecular weight and temperature gradients in samples with varying thickness, thereby demonstrating that induction curing represents a designable and tunable polymerization method. Finally, induction curing was utilized to cure thiol-acrylate systems containing carbon nanotubes where 1 wt% carbon nanotubes resulted in systems where the storage modulus increased from 17.6 ± 0.2 to 21.6 ± 0.1 MPa and an electrical conductivity that increased from <10−7 to 0.33 ± 0.5 S/m. PMID:21765552

A generalized reaction diffusion model for spatial structure formed by motile cells.

PubMed

Ochoa, F L

1984-01-01

A non-linear stability analysis using a multi-scale perturbation procedure is carried out on a model of a generalized reaction diffusion mechanism which involves only a single equation but which nevertheless exhibits bifurcation to non-uniform states. The patterns generated by this model by variation in a parameter related to the scalar dimensions of domain of definition, indicate its capacity to represent certain key morphogenetic features of multicellular systems formed by motile cells.

Gas-Phase Reaction Pathways and Rate Coefficients for the Dichlorosilane-Hydrogen and Trichlorosilane-Hydrogen Systems

NASA Technical Reports Server (NTRS)

Dateo, Christopher E.; Walch, Stephen P.

2002-01-01

As part of NASA Ames Research Center's Integrated Process Team on Device/Process Modeling and Nanotechnology our goal is to create/contribute to a gas-phase chemical database for use in modeling microelectronics devices. In particular, we use ab initio methods to determine chemical reaction pathways and to evaluate reaction rate coefficients. Our initial studies concern reactions involved in the dichlorosilane-hydrogen (SiCl2H2--H2) and trichlorosilane-hydrogen (SiCl2H-H2) systems. Reactant, saddle point (transition state), and product geometries and their vibrational harmonic frequencies are determined using the complete-active-space self-consistent-field (CASSCF) electronic structure method with the correlation consistent polarized valence double-zeta basis set (cc-pVDZ). Reaction pathways are constructed by following the imaginary frequency mode of the saddle point to both the reactant and product. Accurate energetics are determined using the singles and doubles coupled-cluster method that includes a perturbational estimate of the effects of connected triple excitations (CCSD(T)) extrapolated to the complete basis set limit. Using the data from the electronic structure calculations, reaction rate coefficients are obtained using conventional and variational transition state and RRKM theories.

Computational singular perturbation analysis of stochastic chemical systems with stiffness

DOE PAGES

Wang, Lijin; Han, Xiaoying; Cao, Yanzhao; ...

2017-01-25

Computational singular perturbation (CSP) is a useful method for analysis, reduction, and time integration of stiff ordinary differential equation systems. It has found dominant utility, in particular, in chemical reaction systems with a large range of time scales at continuum and deterministic level. On the other hand, CSP is not directly applicable to chemical reaction systems at micro or meso-scale, where stochasticity plays an non-negligible role and thus has to be taken into account. In this work we develop a novel stochastic computational singular perturbation (SCSP) analysis and time integration framework, and associated algorithm, that can be used to notmore » only construct accurately and efficiently the numerical solutions to stiff stochastic chemical reaction systems, but also analyze the dynamics of the reduced stochastic reaction systems. Furthermore, the algorithm is illustrated by an application to a benchmark stochastic differential equation model, and numerical experiments are carried out to demonstrate the effectiveness of the construction.« less

Contribution of gold nanoparticles to the catalytic DNA strand displacement in leakage reduction and signal amplification.

PubMed

Wang, Bei; Zhou, Xiang; Yao, Dongbao; Sun, Xianbao; He, Miao; Wang, Xiaojing; Yin, Xue; Liang, Haojun

2017-10-03

A new model using a gold nanoparticle (AuNP)-DNA system to constrain leakage and improve efficiency of catalytic toehold-mediated strand displacement reactions was outlined. A 10-bp spacer on AuNPs and fourfold amount of fuels were determined for good performance of this model with an optimized toehold strategy. After the reaction at 25 °C for 10 h, a 258 pM target could be identified, which is a remarkable improvement compared with the traditional AuNP-DNA system without fuel. Moreover, this model was also studied to differentiate specific single nucleotide polymorphism on target with superior selection factors. This model may help by introducing a proposition of target detection to guide further investigation.

A numerical solution for a variable-order reaction-diffusion model by using fractional derivatives with non-local and non-singular kernel

NASA Astrophysics Data System (ADS)

Coronel-Escamilla, A.; Gómez-Aguilar, J. F.; Torres, L.; Escobar-Jiménez, R. F.

2018-02-01

A reaction-diffusion system can be represented by the Gray-Scott model. The reaction-diffusion dynamic is described by a pair of time and space dependent Partial Differential Equations (PDEs). In this paper, a generalization of the Gray-Scott model by using variable-order fractional differential equations is proposed. The variable-orders were set as smooth functions bounded in (0 , 1 ] and, specifically, the Liouville-Caputo and the Atangana-Baleanu-Caputo fractional derivatives were used to express the time differentiation. In order to find a numerical solution of the proposed model, the finite difference method together with the Adams method were applied. The simulations results showed the chaotic behavior of the proposed model when different variable-orders are applied.

Mechanistic Insights into RNA Transphosphorylation from Kinetic Isotope Effects and Linear Free Energy Relationships of Model Reactions

PubMed Central

Chen, Haoyuan; Giese, Timothy J.; Huang, Ming; Wong, Kin-Yiu; Harris, Michael E.; York, Darrin M.

2015-01-01

Phosphoryl transfer reactions are ubiquitous in biology, and the understanding of the mechanisms whereby these reactions are catalyzed by protein and RNA enzymes is central to reveal design principles for new therapeutics. Two of the most powerful experimental probes of chemical mechanism involve the analysis of linear free energy relations (LFERs) and the measurement of kinetic isotope effects (KIEs). These experimental data report directly on differences in bonding between the ground state and the rate-controlling transition state, which is the most critical point along the reaction free energy pathway. However, interpretation of LFER and KIE data in terms of transition state structure and bonding optimally requires the use of theoretical models. In this work, we apply density-functional calculations to determine KIEs for a series of phosphoryl transfer reactions of direct relevance to the 2’-O-transphosphorylation that leads to cleavage of the phosphodiester backbone of RNA. We first examine a well-studied series of phosphate and phosphorothioate mono-, di- and triesters that are useful as mechanistic probes and for which KIEs have been measured. Close agreement is demonstrated between the calculated and measured KIEs, establishing the reliability of our quantum model calculations. Next, we examine a series of RNA transesterification model reactions with a wide range of leaving groups in order to provide a direct connection between observed Brønsted coefficients and KIEs with the structure and bonding in the transition state. These relations can be used for prediction or to aid in the interpretation of experimental data for similar non-enzymatic and enzymatic reactions. Finally, we apply these relations to RNA phosphoryl transfer catalyzed by ribonuclease A, and demonstrate the reaction coordinate-KIE correlation is reasonably preserved. A prediction of the secondary deuterium KIE in this reaction is also provided. These results demonstrate the utility of building up knowledge of mechanism through the systematic study of model systems to provide insight into more complex biological systems such as phosphoryl transfer enzymes and ribozymes. PMID:25223953

Mechanistic insights into RNA transphosphorylation from kinetic isotope effects and linear free energy relationships of model reactions.

PubMed

Chen, Haoyuan; Giese, Timothy J; Huang, Ming; Wong, Kin-Yiu; Harris, Michael E; York, Darrin M

2014-10-27

Phosphoryl transfer reactions are ubiquitous in biology and the understanding of the mechanisms whereby these reactions are catalyzed by protein and RNA enzymes is central to reveal design principles for new therapeutics. Two of the most powerful experimental probes of chemical mechanism involve the analysis of linear free energy relations (LFERs) and the measurement of kinetic isotope effects (KIEs). These experimental data report directly on differences in bonding between the ground state and the rate-controlling transition state, which is the most critical point along the reaction free energy pathway. However, interpretation of LFER and KIE data in terms of transition-state structure and bonding optimally requires the use of theoretical models. In this work, we apply density-functional calculations to determine KIEs for a series of phosphoryl transfer reactions of direct relevance to the 2'-O-transphosphorylation that leads to cleavage of the phosphodiester backbone of RNA. We first examine a well-studied series of phosphate and phosphorothioate mono-, di- and triesters that are useful as mechanistic probes and for which KIEs have been measured. Close agreement is demonstrated between the calculated and measured KIEs, establishing the reliability of our quantum model calculations. Next, we examine a series of RNA transesterification model reactions with a wide range of leaving groups in order to provide a direct connection between observed Brønsted coefficients and KIEs with the structure and bonding in the transition state. These relations can be used for prediction or to aid in the interpretation of experimental data for similar non-enzymatic and enzymatic reactions. Finally, we apply these relations to RNA phosphoryl transfer catalyzed by ribonuclease A, and demonstrate the reaction coordinate-KIE correlation is reasonably preserved. A prediction of the secondary deuterium KIE in this reaction is also provided. These results demonstrate the utility of building up knowledge of mechanism through the systematic study of model systems to provide insight into more complex biological systems such as phosphoryl transfer enzymes and ribozymes. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling Late-State Serpentinization on Enceladus and Implications for Methane-Utilizing Microbial Metabolisms

NASA Astrophysics Data System (ADS)

Hart, R.; Cardace, D.

2017-12-01

Modeling investigations of Enceladus and other icy-satellites have included physicochemical properties (Sohl et al., 2010; Glein et al., 2015; Neveu et al., 2015), geophysical prospects of serpentinization (Malamud and Prialnik, 2016; Vance et al., 2016), and aqueous geochemistry across different antifreeze fluid-rock scenarios (Neveu et al., 2017). To more effectively evaluate the habitability of Enceladus, in the context of recent observations (Waite et al., 2017), we model the potential bioenergetic pathways that would be thermodynamically favorable at the interface of hydrothermal water-rock reactions resulting from late stage serpentinization (>90% serpentinized), hypothesized on Enceladus. Building on previous geochemical model outputs of Enceladus (Neveu et al., 2017), and bioenergetic modeling (as in Amend and Shock, 2001; Cardace et al., 2015), we present a model of late stage serpentinization possible at the water-rock interface of Enceladus, and report changing activities of chemical species related to methane utilization by microbes over the course of serpentinization using the Geochemist's Workbench REACT code [modified Extended Debye-Hückel (Helgeson, 1969) using the thermodynamic database of SUPCRT92 (Johnson et al., 1992)]. Using a model protolith speculated to exist at Enceladus's water-rock boundary, constrained by extraterrestrial analog analytical data for subsurface serpentinites of the Coast Range Ophiolite (Lower Lake, CA, USA) mélange rocks, we deduce evolving habitability conditions as the model protolith reacts with feasible, though hypothetical, planetary ocean chemistries (from Glien et al., 2015, and Neveu et al., 2017). Major components of modeled oceans, Na-Cl, Mg-Cl, and Ca-Cl, show shifts in the feasibility of CO2-CH4-H2 driven microbial habitability, occurring early in the reaction progress, with methanogenesis being bioenergetically favored. Methanotrophy was favored late in the reaction progress of some Na-Cl systems and in the Mg-Cl systems, with shifts in Gibbs Energy values for Mg-Cl systems progressing in the middle of the reaction process. In sum, we show that the bioenergetic yield of fundamental methanogenetic and methanotrophic reactions changes as late stage serpentinization progresses under different Enceladus seawater conditions.

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

PubMed

Du, Bin; Zielinski, Daniel C; Kavvas, Erol S; Dräger, Andreas; Tan, Justin; Zhang, Zhen; Ruggiero, Kayla E; Arzumanyan, Garri A; Palsson, Bernhard O

2016-06-06

The mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question. In this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations. Overall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches.

LSENS, The NASA Lewis Kinetics and Sensitivity Analysis Code

NASA Technical Reports Server (NTRS)

Radhakrishnan, K.

2000-01-01

A general chemical kinetics and sensitivity analysis code for complex, homogeneous, gas-phase reactions is described. The main features of the code, LSENS (the NASA Lewis kinetics and sensitivity analysis code), are its flexibility, efficiency and convenience in treating many different chemical reaction models. The models include: static system; steady, one-dimensional, inviscid flow; incident-shock initiated reaction in a shock tube; and a perfectly stirred reactor. In addition, equilibrium computations can be performed for several assigned states. An implicit numerical integration method (LSODE, the Livermore Solver for Ordinary Differential Equations), which works efficiently for the extremes of very fast and very slow reactions, is used to solve the "stiff" ordinary differential equation systems that arise in chemical kinetics. For static reactions, the code uses the decoupled direct method to calculate sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of dependent variables and/or the rate coefficient parameters. Solution methods for the equilibrium and post-shock conditions and for perfectly stirred reactor problems are either adapted from or based on the procedures built into the NASA code CEA (Chemical Equilibrium and Applications).

Non-steady state mass action dynamics without rate constants: dynamics of coupled reactions using chemical potentials

NASA Astrophysics Data System (ADS)

Cannon, William R.; Baker, Scott E.

2017-10-01

Comprehensive and predictive simulation of coupled reaction networks has long been a goal of biology and other fields. Currently, metabolic network models that utilize enzyme mass action kinetics have predictive power but are limited in scope and application by the fact that the determination of enzyme rate constants is laborious and low throughput. We present a statistical thermodynamic formulation of the law of mass action for coupled reactions at both steady states and non-stationary states. The formulation uses chemical potentials instead of rate constants. When used to model deterministic systems, the method corresponds to a rescaling of the time dependent reactions in such a way that steady states can be reached on the same time scale but with significantly fewer computational steps. The relationships between reaction affinities, free energy changes and generalized detailed balance are central to the discussion. The significance for applications in systems biology are discussed as is the concept and assumption of maximum entropy production rate as a biological principle that links thermodynamics to natural selection.

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.

Nonequilibrium Statistical Mechanics in One Dimension

NASA Astrophysics Data System (ADS)

Privman, Vladimir

2005-08-01

Part I. Reaction-Diffusion Systems and Models of Catalysis; 1. Scaling theories of diffusion-controlled and ballistically-controlled bimolecular reactions S. Redner; 2. The coalescence process, A+A->A, and the method of interparticle distribution functions D. ben-Avraham; 3. Critical phenomena at absorbing states R. Dickman; Part II. Kinetic Ising Models; 4. Kinetic ising models with competing dynamics: mappings, correlations, steady states, and phase transitions Z. Racz; 5. Glauber dynamics of the ising model N. Ito; 6. 1D Kinetic ising models at low temperatures - critical dynamics, domain growth, and freezing S. Cornell; Part III. Ordering, Coagulation, Phase Separation; 7. Phase-ordering dynamics in one dimension A. J. Bray; 8. Phase separation, cluster growth, and reaction kinetics in models with synchronous dynamics V. Privman; 9. Stochastic models of aggregation with injection H. Takayasu and M. Takayasu; Part IV. Random Sequential Adsorption and Relaxation Processes; 10. Random and cooperative sequential adsorption: exactly solvable problems on 1D lattices, continuum limits, and 2D extensions J. W. Evans; 11. Lattice models of irreversible adsorption and diffusion P. Nielaba; 12. Deposition-evaporation dynamics: jamming, conservation laws and dynamical diversity M. Barma; Part V. Fluctuations In Particle and Surface Systems; 13. Microscopic models of macroscopic shocks S. A. Janowsky and J. L. Lebowitz; 14. The asymmetric exclusion model: exact results through a matrix approach B. Derrida and M. R. Evans; 15. Nonequilibrium surface dynamics with volume conservation J. Krug; 16. Directed walks models of polymers and wetting J. Yeomans; Part VI. Diffusion and Transport In One Dimension; 17. Some recent exact solutions of the Fokker-Planck equation H. L. Frisch; 18. Random walks, resonance, and ratchets C. R. Doering and T. C. Elston; 19. One-dimensional random walks in random environment K. Ziegler; Part VII. Experimental Results; 20. Diffusion-limited exciton kinetics in one-dimensional systems R. Kroon and R. Sprik; 21. Experimental investigations of molecular and excitonic elementary reaction kinetics in one-dimensional systems R. Kopelman and A. L. Lin; 22. Luminescence quenching as a probe of particle distribution S. H. Bossmann and L. S. Schulman; Index.

Experimental measurement of binding energy, selectivity, and allostery using fluctuation theorems.

PubMed

Camunas-Soler, Joan; Alemany, Anna; Ritort, Felix

2017-01-27

Thermodynamic bulk measurements of binding reactions rely on the validity of the law of mass action and the assumption of a dilute solution. Yet, important biological systems such as allosteric ligand-receptor binding, macromolecular crowding, or misfolded molecules may not follow these assumptions and may require a particular reaction model. Here we introduce a fluctuation theorem for ligand binding and an experimental approach using single-molecule force spectroscopy to determine binding energies, selectivity, and allostery of nucleic acids and peptides in a model-independent fashion. A similar approach could be used for proteins. This work extends the use of fluctuation theorems beyond unimolecular folding reactions, bridging the thermodynamics of small systems and the basic laws of chemical equilibrium. Copyright © 2017, American Association for the Advancement of Science.

A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models.

PubMed

Reimers, Alexandra-M; Lindhorst, Henning; Waldherr, Steffen

2017-09-06

In this article, we present a protocol for generating a complete (genome-scale) metabolic resource allocation model, as well as a proposal for how to represent such models in the systems biology markup language (SBML). Such models are used to investigate enzyme levels and achievable growth rates in large-scale metabolic networks. Although the idea of metabolic resource allocation studies has been present in the field of systems biology for some years, no guidelines for generating such a model have been published up to now. This paper presents step-by-step instructions for building a (dynamic) resource allocation model, starting with prerequisites such as a genome-scale metabolic reconstruction, through building protein and noncatalytic biomass synthesis reactions and assigning turnover rates for each reaction. In addition, we explain how one can use SBML level 3 in combination with the flux balance constraints and our resource allocation modeling annotation to represent such models.

Furfural formation from the pre-hydrolysis liquor of a hardwood kraft-based dissolving pulp production process.

PubMed

Liu, Haitang; Hu, Huiren; Jahan, M Sarwar; Ni, Yonghao

2013-03-01

This study aimed to produce furfural from the PHL. Results showed best furfural yield of 32.8% and the furfural selectivity of 37.7% in the monophase system (170 °C, 100 min), while they were 60.1% and 69.8%, respectively in the biphase system. The lower furfural selectivity in the monophase system was explained by more side reactions, such as fragmentation, condensation reactions, resinification and others. Model compounds such as: xylose, furfural, syringaldehyde, were used to confirm/identify these side reactions. The addition of dilute sulfuric acid/acetic acid in the system under the same conditions decreased the recovery of furfural. The addition of syringaldehyde into the PHL also led to a decrease in the furfural yield, supporting the conclusion that lignin structures in the PHL may also be involved in the side reactions, thus decreasing the furfural yield. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

A Lagrangian Transport Eulerian Reaction Spatial (LATERS) Markov Model for Prediction of Effective Bimolecular Reactive Transport

NASA Astrophysics Data System (ADS)

Sund, Nicole; Porta, Giovanni; Bolster, Diogo; Parashar, Rishi

2017-11-01

Prediction of effective transport for mixing-driven reactive systems at larger scales, requires accurate representation of mixing at small scales, which poses a significant upscaling challenge. Depending on the problem at hand, there can be benefits to using a Lagrangian framework, while in others an Eulerian might have advantages. Here we propose and test a novel hybrid model which attempts to leverage benefits of each. Specifically, our framework provides a Lagrangian closure required for a volume-averaging procedure of the advection diffusion reaction equation. This hybrid model is a LAgrangian Transport Eulerian Reaction Spatial Markov model (LATERS Markov model), which extends previous implementations of the Lagrangian Spatial Markov model and maps concentrations to an Eulerian grid to quantify closure terms required to calculate the volume-averaged reaction terms. The advantage of this approach is that the Spatial Markov model is known to provide accurate predictions of transport, particularly at preasymptotic early times, when assumptions required by traditional volume-averaging closures are least likely to hold; likewise, the Eulerian reaction method is efficient, because it does not require calculation of distances between particles. This manuscript introduces the LATERS Markov model and demonstrates by example its ability to accurately predict bimolecular reactive transport in a simple benchmark 2-D porous medium.

Application of Tube Dynamics to Non-Statistical Reaction Processes

NASA Astrophysics Data System (ADS)

Gabern, F.; Koon, W. S.; Marsden, J. E.; Ross, S. D.; Yanao, T.

2006-06-01

A technique based on dynamical systems theory is introduced for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. In particular, we merge invariant manifold tube dynamics with Monte Carlo volume determination for accurate rate calculations. This methodology is applied to a three-degree-of-freedom model problem and some ideas on how it might be extended to higher-degree-of-freedom systems are presented.

A Priori Estimation of Organic Reaction Yields

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

Emami, Fateme S.; Vahid, Amir; Wylie, Elizabeth K.

2015-07-21

A thermodynamically guided calculation of free energies of substrate and product molecules allows for the estimation of the yields of organic reactions. The non-ideality of the system and the solvent effects are taken into account through the activity coefficients calculated at the molecular level by perturbed-chain statistical associating fluid theory (PC-SAFT). The model is iteratively trained using a diverse set of reactions with yields that have been reported previously. This trained model can then estimate a priori the yields of reactions not included in the training set with an accuracy of ca. ±15 %. This ability has the potential tomore » translate into significant economic savings through the selection and then execution of only those reactions that can proceed in good yields.« less

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.

DYNAMICS OF MINERAL STRUCTURES AND THE FATE OF METALS IN SOILS AND SEDIMENTS

EPA Science Inventory

Significant progress has been made in elucidating sorption reactions that control the partitioning of metals from solution to mineral surfaces in contaminated soil/sediment systems. Surface complexation models have been developed to quantify the forward reaction with reasonable ...

REDUCTIVE DEHALOGENATION OF HALOMETHANES IN NATURAL AND MODEL SYSTEMS: QSAR ANALYSIS

EPA Science Inventory

Reductive dehalogenation is a dominant reaction pathway for halogenated organics in anoxic environments. Towards the goal of developing predictive tools for this reaction process, the reduction kinetics for a series of halomethanes were measured in batch studies with both natural...

A universal surface complexation framework for modeling proton binding onto bacterial surfaces in geologic settings

USGS Publications Warehouse

Borrok, D.; Turner, B.F.; Fein, J.B.

2005-01-01

Adsorption onto bacterial cell walls can significantly affect the speciation and mobility of aqueous metal cations in many geologic settings. However, a unified thermodynamic framework for describing bacterial adsorption reactions does not exist. This problem originates from the numerous approaches that have been chosen for modeling bacterial surface protonation reactions. In this study, we compile all currently available potentiometric titration datasets for individual bacterial species, bacterial consortia, and bacterial cell wall components. Using a consistent, four discrete site, non-electrostatic surface complexation model, we determine total functional group site densities for all suitable datasets, and present an averaged set of 'universal' thermodynamic proton binding and site density parameters for modeling bacterial adsorption reactions in geologic systems. Modeling results demonstrate that the total concentrations of proton-active functional group sites for the 36 bacterial species and consortia tested are remarkably similar, averaging 3.2 ?? 1.0 (1??) ?? 10-4 moles/wet gram. Examination of the uncertainties involved in the development of proton-binding modeling parameters suggests that ignoring factors such as bacterial species, ionic strength, temperature, and growth conditions introduces relatively small error compared to the unavoidable uncertainty associated with the determination of cell abundances in realistic geologic systems. Hence, we propose that reasonable estimates of the extent of bacterial cell wall deprotonation can be made using averaged thermodynamic modeling parameters from all of the experiments that are considered in this study, regardless of bacterial species used, ionic strength, temperature, or growth condition of the experiment. The average site densities for the four discrete sites are 1.1 ?? 0.7 ?? 10-4, 9.1 ?? 3.8 ?? 10-5, 5.3 ?? 2.1 ?? 10-5, and 6.6 ?? 3.0 ?? 10-5 moles/wet gram bacteria for the sites with pKa values of 3.1, 4.7, 6.6, and 9.0, respectively. It is our hope that this thermodynamic framework for modeling bacteria-proton binding reactions will also provide the basis for the development of an internally consistent set of bacteria-metal binding constants. 'Universal' constants for bacteria-metal binding reactions can then be used in conjunction with equilibrium constants for other important metal adsorption and complexation reactions to calculate the overall distribution of metals in realistic geologic systems.

Evaluation of maillard reaction variables and their effect on heterocyclic amine formation in chemical model systems.

PubMed

Dennis, Cara; Karim, Faris; Smith, J Scott

2015-02-01

Heterocyclic amines (HCAs), highly mutagenic and potentially carcinogenic by-products, form during Maillard browning reactions, specifically in muscle-rich foods. Chemical model systems allow examination of in vitro formation of HCAs while eliminating complex matrices of meat. Limited research has evaluated the effects of Maillard reaction parameters on HCA formation. Therefore, 4 essential Maillard variables (precursors molar concentrations, water amount, sugar type, and sugar amounts) were evaluated to optimize a model system for the study of 4 HCAs: 2-amino-3-methylimidazo-[4,5-f]quinoline, 2-amino-3-methylimidazo[4,5-f]quinoxaline, 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline, and 2-amino-3,4,8-trimethyl-imidazo[4,5-f]quinoxaline. Model systems were dissolved in diethylene glycol, heated at 175 °C for 40 min, and separated using reversed-phase liquid chromatography. To define the model system, precursor amounts (threonine and creatinine) were adjusted in molar increments (0.2/0.2, 0.4/0.4, 0.6/0.6, and 0.8/0.8 mmol) and water amounts by percentage (0%, 5%, 10%, and 15%). Sugars (lactose, glucose, galactose, and fructose) were evaluated in several molar amounts proportional to threonine and creatinine (quarter, half, equi, and double). The precursor levels and amounts of sugar were significantly different (P < 0.05) in regards to total HCA formation, with 0.6/0.6/1.2 mmol producing higher levels. Water concentration and sugar type also had a significant effect (P < 0.05), with 5% water and lactose producing higher total HCA amounts. A model system containing threonine (0.6 mmol), creatinine (0.6 mmol), and glucose (1.2 mmol), with 15% water was determined to be the optimal model system with glucose and 15% water being a better representation of meat systems. © 2015 Institute of Food Technologists®

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.

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.

Organisational Pattern Driven Recovery Mechanisms

NASA Astrophysics Data System (ADS)

Giacomo, Valentina Di; Presenza, Domenico; Riccucci, Carlo

The process of reaction to system failures and security attacks is strongly influenced by its infrastructural, procedural and organisational settings. Analysis of reaction procedures and practices from different domains (Air Traffic Management, Response to Computer Security Incident, Response to emergencies, recovery in Chemical Process Industry) highlight three key requirements for this activity: smooth collaboration and coordination among responders, accurate monitoring and management of resources and ability to adapt pre-established reaction plans to the actual context. The SERENITY Reaction Mechanisms (SRM) is the subsystem of the SERENITY Run-time Framework aimed to provide SERENITY aware AmI settings (i.e. socio-technical systems with highly distributed dynamic services) with functionalities to implement applications specific reaction strategies. The SRM uses SERENITY Organisational S&D Patterns as run-time models to drive these three key functionalities.

A Scalable Computational Framework for Establishing Long-Term Behavior of Stochastic Reaction Networks

PubMed Central

Khammash, Mustafa

2014-01-01

Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed. PMID:24968191

Numerical quantification of habitability in serpentinizing systems

NASA Astrophysics Data System (ADS)

Som, S.; Alperin, M. J.; Hoehler, T. M.

2012-12-01

The likely presence of liquid water in contact with olivine-bearing rocks on Mars, the detection of serpentine minerals and of methane emissions possibly consistent with serpentinization, and the observation of serpentine-associated methane-cycling communities on Earth have all led to excitement over the potential of such systems to host life on Mars, even into the present day. However, the habitability of subsurface serpentinizing systems on Mars does not necessarily follow from these qualitative observations. In particular, while the production of H2 during serpentinization could provide methanogens with a needed substrate, the alkaline conditions and corresponding potential for carbon limitation that arise in concert are negatives against which H2 supply must be balanced. We considered this balance via a coupled geochemical-bioenergetic model that weighs the outputs of serpentinization against the metabolic requirements of methanogenesis, in an energetic frame of reference. Serpentinization is modeled using the "Geochemist's Workbench" (GWB) whereby ultramafic harzburgite rocks are reacted with oxygen and sulfate depleted seawater. Reaction kinetics are not explicitly considered, but comparable effects of partial reaction are approximated by assuming post-reaction dilution of equilibrated fluids. The output of GWB serves as the input to the bioenergetic model, which calculates methanogenic energy yields based on spherically-symmetrical diffusion of substrates to a cell followed by reaction at the diffusion-limited rate. Membrane selectivity for substrate transport is explicitly considered. Results will be report updates for two scenarios: (i) High temperature serpentinization followed by cooling and transport of equilibrated fluid to a lower temperature regime accessible to biology; (ii) Serpentinization within the biologically-tolerated range of temperatures. Such coupled models demonstrate that environmental variability with respect to both water-rock reaction, temperature, and biologically-mediated methanogenesis drive orders of magnitude variability in the energy available in methanogenic metabolism.

Gas-phase reactions of uranate ions, UO(2)(-), UO(3)(-), UO(4)(-), and UO(4)H(-), with methanol: a convergence of experiment and theory.

PubMed

Michelini, Maria Del Carmen; Marçalo, Joaquim; Russo, Nino; Gibson, John K

2010-04-19

Bimolecular reactions of uranium oxide molecular anions with methanol have been studied experimentally, by Fourier transform ion cyclotron resonance mass spectrometry, and computationally, by density functional theory (DFT). The primary goals were to provide fundamental insights into mechanistic and structural details of model reactions of uranium oxides with organics, and to examine the validity of theoretical modeling of these types of reactions. The ions UO(3)(-), UO(4)(-), and UO(4)H(-) each reacted with methanol to give a singular product; the primary products each exhibited sequential reactions with two additional methanol molecules to again give singular products. The observed reactions were elimination of water, formaldehyde, or hydrogen, and in one case addition of a methanol molecule. The potential energy profiles were computed for each reaction, and isotopic labeling experiments were performed to probe the validity of the computed mechanisms and structures-in each case where the experiments could be compared with the theory there was concurrence, clearly establishing the efficacy of the employed DFT methodologies for these and related reaction systems. The DFT results were furthermore in accord with the surprisingly inert nature of UO(2)(-). The results provide a basis to understand mechanisms of key reactions of uranium oxides with organics, and a foundation to extend DFT methodologies to more complex actinide systems which are not amenable to such direct experimental studies.

Smouldering (thermal) remediation of soil contaminated with industrial organic liquids: novel insights into heat transfer and kinetics uncovered by integrating experiments and modelling

NASA Astrophysics Data System (ADS)

Gerhard, J.; Zanoni, M. A. B.; Torero, J. L.

2017-12-01

Smouldering (i.e., flameless combustion) underpins the technology Self-sustaining Treatment for Active Remediation (STAR). STAR achieves the in situ destruction of nonaqueous phase liquids (NAPLs) by generating a self-sustained smouldering reaction that propagates through the source zone. This research explores the nature of the travelling reaction and the influence of key in situ and engineered characteristics. A novel one-dimensional numerical model was developed (in COMSOL) to simulate the smouldering remediation of bitumen-contaminated sand. This model was validated against laboratory column experiments. Achieving model validation depended on correctly simulating the energy balance at the reaction front, including properly accounting for heat transfer, smouldering kinetics, and heat losses. Heat transfer between soil and air was demonstrated to be generally not at equilibrium. Moreover, existing heat transfer correlations were found to be inappropriate for the low air flow Reynold's numbers (Re < 30) relevant in this and similar thermal remediation systems. Therefore, a suite of experiments were conducted to generate a new heat transfer correlation, which generated correct simulations of convective heat flow through soil. Moreover, it was found that, for most cases of interest, a simple two-step pyrolysis/oxidation set of kinetic reactions was sufficient. Arrhenius parameters, calculated independently from thermogravimetric experiments, allowed the reaction kinetics to be validated in the smouldering model. Furthermore, a simple heat loss term sufficiently accounted for radial heat losses from the column. Altogether, these advances allow this simple model to reasonably predict the self-sustaining process including the peak reaction temperature, the reaction velocity, and the complete destruction of bitumen behind the front. Simulations with the validated model revealed numerous unique insights, including how the system inherently recycles energy, how air flow rate and NAPL saturation dictate contaminant destruction rates, and the extremes that lead to extinction. Overall, this research provides unique insights into the complex interplay of thermochemical processes that govern the success of smouldering as well as other thermal remediation approaches.

Modeling heat dissipation at the nanoscale: an embedding approach for chemical reaction dynamics on metal surfaces.

PubMed

Meyer, Jörg; Reuter, Karsten

2014-04-25

We present an embedding technique for metallic systems that makes it possible to model energy dissipation into substrate phonons during surface chemical reactions from first principles. The separation of chemical and elastic contributions to the interaction potential provides a quantitative description of both electronic and phononic band structure. Application to the dissociation of O2 at Pd(100) predicts translationally "hot" oxygen adsorbates as a consequence of the released adsorption energy (ca. 2.6 eV). This finding questions the instant thermalization of reaction enthalpies generally assumed in models of heterogeneous catalysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Numerical simulation of the interaction of transport, diffusion and chemical reactions in an urban plume

NASA Technical Reports Server (NTRS)

Vogel, Bernhard; Vogel, Heike; Fiedler, Franz

1994-01-01

A model system is presented that takes into account the main physical and chemical processes on the regional scale here in an area of 100x100 sq km. The horizontal gridsize used is 2x2 sq km. For a case study, it is demonstrated how the model system can be used to separate the contributions of the processes advection, turbulent diffusion, and chemical reactions to the diurnal cycle of ozone. In this way, typical features which are visible in observations and are reproduced by the numerical simulations can be interpreted.

A metabolite-centric view on flux distributions in genome-scale metabolic models

PubMed Central

2013-01-01

Background Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. Results We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. Conclusions The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological interpretations that are not apparent from isolated reaction fluxes. Particularly powerful demonstrations of this are the analyses of the complete metabolic contexts of energy metabolism and the folate-dependent one-carbon pool presented in this work. Finally, a metabolite-centric view on flux distributions can guide the refinement of metabolic reconstructions for specific growth scenarios. PMID:23587327

A surface complexation and ion exchange model of Pb and Cd competitive sorption on natural soils

NASA Astrophysics Data System (ADS)

Serrano, Susana; O'Day, Peggy A.; Vlassopoulos, Dimitri; García-González, Maria Teresa; Garrido, Fernando

2009-02-01

The bioavailability and fate of heavy metals in the environment are often controlled by sorption reactions on the reactive surfaces of soil minerals. We have developed a non-electrostatic equilibrium model (NEM) with both surface complexation and ion exchange reactions to describe the sorption of Pb and Cd in single- and binary-metal systems over a range of pH and metal concentration. Mineralogical and exchange properties of three different acidic soils were used to constrain surface reactions in the model and to estimate surface densities for sorption sites, rather than treating them as adjustable parameters. Soil heterogeneity was modeled with >FeOH and >SOH functional groups, representing Fe- and Al-oxyhydroxide minerals and phyllosilicate clay mineral edge sites, and two ion exchange sites (X - and Y -), representing clay mineral exchange. An optimization process was carried out using the entire experimental sorption data set to determine the binding constants for Pb and Cd surface complexation and ion exchange reactions. Modeling results showed that the adsorption of Pb and Cd was distributed between ion exchange sites at low pH values and specific adsorption sites at higher pH values, mainly associated with >FeOH sites. Modeling results confirmed the greater tendency of Cd to be retained on exchange sites compared to Pb, which had a higher affinity than Cd for specific adsorption on >FeOH sites. Lead retention on >FeOH occurred at lower pH than for Cd, suggesting that Pb sorbs to surface hydroxyl groups at pH values at which Cd interacts only with exchange sites. The results from the binary system (both Pb and Cd present) showed that Cd retained in >FeOH sites decreased significantly in the presence of Pb, while the occupancy of Pb in these sites did not change in the presence of Cd. As a consequence of this competition, Cd was shifted to ion exchange sites, where it competes with Pb and possibly Ca (from the background electrolyte). Sorption on >SOH functional groups increased with increasing pH but was small compared to >FeOH sites, with little difference between single- and binary-metal systems. Model reactions and conditional sorption constants for Pb and Cd sorption were tested on a fourth soil that was not used for model optimization. The same reactions and constants were used successfully without adjustment by estimating surface site concentrations from soil mineralogy. The model formulation developed in this study is applicable to acidic mineral soils with low organic matter content. Extension of the model to soils of different composition may require selection of surface reactions that account for differences in clay and oxide mineral composition and organic matter content.

Determination of osthol and its metabolites in a phase I reaction system and the Caco-2 cell model by HPLC-UV and LC-MS/MS

PubMed Central

Yuan, Zhenting; Xu, Haiyan; Wang, Ke; Zhao, Zhonghua; Hu, Ming

2012-01-01

A straightforward and sensitive reversed-phase high-performance liquid chromatography (HPLC) assay was developed and validated for the analysis of osthol and its phase I metabolites (internal standard: umbelliferone). The method was validated for the determination of osthol with respect to selectivity, precision, linearity, limit of detection, recovery, and stability. The linear response range was 0.47 ~ 60 μM, and the average recoveries ranged from 98 to 101%. The inter-day and intra-day relative standard deviations were both less than 5%. Using this method, we showed that more than 80% of osthol was metabolized in 20 min in a phase I metabolic reaction system. Transport experiments in the Caco-2 cell culture model indicated that osthol was easily absorbed with high absorptive permeability (>10×10-6 cm/sec). The permeability did not display concentration-dependence or vectorial-dependence and is mildly temperature sensitive (activation energy less than 10 Kcal/mole), indicating passive mechanism of transport. When analyzed by LC-MS/MS, five metabolites were detected in a phase I reaction system and in the receiver side of a modified Caco-2 cell model, which was supplemented with the phase I reaction system. The major metabolites appeared to be desmethyl-osthol and multiple isomers of dehydro-osthol. In conclusion, a likely cause of poor osthol bioavailability is rapid phase I metabolism via the cytochrome P-450 pathways. PMID:19304430

Development of the Monolith Froth Reactor for Catalytic Wet Oxidation of CELSS Model Wastes

NASA Technical Reports Server (NTRS)

Abraham, Martin; Fisher, John W.

1995-01-01

The aqueous phase oxidation of acetic acid, used as a model compound for the treatment of CELSS (Controlled Ecological Life Support System) waste, was carried out in the monolith froth reactor which utilizes two-phase flow in the monolith channels. The catalytic oxidation of acetic acid was carried out over a Pt/Al2O3 catalyst, prepared at The University of Tulsa, at temperatures and pressures below the critical point of water. The effect of externally controllable parameters (temperature, liquid flow rate, distributor plate orifice size, pitch, and catalyst distance from the distributor plate) on the rate of acetic acid oxidation was investigated. Results indicate reaction rate increased with increasing temperature and exhibited a maximum with respect to liquid flow rate. The apparent activation energy calculated from reaction rate data was 99.7 kJ/mol. This value is similar to values reported for the oxidation of acetic acid in other systems and is comparable to intrinsic values calculated for oxidation reactions. The kinetic data were modeled using simple power law kinetics. The effect of "froth" feed system characteristics was also investigated. Results indicate that the reaction rate exhibits a maximum with respect to distributor plate orifice size, pitch, and catalyst distance from the distributor plate. Fundamental results obtained were used to extrapolate where the complete removal of acetic acid would be obtained and for the design and operation of a full scale CELSS treatment system.

Nonlinear Chemical Dynamics and Synchronization

NASA Astrophysics Data System (ADS)

Li, Ning

Alan Turing's work on morphogenesis, more than half a century ago, continues to motivate and inspire theoretical and experimental biologists even today. That said, there are very few experimental systems for which Turing's theory is applicable. In this thesis we present an experimental reaction-diffusion system ideally suited for testing Turing's ideas in synthetic "cells" consisting of microfluidically produced surfactant-stabilized emulsions in which droplets containing the Belousov-Zhabotinsky (BZ) oscillatory chemical reactants are dispersed in oil. The BZ reaction has become the prototype of nonlinear dynamics in chemistry and a preferred system for exploring the behavior of coupled nonlinear oscillators. Our system consists of a surfactant stabilized monodisperse emulsion of drops of aqueous BZ solution dispersed in a continuous phase of oil. In contrast to biology, here the chemistry is understood, rate constants are measured and interdrop coupling is purely diffusive. We explore a large set of parameters through control of rate constants, drop size, spacing, and spatial arrangement of the drops in lines and rings in one-dimension (1D) and hexagonal arrays in two-dimensions (2D). The Turing model is regarded as a metaphor for morphogenesis in biology but not for prediction. Here, we develop a quantitative and falsifiable reaction-diffusion model that we experimentally test with synthetic cells. We quantitatively establish the extent to which the Turing model in 1D describes both stationary pattern formation and temporal synchronization of chemical oscillators via reaction-diffusion and in 2D demonstrate that chemical morphogenesis drives physical differentiation in synthetic cells.

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.

Anomalous anisotropies of fission fragments in near- and sub-barrier fusion-fussion reactions

NASA Astrophysics Data System (ADS)

Huanqiao, Zhang; Zuhua, Liu; Jincheng, Xu; Jun, Lu; Ming, Ruan; Kan, Xu

1992-03-01

Fission cross sections and angular distributions have been measured for the reactions of 16O + 232Th and238U, and19F + 208Pb and232Th at near- and sub-barrier energies. The fission excitation functions are rather well reproduced on the basis of Wong model or coupled channels theory. However, the models which reproduce the sub-barrier fusion cross sections fail to account for the experimental anisotropies of fission fragments. It is found that the observed anisotropies are much larger than expected. For the first time it has been observed that the anisotropies as a function of the center-of-mass energy show a peak centered near 4.5 MeV below the fusion barrier for several reaction systems. The present approaches fail to explain these anomalies. For 19F + 208Pb systems, our results confirm the prediction of an approximately constant value for the mean square spin of the compound nucleus produced in far sub-barrier fusion reaction.

In-liquid arc plasma jet and its application to phenol degradation

NASA Astrophysics Data System (ADS)

Liu, Jing-Lin; Park, Hyun-Woo; Hamdan, Ahmad; Cha, Min Suk

2018-03-01

We present a new method for achieving chemical reactions induced by plasmas with liquids—an in-liquid arc plasma jet system—designed to have a few advantages over the existing methods. High-speed imaging and optical emission spectroscopy were adopted to highlight the physical aspects of the in-liquid arc plasma jet system, and the feasibility of the system was investigated in a wastewater treatment case with phenol as the model contaminant. We found that the specific energy input is a reasonable parameter by which to characterize the overall process. The phenol removal reaction could be modeled as a pseudo-first-order reaction, and the reaction constant became smaller as the phenol concentration increased. However, complete decomposition of the phenol into water and carbon dioxide required very high energy because the final intermediate, oxalic acid, is relatively stable. Detailed chemical and physical analyses, including byproducts, ions, solution acidity, and conductivity, were conducted to evaluate this new method for use in the appropriate applications.

Systematic development of reduced reaction mechanisms for dynamic modeling

NASA Technical Reports Server (NTRS)

Frenklach, M.; Kailasanath, K.; Oran, E. S.

1986-01-01

A method for systematically developing a reduced chemical reaction mechanism for dynamic modeling of chemically reactive flows is presented. The method is based on the postulate that if a reduced reaction mechanism faithfully describes the time evolution of both thermal and chain reaction processes characteristic of a more complete mechanism, then the reduced mechanism will describe the chemical processes in a chemically reacting flow with approximately the same degree of accuracy. Here this postulate is tested by producing a series of mechanisms of reduced accuracy, which are derived from a full detailed mechanism for methane-oxygen combustion. These mechanisms were then tested in a series of reactive flow calculations in which a large-amplitude sinusoidal perturbation is applied to a system that is initially quiescent and whose temperature is high enough to start ignition processes. Comparison of the results for systems with and without convective flow show that this approach produces reduced mechanisms that are useful for calculations of explosions and detonations. Extensions and applicability to flames are discussed.

Continuous protein concentration via free-flow moving reaction boundary electrophoresis.

PubMed

Kong, Fanzhi; Zhang, Min; Chen, Jingjing; Fan, Liuyin; Xiao, Hua; Liu, Shaorong; Cao, Chengxi

2017-07-28

In this work, we developed the model and theory of free-flow moving reaction boundary electrophoresis (FFMRB) for continuous protein concentration for the first time. The theoretical results indicated that (i) the moving reaction boundary (MRB) can be quantitatively designed in free-flow electrophoresis (FFE) system; (ii) charge-to-mass ratio (Z/M) analysis could provide guidance for protein concentration optimization; and (iii) the maximum processing capacity could be predicted. To demonstrate the model and theory, three model proteins of hemoglobin (Hb), cytochrome C (Cyt C) and C-phycocyanin (C-PC) were chosen for the experiments. The experimental results verified that (i) stable MRBs with different velocities could be established in FFE apparatus with weak acid/weak base neutralization reaction system; (ii) proteins of Hb, Cyt C and C-PC were well concentrated with FFMRB; and (iii) a maximum processing capacity and recovery ratio of Cyt C enrichment were 126mL/h and 95.5% respectively, and a maximum enrichment factor was achieved 12.6 times for Hb. All of the experiments demonstrated the protein concentration model and theory. In contrast to other methods, the continuous processing ability enables FFMRB to efficiently enrich diluted protein or peptide in large volume solution. Copyright © 2017 Elsevier B.V. All rights reserved.

Primal-mixed formulations for reaction-diffusion systems on deforming domains

NASA Astrophysics Data System (ADS)

Ruiz-Baier, Ricardo

2015-10-01

We propose a finite element formulation for a coupled elasticity-reaction-diffusion system written in a fully Lagrangian form and governing the spatio-temporal interaction of species inside an elastic, or hyper-elastic body. A primal weak formulation is the baseline model for the reaction-diffusion system written in the deformed domain, and a finite element method with piecewise linear approximations is employed for its spatial discretization. On the other hand, the strain is introduced as mixed variable in the equations of elastodynamics, which in turn acts as coupling field needed to update the diffusion tensor of the modified reaction-diffusion system written in a deformed domain. The discrete mechanical problem yields a mixed finite element scheme based on row-wise Raviart-Thomas elements for stresses, Brezzi-Douglas-Marini elements for displacements, and piecewise constant pressure approximations. The application of the present framework in the study of several coupled biological systems on deforming geometries in two and three spatial dimensions is discussed, and some illustrative examples are provided and extensively analyzed.

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.

Unimolecular diffusion-mediated reactions with a nonrandom time-modulated absorbing barrier

NASA Technical Reports Server (NTRS)

Bashford, D.; Weaver, D. L.

1986-01-01

A diffusion-reaction model with time-dependent reactivity is formulated and applied to unimolecular reactions. The model is solved exactly numerically and approximately analytically for the unreacted fraction as a function of time. It is shown that the approximate analytical solution is valid even when the system is far from equilibrium, and when the reactivity probability is more complicated than a square-wave function of time. A discussion is also given of an approach to problems of this type using a stochastically fluctuating reactivity, and the first-passage time for a particular example is derived.

Could Intelligent Tutors Anticipate Successfully User Reactions?

NASA Astrophysics Data System (ADS)

Kalisz, Eugenia; Florea, Adina Magda

2006-06-01

Emotions have been shown to have an important impact on several human processes such as decision-making, planning, cognition, and learning. In an e-learning system, an artificial tutor capable of effectively understanding and anticipating the student emotions during learning will have a significantly enhanced role. The paper presents a model of an artificial tutor endowed with synthesized emotions according to the BDE model, previously developed by the authors. It also analyzes possible student reactions while interacting with the learning material and the way the artificial tutor could anticipate and should respond to these reactions, with adequate actions.

Discreteness effects in a reacting system of particles with finite interaction radius.

PubMed

Berti, S; López, C; Vergni, D; Vulpiani, A

2007-09-01

An autocatalytic reacting system with particles interacting at a finite distance is studied. We investigate the effects of the discrete-particle character of the model on properties like reaction rate, quenching phenomenon, and front propagation, focusing on differences with respect to the continuous case. We introduce a renormalized reaction rate depending both on the interaction radius and the particle density, and we relate it to macroscopic observables (e.g., front speed and front thickness) of the system.

Synthesis of a correcting filter with phase stabilization of the angular velocity of a synchronous motor by the feedback system method

NASA Technical Reports Server (NTRS)

Kazlauskas, K. A.; Kurlavichus, A. I.

1973-01-01

The operating characteristics of a synchronous electric motor are discussed. A system of phase stabilization of the instantaneous angular velocity of rotation of a synchronous-reaction motor is diagrammed. A mathematical model is developed to show the parameters which affect the operation of the motor. The selection of a correcting filter to use with the motor in order to reduce the reaction of the system to interference is explained.

Hybrid stochastic simulation of reaction-diffusion systems with slow and fast dynamics.

PubMed

Strehl, Robert; Ilie, Silvana

2015-12-21

In this paper, we present a novel hybrid method to simulate discrete stochastic reaction-diffusion models arising in biochemical signaling pathways. We study moderately stiff systems, for which we can partition each reaction or diffusion channel into either a slow or fast subset, based on its propensity. Numerical approaches missing this distinction are often limited with respect to computational run time or approximation quality. We design an approximate scheme that remedies these pitfalls by using a new blending strategy of the well-established inhomogeneous stochastic simulation algorithm and the tau-leaping simulation method. The advantages of our hybrid simulation algorithm are demonstrated on three benchmarking systems, with special focus on approximation accuracy and efficiency.

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.

A comprehensive model to determine the effects of temperature and species fluctuations on reaction rates in turbulent reacting flows

NASA Technical Reports Server (NTRS)

Chinitz, W.; Foy, E.; Rowan, G.; Goldstein, D.

1982-01-01

The use of probability theory to determine the effects of turbulent fluctuations on reaction rates in turbulent combustion systems is briefly reviewed. Results are presented for the effect of species fluctuations in particular. It is found that turbulent fluctuations of species act to reduce the reaction rates, in contrast with the temperature fluctuations previously determined to increase Arrhenius reaction rate constants. For the temperature fluctuations, a criterion is set forth for determining if, in a given region of a turbulent flow field, the temperature can be expected to exhibit ramp like fluctuations. Using the above results, along with results previously obtained, a model is described for testing the effects of turbulent fluctuations of temperature and species on reaction rates in computer programs dealing with turbulent reacting flows. An alternative model which employs three variable probability density functions (temperature and two species) and is currently being formulated is discussed as well.

Enhanced Furfural Yields from Xylose Dehydration in the gamma-Valerolactone/Water Solvent System at Elevated Temperatures.

PubMed

Sener, Canan; Motagamwala, Ali Hussain; Alonso, David Martin; Dumesic, James

2018-05-18

High yields of furfural (>90%) were achieved from xylose dehydration in a sustainable solvent system composed of -valerolactone (GVL), a biomass derived solvent, and water. It is identified that high reaction temperatures (e.g., 498 K) are required to achieve high furfural yield. Additionally, it is shown that the furfural yield at these temperatures is independent of the initial xylose concentration, and high furfural yield is obtained for industrially relevant xylose concentrations (10 wt%). A reaction kinetics model is developed to describe the experimental data obtained with solvent system composed of 80 wt% GVL and 20 wt% water across the range of reaction conditions studied (473 - 523 K, 1-10 mM acid catalyst, 66 - 660 mM xylose concentration). The kinetic model demonstrates that furfural loss due to bimolecular condensation of xylose and furfural is minimized at elevated temperature, whereas carbon loss due to xylose degradation increases with increasing temperature. Accordingly, the optimal temperature range for xylose dehydration to furfural in the GVL/H2O solvent system is identified to be from 480 to 500 K. Under these reaction conditions, furfural yield of 93% is achieved at 97% xylan conversion from lignocellulosic biomass (maple wood). © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comparison of quantitative methods for clinical imaging with hyperpolarized (13)C-pyruvate.

PubMed

Daniels, Charlie J; McLean, Mary A; Schulte, Rolf F; Robb, Fraser J; Gill, Andrew B; McGlashan, Nicholas; Graves, Martin J; Schwaiger, Markus; Lomas, David J; Brindle, Kevin M; Gallagher, Ferdia A

2016-04-01

Dissolution dynamic nuclear polarization (DNP) enables the metabolism of hyperpolarized (13)C-labelled molecules, such as the conversion of [1-(13)C]pyruvate to [1-(13)C]lactate, to be dynamically and non-invasively imaged in tissue. Imaging of this exchange reaction in animal models has been shown to detect early treatment response and correlate with tumour grade. The first human DNP study has recently been completed, and, for widespread clinical translation, simple and reliable methods are necessary to accurately probe the reaction in patients. However, there is currently no consensus on the most appropriate method to quantify this exchange reaction. In this study, an in vitro system was used to compare several kinetic models, as well as simple model-free methods. Experiments were performed using a clinical hyperpolarizer, a human 3 T MR system, and spectroscopic imaging sequences. The quantitative methods were compared in vivo by using subcutaneous breast tumours in rats to examine the effect of pyruvate inflow. The two-way kinetic model was the most accurate method for characterizing the exchange reaction in vitro, and the incorporation of a Heaviside step inflow profile was best able to describe the in vivo data. The lactate time-to-peak and the lactate-to-pyruvate area under the curve ratio were simple model-free approaches that accurately represented the full reaction, with the time-to-peak method performing indistinguishably from the best kinetic model. Finally, extracting data from a single pixel was a robust and reliable surrogate of the whole region of interest. This work has identified appropriate quantitative methods for future work in the analysis of human hyperpolarized (13)C data. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

Pulse-density modulation control of chemical oscillation far from equilibrium in a droplet open-reactor system

PubMed Central

Sugiura, Haruka; Ito, Manami; Okuaki, Tomoya; Mori, Yoshihito; Kitahata, Hiroyuki; Takinoue, Masahiro

2016-01-01

The design, construction and control of artificial self-organized systems modelled on dynamical behaviours of living systems are important issues in biologically inspired engineering. Such systems are usually based on complex reaction dynamics far from equilibrium; therefore, the control of non-equilibrium conditions is required. Here we report a droplet open-reactor system, based on droplet fusion and fission, that achieves dynamical control over chemical fluxes into/out of the reactor for chemical reactions far from equilibrium. We mathematically reveal that the control mechanism is formulated as pulse-density modulation control of the fusion–fission timing. We produce the droplet open-reactor system using microfluidic technologies and then perform external control and autonomous feedback control over autocatalytic chemical oscillation reactions far from equilibrium. We believe that this system will be valuable for the dynamical control over self-organized phenomena far from equilibrium in chemical and biomedical studies. PMID:26786848

Pulse-density modulation control of chemical oscillation far from equilibrium in a droplet open-reactor system.

PubMed

Sugiura, Haruka; Ito, Manami; Okuaki, Tomoya; Mori, Yoshihito; Kitahata, Hiroyuki; Takinoue, Masahiro

2016-01-20

The design, construction and control of artificial self-organized systems modelled on dynamical behaviours of living systems are important issues in biologically inspired engineering. Such systems are usually based on complex reaction dynamics far from equilibrium; therefore, the control of non-equilibrium conditions is required. Here we report a droplet open-reactor system, based on droplet fusion and fission, that achieves dynamical control over chemical fluxes into/out of the reactor for chemical reactions far from equilibrium. We mathematically reveal that the control mechanism is formulated as pulse-density modulation control of the fusion-fission timing. We produce the droplet open-reactor system using microfluidic technologies and then perform external control and autonomous feedback control over autocatalytic chemical oscillation reactions far from equilibrium. We believe that this system will be valuable for the dynamical control over self-organized phenomena far from equilibrium in chemical and biomedical studies.

The HNC/HCN ratio in star-forming regions

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

Graninger, Dawn M.; Öberg, Karin I.; Herbst, Eric

2014-05-20

HNC and HCN, typically used as dense gas tracers in molecular clouds, are a pair of isomers that have great potential as a temperature probe because of temperature dependent, isomer-specific formation and destruction pathways. Previous observations of the HNC/HCN abundance ratio show that the ratio decreases with increasing temperature, something that standard astrochemical models cannot reproduce. We have undertaken a detailed parameter study on which environmental characteristics and chemical reactions affect the HNC/HCN ratio and can thus contribute to the observed dependence. Using existing gas and gas-grain models updated with new reactions and reaction barriers, we find that in staticmore » models the H + HNC gas-phase reaction regulates the HNC/HCN ratio under all conditions, except for very early times. We quantitatively constrain the combinations of H abundance and H + HNC reaction barrier that can explain the observed HNC/HCN temperature dependence and discuss the implications in light of new quantum chemical calculations. In warm-up models, gas-grain chemistry contributes significantly to the predicted HNC/HCN ratio and understanding the dynamics of star formation is therefore key to model the HNC/HCN system.« less

Modeling Interfacial Glass-Water Reactions: Recent Advances and Current Limitations

DOE PAGES

Pierce, Eric M.; Frugier, Pierre; Criscenti, Louise J.; ...

2014-07-12

Describing the reactions that occur at the glass-water interface and control the development of the altered layer constitutes one of the main scientific challenges impeding existing models from providing accurate radionuclide release estimates. Radionuclide release estimates are a critical component of the safety basis for geologic repositories. The altered layer (i.e., amorphous hydrated surface layer and crystalline reaction products) represents a complex region, both physically and chemically, sandwiched between two distinct boundaries pristine glass surface at the inner most interface and aqueous solution at the outer most interface. Computational models, spanning different length and time-scales, are currently being developed tomore » improve our understanding of this complex and dynamic process with the goal of accurately describing the pore-scale changes that occur as the system evolves. These modeling approaches include geochemical simulations [i.e., classical reaction path simulations and glass reactivity in allowance for alteration layer (GRAAL) simulations], Monte Carlo simulations, and Molecular Dynamics methods. Finally, in this manuscript, we discuss the advances and limitations of each modeling approach placed in the context of the glass-water reaction and how collectively these approaches provide insights into the mechanisms that control the formation and evolution of altered layers.« less

Predictors of severe systemic anaphylactic reactions in patients with Hymenoptera venom allergy: importance of baseline serum tryptase-a study of the European Academy of Allergology and Clinical Immunology Interest Group on Insect Venom Hypersensitivity.

PubMed

Ruëff, Franziska; Przybilla, Bernhard; Biló, Maria Beatrice; Müller, Ulrich; Scheipl, Fabian; Aberer, Werner; Birnbaum, Joëlle; Bodzenta-Lukaszyk, Anna; Bonifazi, Floriano; Bucher, Christoph; Campi, Paolo; Darsow, Ulf; Egger, Cornelia; Haeberli, Gabrielle; Hawranek, Thomas; Körner, Michael; Kucharewicz, Iwona; Küchenhoff, Helmut; Lang, Roland; Quercia, Oliviero; Reider, Norbert; Severino, Maurizio; Sticherling, Michael; Sturm, Gunter Johannes; Wüthrich, Brunello

2009-11-01

Severe anaphylaxis to honeybee or vespid stings is associated with a variety of risk factors, which are poorly defined. Our aim was to evaluate the association of baseline serum tryptase concentrations and other variables routinely recorded during patient evaluation with the frequency of past severe anaphylaxis after a field sting. In this observational multicenter study, we enrolled 962 patients with established bee or vespid venom allergy who had a systemic reaction after a field sting. Data were collected on tryptase concentration, age, sex, culprit insect, cardiovascular medication, and the number of preceding minor systemic reactions before the index field sting. A severe reaction was defined as anaphylactic shock, loss of consciousness, or cardiopulmonary arrest. The index sting was defined as the hitherto first, most severe systemic field-sting reaction. Relative rates were calculated with generalized additive models. Two hundred six (21.4%) patients had a severe anaphylactic reaction after a field sting. The frequency of this event increased significantly with higher tryptase concentrations (nonlinear association). Other factors significantly associated with severe reactions after a field sting were vespid venom allergy, older age, male sex, angiotensin-converting enzyme inhibitor medication, and 1 or more preceding field stings with a less severe systemic reaction. In patients with honeybee or vespid venom allergy, baseline serum tryptase concentrations are associated with the risk for severe anaphylactic reactions. Preventive measures should include substitution of angiotensin-converting enzyme inhibitors.

Tracking the behavior of Maillard browning in lysine/arginine-sugar model systems under high hydrostatic pressure.

PubMed

Ma, Xiao-Juan; Gao, Jin-Yan; Tong, Ping; Li, Xin; Chen, Hong-Bing

2017-12-01

High-pressure processing is gaining popularity in the food industry. However, its effect on the Maillard reaction during high-pressure-assisted pasteurization and sterilization is not well documented. This study aimed to investigate the effects of high hydrostatic pressure on the Maillard reaction during these processes using amino acid (lysine or arginine)-sugar (glucose or fructose) solution models. High pressure retarded the intermediate and final stages of the Maillard reaction in the lysine-sugar model. For the lysine-glucose model, the degradation rate of Amadori compounds was decelerated, while acceleration was observed in the arginine-sugar model. Increased temperature not only accelerated the Maillard reaction over time but also formed fluorescent compounds with different emission wavelengths. Lysine reacted with the sugars more readily than arginine under the same conditions. In addition, it was easier for lysine to react with glucose, whereas arginine reacted more readily with fructose under high pressure. High pressure exerts different effects on lysine-sugar and arginine-sugar models. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Shear-induced reaction-limited aggregation kinetics of Brownian particles at arbitrary concentrations

NASA Astrophysics Data System (ADS)

Zaccone, Alessio; Gentili, Daniele; Wu, Hua; Morbidelli, Massimo

2010-04-01

The aggregation of interacting Brownian particles in sheared concentrated suspensions is an important issue in colloid and soft matter science per se. Also, it serves as a model to understand biochemical reactions occurring in vivo where both crowding and shear play an important role. We present an effective medium approach within the Smoluchowski equation with shear which allows one to calculate the encounter kinetics through a potential barrier under shear at arbitrary colloid concentrations. Experiments on a model colloidal system in simple shear flow support the validity of the model in the concentration range considered. By generalizing Kramers' rate theory to the presence of shear and collective hydrodynamics, our model explains the significant increase in the shear-induced reaction-limited aggregation kinetics upon increasing the colloid concentration.

Kinetic Analysis for Macrocyclizations Involving Anionic Template at the Transition State

PubMed Central

Martí-Centelles, Vicente; Burguete, M. Isabel; Luis, Santiago V.

2012-01-01

Several kinetic models for the macrocyclization of a C2 pseudopeptide with a dihalide through a SN2 reaction have been developed. These models not only focus on the kinetic analysis of the main macrocyclization reaction, but also consider the competitive oligomerization/polymerization processes yielding undesired oligomeric/polymeric byproducts. The effect of anions has also been included in the kinetic models, as they can act as catalytic templates in the transition state reducing and stabilizing the transition state. The corresponding differential equation systems for each kinetic model can be solved numerically. Through a comprehensive analysis of these results, it is possible to obtain a better understanding of the different parameters that are involved in the macrocyclization reaction mechanism and to develop strategies for the optimization of the desired processes. PMID:22666148

A comprehensive model to determine the effects of temperature and species fluctuations on reaction rates in turbulent reacting flows

NASA Technical Reports Server (NTRS)

Goldstein, D.; Magnotti, F.; Chinitz, W.

1983-01-01

Reaction rates in turbulent, reacting flows are reviewed. Assumed probability density functions (pdf) modeling of reaction rates is being investigated in relation to a three variable pdf employing a 'most likely pdf' model. Chemical kinetic mechanisms treating hydrogen air combustion is studied. Perfectly stirred reactor modeling of flame stabilizing recirculation regions was used to investigate the stable flame regions for silane, hydrogen, methane, and propane, and for certain mixtures thereof. It is concluded that in general, silane can be counted upon to stabilize flames only when the overall fuel air ratio is close to or greater than unity. For lean flames, silane may tend to destabilize the flame. Other factors favoring stable flames are high initial reactant temperatures and system pressure.

Mean-field hierarchical equations for some A+BC catalytic reaction models

NASA Astrophysics Data System (ADS)

Cortés, Joaquín; Puschmann, Heinrich; Valencia, Eliana

1998-10-01

A mean-field study of the (A+BC→AC+1/2B2) system is developed from hierarchical equations, considering mechanisms that include dissociation, reaction with finite rates, desorption, and diffusion of the adsorbed species. The phase diagrams are compared to Monte Carlo simulations.

CHARACTERIZING PIPE WALL DEMAND: IMPLICATIONS FOR WATER QUALITY MODELING

EPA Science Inventory

It has become generally accepted that water quality can deteriorate in a distribution system through reactions in the bulk phase and/or at the pipe wall. These reactions may be physical, chemical or microbiological in nature. Perhaps one of the most serious aspects of water qua...

Model studies on precursor system generating blue pigment in onion and garlic.

PubMed

Imai, Shinsuke; Akita, Kaori; Tomotake, Muneaki; Sawada, Hiroshi

2006-02-08

Reactions involved in blue-green discoloration in a mixture of onion (Allium cepa L.) and garlic (Allium sativum L.) were investigated. Vivid-blue color was successfully reproduced by using a defined model reaction system comprising only trans-(+)-S-(1-propenyl)-L-cysteine sulfoxide (1-PeCSO) from onion, S-allyl-L-cysteine sulfoxide (2-PeCSO) from garlic, purified alliinase (EC 4.4.1.4), and glycine (or some other amino acids). Four reaction steps identified and factors affecting the blue color formation were in good agreement with those suggested by earlier investigators. When crude onion alliinase was used in place of garlic alliinase, less pigment was formed. This result was explained by a difference in the amount of thiosulfinates, colorless intermediates termed color developers, yielded from 1-PeCSO by these enzymes.

Chelate-Modified Fenton Reaction for the Degradation of Trichloroethylene in Aqueous and Two-Phase Systems

PubMed Central

Lewis, Scott; Lynch, Andrew; Bachas, Leonidas; Hampson, Steve; Ormsbee, Lindell; Bhattacharyya, Dibakar

2009-01-01

Abstract The primary objective of this research was to model and understand the chelate-modified Fenton reaction for the destruction of trichloroethylene (TCE) present in both the aqueous and organic (in the form of droplets) phases. The addition of a nontoxic chelate (L), such as citrate or gluconic acid, allows for operation at near-neutral pH and controlled release of Fe(II)/Fe(III). For the standard Fenton reaction at low pH in two-phase systems, an optimum H2O2:Fe(II) molar ratio was found to be between 1:1 and 2:1. Experimentation proved the chelate-modified Fenton reaction effectively dechlorinated TCE in both the aqueous and organic phases at pH 6–7 using low H2O2:Fe(II) molar ratios (4:1 to 8:1). Increasing the L:Fe ratio was found to decrease the rate of H2O2 degradation in both Fe(II) and Fe(III) systems at near-neutral pH. Generalized models were developed to predict the concentration of TCE in the aqueous phase and TCE droplet radius as a function of time using literature-reported hydroxyl radical reaction kinetics and mass transfer relationships. Additional aspects of this work include the reusability of the Fe–citrate complex under repeated H2O2 injections in real water systems as well as packed column studies for simulated groundwater injection. PMID:20418966

Constraining Habitable Environments on Mars by Quantifying Available Geochemical Energy

NASA Astrophysics Data System (ADS)

Tierney, L. L.; Jakosky, B. M.

2009-12-01

The search for life on Mars includes the availability of liquid water, access to biogenic elements and an energy source. In the past, when water was more abundant on Mars, a source of energy may have been the limiting factor for potential life. Energy, either from photosynthesis or chemosynthesis, is required in order to drive metabolism. Potential martian organisms most likely took advantage of chemosynthetic reactions at and below the surface. Terrestrial chemolithoautotrophs, for example, thrive off of chemical disequilibrium that exists in many environments and use inorganic redox (reduction-oxidation) reactions to drive metabolism and create cellular biomass. The chemical disequilibrium of six different martian environments were modeled in this study and analyzed incorporating a range of water and rock compositions, water:rock mass ratios, atmospheric fugacities, pH, and temperatures. All of these models can be applied to specific sites on Mars including environments similar to Meridiani Planum and Gusev Crater. Both a mass transfer geochemical model of groundwater-basalt interaction and a mixing model of groundwater-hydrothermal fluid interaction were used to estimate hypothetical martian fluid compositions that results from mixing over the entire reaction path. By determining the overall Gibbs free energy yields for redox reactions in the H-O-C-S-Fe-Mn system, the amount of geochemical energy that was available for potential chemolithoautotrophic microorganisms was quantified and the amount of biomass that could have been sustained was estimated. The quantity of biomass that can be formed and supported within a system depends on energy availability, thus sites that have higher levels and fluxes of energy have greater potential to support life. Results show that iron- and sulfur-oxidation reactions would have been the most favorable redox reactions in aqueous systems where groundwater and rock interacted at or near the surface. These types of reactions could have supported between 0.05 and 1.0 grams (dry weight) of biomass per mole of iron or sulfur. The hydrothermal environments would have had numerous redox reactions in the H-O-C-S-Fe-Mn system that could have provided sufficient metabolic energy for potential microorganisms. Methanotrophy, for example, provides the greatest amount of energy at ~760 kJ per mole of methane, which is equivalent to 0.6 grams (dry weight) of biomass. Additional results show that varying the amount of CO2 in the martian atmosphere or adjusting the water:rock ratios has little effect on the resulting Gibbs free energies. The martian values that are reported for available free energy in this study are similar to values that have been calculated for terrestrial systems in hydrothermal settings in which life is known to be abundant. In summary, the models indicate that martian aqueous environments were likely to have been habitable at a wide range of conditions when liquid water was more abundant and would have been able to supply a large amount of energy for potential organisms.

Lagrangian simulation of mixing and reactions in complex geochemical systems

NASA Astrophysics Data System (ADS)

Engdahl, Nicholas B.; Benson, David A.; Bolster, Diogo

2017-04-01

Simulations of detailed geochemical systems have traditionally been restricted to Eulerian reactive transport algorithms. This note introduces a Lagrangian method for modeling multicomponent reaction systems. The approach uses standard random walk-based methods for the particle motion steps but allows the particles to interact with each other by exchanging mass of their various chemical species. The colocation density of each particle pair is used to calculate the mass transfer rate, which creates a local disequilibrium that is then relaxed back toward equilibrium using the reaction engine PhreeqcRM. The mass exchange is the only step where the particles interact and the remaining transport and reaction steps are entirely independent for each particle. Several validation examples are presented, which reproduce well-known analytical solutions. These are followed by two demonstration examples of a competitive decay chain and an acid-mine drainage system. The source code, entitled Complex Reaction on Particles (CRP), and files needed to run these examples are hosted openly on GitHub (https://github.com/nbengdahl/CRP), so as to enable interested readers to readily apply this approach with minimal modifications.

Dynamical patterns and regime shifts in the nonlinear model of soil microorganisms growth

NASA Astrophysics Data System (ADS)

Zaitseva, Maria; Vladimirov, Artem; Winter, Anna-Marie; Vasilyeva, Nadezda

2017-04-01

Dynamical model of soil microorganisms growth and turnover is formulated as a system of nonlinear partial differential equations of reaction-diffusion type. We consider spatial distributions of concentrations of several substrates and microorganisms. Biochemical reactions are modelled by chemical kinetic equations. Transport is modelled by simple linear diffusion for all chemical substances, while for microorganisms we use different transport functions, e.g. some of them can actively move along gradient of substrate concentration, while others cannot move. We solve our model in two dimensions, starting from uniform state with small initial perturbations for various parameters and find parameter range, where small initial perturbations grow and evolve. We search for bifurcation points and critical regime shifts in our model and analyze time-space profile and phase portraits of these solutions approaching critical regime shifts in the system, exploring possibility to detect such shifts in advance. This work is supported by NordForsk, project #81513.

Modeling and Simulations in Photoelectrochemical Water Oxidation: From Single Level to Multiscale Modeling.

PubMed

Zhang, Xueqing; Bieberle-Hütter, Anja

2016-06-08

This review summarizes recent developments, challenges, and strategies in the field of modeling and simulations of photoelectrochemical (PEC) water oxidation. We focus on water splitting by metal-oxide semiconductors and discuss topics such as theoretical calculations of light absorption, band gap/band edge, charge transport, and electrochemical reactions at the electrode-electrolyte interface. In particular, we review the mechanisms of the oxygen evolution reaction, strategies to lower overpotential, and computational methods applied to PEC systems with particular focus on multiscale modeling. The current challenges in modeling PEC interfaces and their processes are summarized. At the end, we propose a new multiscale modeling approach to simulate the PEC interface under conditions most similar to those of experiments. This approach will contribute to identifying the limitations at PEC interfaces. Its generic nature allows its application to a number of electrochemical systems. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drosophila segmentation: supercomputer simulation of prepattern hierarchy.

PubMed

Hunding, A; Kauffman, S A; Goodwin, B C

1990-08-09

Spontaneous prepattern formation in a two level hierarchy of reaction-diffusion systems is simulated in three space co-ordinates and time, mimicking gap gene and primary pair-rule gene expression. The model rests on the idea of Turing systems of the second kind, in which one prepattern generates position dependent rate constants for a subsequent reaction-diffusion system. Maternal genes are assumed responsible for setting up gradients from the anterior and posterior ends, one of which is needed to stabilize a double period prepattern suggested to underly the read out of the gap genes. The resulting double period pattern in turn stabilizes the next prepattern in the hierarchy, which has a short wavelength with many characteristics of the stripes seen in actual primary pair-rule gene expression. Without such hierarchical stabilization, reaction-diffusion mechanisms yield highly patchy short wave length patterns, and thus unreliable stripes. The model yields seven stable stripes located in the middle of the embryo, with the potential for additional expression near the poles, as observed experimentally. The model does not rely on specific chemical reaction kinetics, rather the effect is general to many such kinetic schemes. This makes it robust to parameter changes, and it has good potential for adapting to size and shape changes as well. The study thus suggests that the crucial organizing principle in early Drosophila embryogenesis is based on global field mechanisms, not on particular local interactions.

Comparing 2-nt 3' overhangs against blunt-ended siRNAs: a systems biology based study.

PubMed

Ghosh, Preetam; Dullea, Robert; Fischer, James E; Turi, Tom G; Sarver, Ronald W; Zhang, Chaoyang; Basu, Kalyan; Das, Sajal K; Poland, Bradley W

2009-07-07

In this study, we formulate a computational reaction model following a chemical kinetic theory approach to predict the binding rate constant for the siRNA-RISC complex formation reaction. The model allowed us to study the potency difference between 2-nt 3' overhangs against blunt-ended siRNA molecules in an RNA interference (RNAi) system. The rate constant predicted by this model was fed into a stochastic simulation of the RNAi system (using the Gillespie stochastic simulator) to study the overall potency effect. We observed that the stochasticity in the transcription/translation machinery has no observable effects in the RNAi pathway. Sustained gene silencing using siRNAs can be achieved only if there is a way to replenish the dsRNA molecules in the cell. Initial findings show about 1.5 times more blunt-ended molecules will be required to keep the mRNA at the same reduced level compared to the 2-nt overhang siRNAs. However, the mRNA levels jump back to saturation after a longer time when blunt-ended siRNAs are used. We found that the siRNA-RISC complex formation reaction rate was 2 times slower when blunt-ended molecules were used pointing to the fact that the presence of the 2-nt overhangs has a greater effect on the reaction in which the bound RISC complex cleaves the mRNA.

Comparing 2-nt 3' overhangs against blunt-ended siRNAs: a systems biology based study

PubMed Central

Ghosh, Preetam; Dullea, Robert; Fischer, James E; Turi, Tom G; Sarver, Ronald W; Zhang, Chaoyang; Basu, Kalyan; Das, Sajal K; Poland, Bradley W

2009-01-01

In this study, we formulate a computational reaction model following a chemical kinetic theory approach to predict the binding rate constant for the siRNA-RISC complex formation reaction. The model allowed us to study the potency difference between 2-nt 3' overhangs against blunt-ended siRNA molecules in an RNA interference (RNAi) system. The rate constant predicted by this model was fed into a stochastic simulation of the RNAi system (using the Gillespie stochastic simulator) to study the overall potency effect. We observed that the stochasticity in the transcription/translation machinery has no observable effects in the RNAi pathway. Sustained gene silencing using siRNAs can be achieved only if there is a way to replenish the dsRNA molecules in the cell. Initial findings show about 1.5 times more blunt-ended molecules will be required to keep the mRNA at the same reduced level compared to the 2-nt overhang siRNAs. However, the mRNA levels jump back to saturation after a longer time when blunt-ended siRNAs are used. We found that the siRNA-RISC complex formation reaction rate was 2 times slower when blunt-ended molecules were used pointing to the fact that the presence of the 2-nt overhangs has a greater effect on the reaction in which the bound RISC complex cleaves the mRNA. PMID:19594876

Remodelling of cellular excitation (reaction) and intercellular coupling (diffusion) by chronic atrial fibrillation represented by a reaction-diffusion system

NASA Astrophysics Data System (ADS)

Zhang, Henggui; Garratt, Clifford J.; Kharche, Sanjay; Holden, Arun V.

2009-06-01

Human atrial tissue is an excitable system, in which myocytes are excitable elements, and cell-to-cell electrotonic interactions are via diffusive interactions of cell membrane potentials. We developed a family of excitable system models for human atrium at cellular, tissue and anatomical levels for both normal and chronic atrial fibrillation (AF) conditions. The effects of AF-induced remodelling of cell membrane ionic channels (reaction kinetics) and intercellular gap junctional coupling (diffusion) on atrial excitability, conduction of excitation waves and dynamics of re-entrant excitation waves are quantified. Both ionic channel and gap junctional coupling remodelling have rate dependent effects on atrial propagation. Membrane channel conductance remodelling allows the propagation of activity at higher rates than those sustained in normal tissue or in tissue with gap junctional remodelling alone. Membrane channel conductance remodelling is essential for the propagation of activity at rates higher than 300/min as seen in AF. Spatially heterogeneous gap junction coupling remodelling increased the risk of conduction block, an essential factor for the genesis of re-entry. In 2D and 3D anatomical models, the dynamical behaviours of re-entrant excitation waves are also altered by membrane channel modelling. This study provides insights to understand the pro-arrhythmic effects of AF-induced reaction and diffusion remodelling in atrial tissue.

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.

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.

The ^132Sn + ^96Zr reaction: a study of fusion enhancement/hindrance

NASA Astrophysics Data System (ADS)

Loveland, Walter; Vinodkumar, A. M.; Neeway, James; Sprunger, Peter; Prisbrey, Landon; Peterson, Donald; Liang, J. F.; Shapira, Dan; Gross, C. J.; Varner, R. L.; Kolata, J. J.; Roberts, A.; Caraley, A. L.

2008-10-01

Capture-fission cross sections were measured for the collision of the massive nucleus ^132Sn with ^96Zr at center of mass energies ranging from 192.8 to 249.6 MeV in an attempt to study fusion enhancement and hindrance in this reaction involving very neutron-rich nuclei. Coincident fission fragments were detected using silicon detectors. Using angle and energy conditions, deep inelastic scattering events were separated from fission events. Coupled channels calculations can describe the data if the surface diffuseness parameter, a, is allowed to be 1.10 fm, instead of the customary 0.6 fm. The measured capture-fission cross sections agree moderately well with model calculations using the dinuclear system (DNS) model. If we use this model to predict fusion barrier heights for these reactions, we find the predicted fusion hindrance, as represented by the extra push energy, is greater for the more neutron-rich system, lessening the advantage of the lower interaction barriers with neutron rich projectiles.

132Sn+96Zr reaction: A study of fusion enhancement/hindrance

NASA Astrophysics Data System (ADS)

Vinodkumar, A. M.; Loveland, W.; Neeway, J. J.; Prisbrey, L.; Sprunger, P. H.; Peterson, D.; Liang, J. F.; Shapira, D.; Gross, C. J.; Varner, R. L.; Kolata, J. J.; Roberts, A.; Caraley, A. L.

2008-11-01

Capture-fission cross sections were measured for the collision of the massive nucleus Sn132 with Zr96 at center-of-mass energies ranging from 192.8 to 249.6 MeV in an attempt to study fusion enhancement and hindrance in this reaction involving very neutron-rich nuclei. Coincident fission fragments were detected using silicon detectors. Using angle and energy conditions, deep inelastic scattering events were separated from fission events. Coupled-channels calculations can describe the data if the surface diffuseness parameter, a, is allowed to be 1.10 fm instead of the customary 0.6 fm. The measured capture-fission cross sections agree moderately well with model calculations using the dinuclear system model. If we use this model to predict fusion barrier heights for these reactions, we find the predicted fusion hindrance, as represented by the extra push energy, is greater for the more neutron-rich system, lessening the advantage of the lower interaction barriers with neutron-rich projectiles.

An adaptive tau-leaping method for stochastic simulations of reaction-diffusion systems

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

Padgett, Jill M. A.; Ilie, Silvana, E-mail: silvana@ryerson.ca

2016-03-15

Stochastic modelling is critical for studying many biochemical processes in a cell, in particular when some reacting species have low population numbers. For many such cellular processes the spatial distribution of the molecular species plays a key role. The evolution of spatially heterogeneous biochemical systems with some species in low amounts is accurately described by the mesoscopic model of the Reaction-Diffusion Master Equation. The Inhomogeneous Stochastic Simulation Algorithm provides an exact strategy to numerically solve this model, but it is computationally very expensive on realistic applications. We propose a novel adaptive time-stepping scheme for the tau-leaping method for approximating themore » solution of the Reaction-Diffusion Master Equation. This technique combines effective strategies for variable time-stepping with path preservation to reduce the computational cost, while maintaining the desired accuracy. The numerical tests on various examples arising in applications show the improved efficiency achieved by the new adaptive method.« less

Nucleophilic substitution at phosphorus centers (SN2@p).

PubMed

van Bochove, Marc A; Swart, Marcel; Bickelhaupt, F Matthias

2007-12-03

We have studied the characteristics of archetypal model systems for bimolecular nucleophilic substitution at phosphorus (SN2@P) and, for comparison, at carbon (SN2@C) and silicon (SN2@Si) centers. In our studies, we applied the generalized gradient approximation (GGA) of density functional theory (DFT) at the OLYP/TZ2P level. Our model systems cover nucleophilic substitution at carbon in X(-)+CH3Y (SN2@C), at silicon in X(-)+SiH3Y (SN2@Si), at tricoordinate phosphorus in X(-)+PH2Y (SN2@P3), and at tetracoordinate phosphorus in X(-)+POH2Y (SN2@P4). The main feature of going from SN2@C to SN2@P is the loss of the characteristic double-well potential energy surface (PES) involving a transition state [X--CH3--Y]- and the occurrence of a single-well PES with a stable transition complex, namely, [X--PH2--Y]- or [X--POH2--Y](-). The differences between SN2@P3 and SN2@P4 are relatively small. We explored both the symmetric and asymmetric (i.e. X, Y=Cl, OH) SN2 reactions in our model systems, the competition between backside and frontside pathways, and the dependence of the reactions on the conformation of the reactants. Furthermore, we studied the effect, on the symmetric and asymmetric SN2@P3 and S(N)2@P4 reactions, of replacing hydrogen substituents at the phosphorus centers by chlorine and fluorine in the model systems X(-)+PR2Y and X(-)+POR2Y, with R=Cl, F. An interesting phenomenon is the occurrence of a triple-well PES not only in the symmetric, but also in the asymmetric SN2@P4 reactions of X(-)+POCl2--Y.

A Simple and Accurate Method To Calculate Free Energy Profiles and Reaction Rates from Restrained Molecular Simulations of Diffusive Processes.

PubMed

Ovchinnikov, Victor; Nam, Kwangho; Karplus, Martin

2016-08-25

A method is developed to obtain simultaneously free energy profiles and diffusion constants from restrained molecular simulations in diffusive systems. The method is based on low-order expansions of the free energy and diffusivity as functions of the reaction coordinate. These expansions lead to simple analytical relationships between simulation statistics and model parameters. The method is tested on 1D and 2D model systems; its accuracy is found to be comparable to or better than that of the existing alternatives, which are briefly discussed. An important aspect of the method is that the free energy is constructed by integrating its derivatives, which can be computed without need for overlapping sampling windows. The implementation of the method in any molecular simulation program that supports external umbrella potentials (e.g., CHARMM) requires modification of only a few lines of code. As a demonstration of its applicability to realistic biomolecular systems, the method is applied to model the α-helix ↔ β-sheet transition in a 16-residue peptide in implicit solvent, with the reaction coordinate provided by the string method. Possible modifications of the method are briefly discussed; they include generalization to multidimensional reaction coordinates [in the spirit of the model of Ermak and McCammon (Ermak, D. L.; McCammon, J. A. J. Chem. Phys. 1978, 69, 1352-1360)], a higher-order expansion of the free energy surface, applicability in nonequilibrium systems, and a simple test for Markovianity. In view of the small overhead of the method relative to standard umbrella sampling, we suggest its routine application in the cases where umbrella potential simulations are appropriate.

Convective instability and boundary driven oscillations in a reaction-diffusion-advection model

NASA Astrophysics Data System (ADS)

Vidal-Henriquez, Estefania; Zykov, Vladimir; Bodenschatz, Eberhard; Gholami, Azam

2017-10-01

In a reaction-diffusion-advection system, with a convectively unstable regime, a perturbation creates a wave train that is advected downstream and eventually leaves the system. We show that the convective instability coexists with a local absolute instability when a fixed boundary condition upstream is imposed. This boundary induced instability acts as a continuous wave source, creating a local periodic excitation near the boundary, which initiates waves travelling both up and downstream. To confirm this, we performed analytical analysis and numerical simulations of a modified Martiel-Goldbeter reaction-diffusion model with the addition of an advection term. We provide a quantitative description of the wave packet appearing in the convectively unstable regime, which we found to be in excellent agreement with the numerical simulations. We characterize this new instability and show that in the limit of high advection speed, it is suppressed. This type of instability can be expected for reaction-diffusion systems that present both a convective instability and an excitable regime. In particular, it can be relevant to understand the signaling mechanism of the social amoeba Dictyostelium discoideum that may experience fluid flows in its natural habitat.

Fragment distribution in 78,86Kr+181Ta reactions

NASA Astrophysics Data System (ADS)

Zhang, Dong-Hong; Zhang, Feng-Shou

2018-05-01

Within the framework of the isospin-dependent quantum molecular dynamics model, along with the GEMINI model, the 86Kr+181Ta reaction at 80, 120 and 160 MeV/nucleon and the 78Kr+181Ta reaction at 160 MeV/nucleon are studied, and the production cross sections of the generated fragments are calculated. More inter-mediate and large mass fragments can be produced in the reactions with a large range of impact parameter. The production cross sections of nuclei such as the isotopes of Si and P generally decrease with increasing incident energy. Isotopes near the neutron drip line are produced more in the neutron-rich system 86Kr+181Ta. Supported by Youth Research Foundation of Shanxi Datong University (2016Q10)

A systems biology approach to investigate the antimicrobial activity of oleuropein.

PubMed

Li, Xianhua; Liu, Yanhong; Jia, Qian; LaMacchia, Virginia; O'Donoghue, Kathryn; Huang, Zuyi

2016-12-01

Oleuropein and its hydrolysis products are olive phenolic compounds that have antimicrobial effects on a variety of pathogens, with the potential to be utilized in food and pharmaceutical products. While the existing research is mainly focused on individual genes or enzymes that are regulated by oleuropein for antimicrobial activities, little work has been done to integrate intracellular genes, enzymes and metabolic reactions for a systematic investigation of antimicrobial mechanism of oleuropein. In this study, the first genome-scale modeling method was developed to predict the system-level changes of intracellular metabolism triggered by oleuropein in Staphylococcus aureus, a common food-borne pathogen. To simulate the antimicrobial effect, an existing S. aureus genome-scale metabolic model was extended by adding the missing nitric oxide reactions, and exchange rates of potassium, phosphate and glutamate were adjusted in the model as suggested by previous research to mimic the stress imposed by oleuropein on S. aureus. The developed modeling approach was able to match S. aureus growth rates with experimental data for five oleuropein concentrations. The reactions with large flux change were identified and the enzymes of fifteen of these reactions were validated by existing research for their important roles in oleuropein metabolism. When compared with experimental data, the up/down gene regulations of 80% of these enzymes were correctly predicted by our modeling approach. This study indicates that the genome-scale modeling approach provides a promising avenue for revealing the intracellular metabolism of oleuropein antimicrobial properties.

PENDISC: a simple method for constructing a mathematical model from time-series data of metabolite concentrations.

PubMed

Sriyudthsak, Kansuporn; Iwata, Michio; Hirai, Masami Yokota; Shiraishi, Fumihide

2014-06-01

The availability of large-scale datasets has led to more effort being made to understand characteristics of metabolic reaction networks. However, because the large-scale data are semi-quantitative, and may contain biological variations and/or analytical errors, it remains a challenge to construct a mathematical model with precise parameters using only these data. The present work proposes a simple method, referred to as PENDISC (Parameter Estimation in a N on- DImensionalized S-system with Constraints), to assist the complex process of parameter estimation in the construction of a mathematical model for a given metabolic reaction system. The PENDISC method was evaluated using two simple mathematical models: a linear metabolic pathway model with inhibition and a branched metabolic pathway model with inhibition and activation. The results indicate that a smaller number of data points and rate constant parameters enhances the agreement between calculated values and time-series data of metabolite concentrations, and leads to faster convergence when the same initial estimates are used for the fitting. This method is also shown to be applicable to noisy time-series data and to unmeasurable metabolite concentrations in a network, and to have a potential to handle metabolome data of a relatively large-scale metabolic reaction system. Furthermore, it was applied to aspartate-derived amino acid biosynthesis in Arabidopsis thaliana plant. The result provides confirmation that the mathematical model constructed satisfactorily agrees with the time-series datasets of seven metabolite concentrations.

Open quantum system approach to the modeling of spin recombination reactions.

PubMed

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

2012-04-26

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

Comparative simulation study of chemical synthesis of functional DADNE material.

PubMed

Liu, Min Hsien; Liu, Chuan Wen

2017-01-01

Amorphous molecular simulation to model the reaction species in the synthesis of chemically inert and energetic 1,1-diamino-2,2-dinitroethene (DADNE) explosive material was performed in this work. Nitromethane was selected as the starting reactant to undergo halogenation, nitration, deprotonation, intermolecular condensation, and dehydration to produce the target DADNE product. The Materials Studio (MS) forcite program allowed fast energy calculations and reliable geometric optimization of all aqueous molecular reaction systems (0.1-0.5 M) at 283 K and 298 K. The MS forcite-computed and Gaussian polarizable continuum model (PCM)-computed results were analyzed and compared in order to explore feasible reaction pathways under suitable conditions for the synthesis of DADNE. Through theoretical simulation, the findings revealed that synthesis was possible, and a total energy barrier of 449.6 kJ mol -1 needed to be overcome in order to carry out the reaction according to MS calculation of the energy barriers at each stage at 283 K, as shown by the reaction profiles. Local analysis of intermolecular interaction, together with calculation of the stabilization energy of each reaction system, provided information that can be used as a reference regarding molecular integrated stability. Graphical Abstract Materials Studio software has been suggested for the computation and simulation of DADNE synthesis.

Maillard-reaction-induced modification and aggregation of proteins and hardening of texture in protein bar model systems.

PubMed

Zhou, Peng; Guo, Mufan; Liu, Dasong; Liu, Xiaoming; Labuza, Teodore P

2013-03-01

The hardening of high-protein bars causes problems in their acceptability to consumers. The objective of this study was to determine the progress of the Maillard reaction in model systems of high-protein nutritional bars containing reducing sugars, and to illustrate the influences of the Maillard reaction on the modification and aggregation of proteins and the hardening of bar matrices during storage. The progress of the Maillard reaction, glycation, and aggregation of proteins, and textural changes in bar matrices were investigated during storage at 25, 35, and 45 °C. The initial development of the Maillard reaction caused little changes in hardness; however, further storage resulted in dramatic modification of protein with formation of high-molecular-weight polymers, resulting in the hardening in texture. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula minimized the changes in texture. The hardening of high-protein bars causes problems in their acceptability to consumers. Maillard reaction is one of the mechanisms contributing to the hardening of bar matrix, particularly for the late stage of storage. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula will minimize the changes in texture. © 2013 Institute of Food Technologists®

Are dinucleoside monophosphates relevant models for the study of DNA intrastrand cross-link lesions? The example of g[8-5m]T.

PubMed

Garrec, Julian; Dumont, Elise

2014-07-21

Oxidatively generated tandem lesions such as G[8-5m]T pose a potent threat to genome integrity. Direct experimental studies of the kinetics and thermodynamics of a specific lesion within DNA are very challenging, mostly due to the variety of products that can be formed in oxidative conditions. Dinucleoside monophosphates (DM) involving only the reactive nucleobases in water represent appealing alternative models on which most physical chemistry and structural techniques can be applied. However, it is not yet clear how relevant these models are. Here, we present QM/MM MD simulations of the cyclization step involved in the formation of G[8-5m]T from the guanine-thymine (GpT) DM in water, with the aim of comparing our results to our previous investigation of the same reaction in DNA ( Garrec , J. , Patel , C. , Rothlisberger , U. , and Dumont , E. ( 2012 ) J. Am. Chem. Soc. 134 , 2111 - 2119 ). We show that, despite the different levels of preorganization of the two systems, the corresponding reactions share many energetic and structural characteristics. The main difference lies in the angle between the G and T bases, which is slightly higher in the transition state (TS) and product of the reaction in water than in the reaction in DNA. This effect is due to the Watson-Crick H-bonds, which are absent in the {GpT+water} system and restrain the relative positioning of the reactive nucleobases in DNA. However, since the lesion is accommodated easily in the DNA macromolecule, the induced energetic penalty is relatively small. The high similarity between the two reactions strongly supports the use of GpT in water as a model of the corresponding reaction in DNA.

Towards a Model of Reactive-Cracking: the Role of Reactions, Elasticity and Surface Energy Driven Flow in Poro-elastic Media

NASA Astrophysics Data System (ADS)

Evans, O.; Spiegelman, M. W.; Wilson, C. R.; Kelemen, P. B.

2016-12-01

Many critical processes can be described by reactive fluid flow in brittle media, including hydration/alteration of oceanic plates near spreading ridges, chemical weathering, and dehydration/decarbonation of subducting plates. Such hydration reactions can produce volume changes that may induce stresses large enough to drive fracture in the rock, in turn exposing new reactive surface and modifying the permeability. A better understanding of this potentially rich feedback could also be critical in the design of engineered systems for geologic carbon sequestration. To aid understanding of these processes we have developed a macroscopic continuum description of reactive fluid flow in an elastically deformable porous media. We explore the behaviour of this model by considering a simplified hydration reaction (e.g. olivine + H20 -> serpentine + brucite). In a closed system, these hydration reactions will continue to consume available fluids until the permeability reaches zero, leaving behind it a highly stressed residuum. Our model demonstrates this limiting behaviour, and that the elastic stresses generated are large enough to cause failure/fracture of the host rock. Whilst it is understood that `reactive fracture' is an important mechanism for the continued evolution of this process, it is also proposed that imbibition/surface energy driven flow may play a role. Through a simplified set of computational experiments, we investigate the relative roles of elasticity and surface energy in both a non-reactive purely poro-elastic framework, and then in the presence of reaction. We demonstrate that surface energy can drive rapid diffusion of porosity, thus allowing the reaction to propagate over larger areas. As we expect both surface energy and fracture/failure to be of importance in these processes, we plan to integrate the current model into one that allows for fracture once critical stresses are exceeded.

Predicting effects of structural stress in a genome-reduced model bacterial metabolism

NASA Astrophysics Data System (ADS)

Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

2012-08-01

Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

PubMed Central

Yang, Jin; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.

2009-01-01

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena. PMID:18851068

Challenges in modelling homogeneous catalysis: new answers from ab initio molecular dynamics to the controversy over the Wacker process.

PubMed

Stirling, András; Nair, Nisanth N; Lledós, Agustí; Ujaque, Gregori

2014-07-21

We present here a review of the mechanistic studies of the Wacker process stressing the long controversy about the key reaction steps. We give an overview of the previous experimental and theoretical studies on the topic. Then we describe the importance of the most recent Ab Initio Molecular Dynamics (AIMD) calculations in modelling organometallic reactivity in water. As a prototypical example of homogeneous catalytic reactions, the Wacker process poses serious challenges to modelling. The adequate description of the multiple role of the water solvent is very difficult by using static quantum chemical approaches including cluster and continuum solvent models. In contrast, such reaction systems are suitable for AIMD, and by combining with rare event sampling techniques, the method provides reaction mechanisms and the corresponding free energy profiles. The review also highlights how AIMD has helped to obtain a novel understanding of the mechanism and kinetics of the Wacker process.

Radiative interactions in chemically reacting supersonic internal flows

NASA Technical Reports Server (NTRS)

Tiwari, S. N.; Chandrasekhar, R.

1991-01-01

The two-dimensional, elliptic Navier-Stokes equations are used to investigate supersonic flows with finite-rate chemistry and radiation for hydrogen-air systems. The chemistry source terms in the species equation is treated implicitly to alleviate the stiffness associated with fast reactions. The explicit, unsplit MacCormack finite-difference scheme is used to advance the governing equations in time, until convergence is achieved. The specific problem considered is the premixed flow in a channel with a ten-degree compression ramp. Three different chemistry models are used, accounting for increasing number of reactions and participating species. Two chemistry models assure nitrogen as inert, while the third model accounts for nitrogen reactions and NO(x) formation. The tangent slab approximation is used in the radiative flux formulation. A pseudo-gray model is used to represent the absorption-emission characteristics of the participating species. Results obtained for specific conditions indicate that the radiative interactions vary substantially, depending on reactions involving HO2 and NO species and that this can have a significant influence on the flowfield.

Experimental Insights into Multiphase (H2O-CO2) Fluid-Rock Interactions in Geothermal Systems

NASA Astrophysics Data System (ADS)

Kaszuba, J. P.; Lo Re, C.; Martin, J.; McPherson, B. J.; Moore, J. N.

2012-12-01

Integrated hydrothermal experiments and geochemical modeling elucidate fluid-rock interactions and reaction pathways in both natural and anthropogenic systems, including enhanced geothermal systems (EGS) in which CO2 is introduced as a working fluid. Experiments are conducted in rocker bombs and flexible Au-Ti reaction cells. Individual experiments require one to three months to complete; intensive in-situ fluid/gas sampling gauges reaction progress. Investigation of granitic reservoirs and associated vein minerals are broadly based on the Roosevelt Hot Springs thermal area, Utah, USA. The granite consists of subequal amounts of quartz, perthitic K-feldspar (~25% wt% albite and 75% wt% K-feldspar), and oligoclase (An23), and 4 wt% Fe-rich biotite. Vein minerals include epidote and chlorite (clinochlore). Experiments are conducted at 250°C and 25 to 45 MPa. Each experiment uses mineral powders (75 wt% of rock mass, ground to <45 um) to increase reactivity and also mineral pieces (0.1-0.7 cm in size) to promote petrologic evaluation of mineral reactions. The water (I ≈ 0.1 molal) initially contains millimolal quantities of SiO2, Al, Ca, Mg, K, SO4, and HCO3 and is designed to be saturated with all of the minerals present at the start of each experiment. Excess CO2 is injected to saturate the water and maintain an immiscible supercritical fluid phase. The entire evolutionary path of the natural system is not replicated at laboratory scales. Instead, experiments define a segment of the reaction path and, in combination with geochemical modeling, provide clear trajectories towards equilibrium. Reaction of granite+water yields illite+zeolite; smectite subsequently precipitates in response to CO2 injection. Reaction of granite+epidote+water yields illite+zeolite+smectite; zeolite does not precipitate after CO2 is injected. Water in all experiments become saturated with chalcedony. Carbonate minerals do not precipitate but are predicted as final equilbrium products. Enhanced Geothermal Systems are expected to follow similar reaction pathways and produce metastable minerals during initial development.

An Evaluation System for the Online Training Programs in Meteorology and Hydrology

ERIC Educational Resources Information Center

Wang, Yong; Zhi, Xiefei

2009-01-01

This paper studies the current evaluation system for the online training program in meteorology and hydrology. CIPP model that includes context evaluation, input evaluation, process evaluation and product evaluation differs from Kirkpatrick model including reactions evaluation, learning evaluation, transfer evaluation and results evaluation in…

MODELING OF SO2 REMOVAL IN SPRAY-DRYER FLUE-GAS DESULFURIZATION SYSTEM

EPA Science Inventory

The report presents a comprehensive mathematical model of the SO2 removal process in a spray-dryer flue-gas desulfurization system. Simultaneous evaporation of a sorbent droplet and absorption/reaction of SO2 in the droplet are described by the corresponding heat- and mass-transf...

IMPACT OF AN UPDATED CARBON BOND MECHANISM ON PREDICTIONS FROM THE CMAQ MODELING SYSTEM: PRELIMINARY ASSESSMENT

EPA Science Inventory

An updated and expanded Carbon Bond mechanism (CB05) has been incorporated into the Community Multiscale Air Quality modeling system to more accurately simulate wintertime, pristine, and high altitude situations. The CB05 mechanism has nearly twice the number of reactions compare...

Influence of roasting on the antioxidant activity and HMF formation of a cocoa bean model systems.

PubMed

Oliviero, Teresa; Capuano, Edoardo; Cämmerer, Bettina; Fogliano, Vincenzo

2009-01-14

During the roasting of cocoa beans chemical reactions lead to the formation of Maillard reaction (MR) products and to the degradation of catechin-containing compounds, which are very abundant in these seeds. To study the modifications occurring during thermal treatment of fat and antioxidant rich foods, such as cocoa, a dry model system was set up and roasted at 180 degrees C for different times. The role played in the formation of MR products and in the antioxidant activity of the system by proteins, catechin, and cocoa butter was investigated by varying the model system formulation. Results showed that the antioxidant activity decreased during roasting, paralleling catechin concentration, thus suggesting that this compound is mainly responsible for the antioxidant activity of roasted cocoa beans. Model system browning was significantly higher in the presence of catechin, which contributed to the formation of water-insoluble melanoidins, which are mainly responsible for browning. HMF concentration was higher in casein-containing systems, and its formation was strongly inhibited in the presence of catechin. No effects related to the degree of lipid oxidation could be observed. Data from model systems obtained by replacing fat with water showed a much lower rate of MR development and catechin degradation but the same inhibitory effect of catechin on HMF formation.

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.

Making peanut allergens indigestible: a model system for reducing or preventing an allergic reaction

USDA-ARS?s Scientific Manuscript database

Peanut allergens are not totally resistant to digestion as previously known. Creating peanut allergen conjugates that are more resistant to digestion may prevent absorption of the allergens into the bloodstream, and thereby, an allergic reaction. Peanut allergen conjugates were prepared by covalen...

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.

Kinetic study of lipase-catalyzed glycerolysis of palm olein using Lipozyme TLIM in solvent-free system

PubMed Central

Phuah, Eng-Tong; Lee, Yee-Ying; Tang, Teck-Kim

2018-01-01

Diacylglycerol (DAG) and monoacylglycerol (MAG) are two natural occurring minor components found in most edible fats and oils. These compounds have gained increasing market demand owing to their unique physicochemical properties. Enzymatic glycerolysis in solvent-free system might be a promising approach in producing DAG and MAG-enriched oil. Understanding on glycerolysis mechanism is therefore of great importance for process simulation and optimization. In this study, a commercial immobilized lipase (Lipozyme TL IM) was used to catalyze the glycerolysis reaction. The kinetics of enzymatic glycerolysis reaction between triacylglycerol (TAG) and glycerol (G) were modeled using rate equation with unsteady-state assumption. Ternary complex, ping-pong bi-bi and complex ping-pong bi-bi models were proposed and compared in this study. The reaction rate constants were determined using non-linear regression and sum of square errors (SSE) were minimized. Present work revealed satisfactory agreement between experimental data and the result generated by complex ping-pong bi-bi model as compared to other models. The proposed kinetic model would facilitate understanding on enzymatic glycerolysis for DAG and MAG production and design optimization of a pilot-scale reactor. PMID:29401481

Two-dimensional free-energy surface on the exchange reaction of alkyl chloride/chloride using the QM/MM-MC method

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

Ohisa, M.; Yamataka, H.; Dupuis, Michel

2007-12-05

Two-dimensional free-energy surfaces are calculated for alkyl chloride/chloride exchange/inversion reactions: Cl- + RCl (R = Me and t-Bu) surrounded by one hundred H2O molecules as a model of solvent. The methodology of free-energy calculation by perturbation theory based on a mixed-Hamiltonian model (QM/MM) combined with Monte Carlo sampling of the solvent configurations was used to obtain the changes in solvation free energy. We devised a special procedure to analyze the two-dimensional free-energy surfaces to gain unique insight into the differences in the reaction mechanisms between the two systems. The inversion reaction path for R = t-Bu on the free-energy surfacemore » is found to proceed in an asynchronous way within a concerted framework via the ion-pair region. This is in contrast to the R = Me system that proceeds as a typical SN2 reaction. This work was supported by the U.S. Department of Energy's (DOE) Office of Basic Energy Sciences, Chemical Sciences program. The Pacific Northwest National Laboratory is operated by Battelle for DOE.« less

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.

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a petri net approach.

PubMed

Bortfeldt, Ralf H; Schuster, Stefan; Koch, Ina

2011-01-01

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier. Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a Petri net approach.

PubMed

Bortfeldt, Ralf H; Schuster, Stefan; Koch, Ina

2010-01-01

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier.Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.

Modelling chemical depletion profiles in regolith

USGS Publications Warehouse

Brantley, S.L.; Bandstra, J.; Moore, J.; White, A.F.

2008-01-01

Chemical or mineralogical profiles in regolith display reaction fronts that document depletion of leachable elements or minerals. A generalized equation employing lumped parameters was derived to model such ubiquitously observed patterns:C = frac(C0, frac(C0 - Cx = 0, Cx = 0) exp (??ini ?? over(k, ??) ?? x) + 1)Here C, Cx = 0, and Co are the concentrations of an element at a given depth x, at the top of the reaction front, or in parent respectively. ??ini is the roughness of the dissolving mineral in the parent and k???? is a lumped kinetic parameter. This kinetic parameter is an inverse function of the porefluid advective velocity and a direct function of the dissolution rate constant times mineral surface area per unit volume regolith. This model equation fits profiles of concentration versus depth for albite in seven weathering systems and is consistent with the interpretation that the surface area (m2 mineral m- 3 bulk regolith) varies linearly with the concentration of the dissolving mineral across the front. Dissolution rate constants can be calculated from the lumped fit parameters for these profiles using observed values of weathering advance rate, the proton driving force, the geometric surface area per unit volume regolith and parent concentration of albite. These calculated values of the dissolution rate constant compare favorably to literature values. The model equation, useful for reaction fronts in both steady-state erosional and quasi-stationary non-erosional systems, incorporates the variation of reaction affinity using pH as a master variable. Use of this model equation to fit depletion fronts for soils highlights the importance of buffering of pH in the soil system. Furthermore, the equation should allow better understanding of the effects of important environmental variables on weathering rates. ?? 2008.

Characterization of plastic deformation and chemical reaction in titanium-polytetrafluoroethylene mixture

NASA Astrophysics Data System (ADS)

Davis, Jeffery Jon

1998-09-01

The subject of this dissertation is the deformation process of a single metal - polymer system (titanium - polytetrafluoroethylene) and how this process leads to initiation of chemical reaction. Several different kinds of experiments were performed to characterize the behavior of this material to shock and impact. These mechanical conditions induce a rapid plastic deformation of the sample. All of the samples tested had an initial porosity which increased the plastic flow condition. It is currently believed that during the deformation process two important conditions occur: removal of the oxide layer from the metal and decomposition of the polymer. These conditions allow for rapid chemical reaction. The research from this dissertation has provided insight into the complex behavior of plastic deformation and chemical reactions in titanium - polytetrafluoroethylene (PTFE, Teflon). A hydrodynamic computational code was used to model the plastic flow for correlation with the results from the experiments. The results from this work are being used to develop an ignition and growth model for metal/polymer systems. Three sets of experiments were used to examine deformation of the 80% Ti and 20% Teflon materials: drop- weight, gas gun, and split-Hopkinson pressure bar. Recovery studies included post shot analysis of the samples using x-ray diffraction. Lagrangian hydrocode DYNA2D modeling of the drop-weight tests was performed for comparison with experiments. One of the reactions know to occur is Ti + C → TiC (s) which results in an exothermic release. However, the believed initial reactions occur between Ti and fluorine which produces TixFy gases. The thermochemical code CHEETAH was used to investigate the detonation products and concentrations possible during Ti - Teflon reaction. CHEETAH shows that the Ti - fluorine reactions are thermodynamically favorable. This research represents the most comprehensive to date study of deformation induced chemical reaction in metal/polymers.

Chemical networks with inflows and outflows: a positive linear differential inclusions approach.

PubMed

Angeli, David; De Leenheer, Patrick; Sontag, Eduardo D

2009-01-01

Certain mass-action kinetics models of biochemical reaction networks, although described by nonlinear differential equations, may be partially viewed as state-dependent linear time-varying systems, which in turn may be modeled by convex compact valued positive linear differential inclusions. A result is provided on asymptotic stability of such inclusions, and applied to a ubiquitous biochemical reaction network with inflows and outflows, known as the futile cycle. We also provide a characterization of exponential stability of general homogeneous switched systems which is not only of interest in itself, but also plays a role in the analysis of the futile cycle. 2009 American Institute of Chemical Engineers

Comparison of Mars Science Laboratory Reaction Control System Jet Computations With Flow Visualization and Velocimetry

NASA Technical Reports Server (NTRS)

Bathel, Brett F.; Danehy, Paul M.; Johansen, Craig T.; Ashcraft, Scott W.; Novak, Luke A.

2013-01-01

Numerical predictions of the Mars Science Laboratory reaction control system jets interacting with a Mach 10 hypersonic flow are compared to experimental nitric oxide planar laser-induced fluorescence data. The steady Reynolds Averaged Navier Stokes equations using the Baldwin-Barth one-equation turbulence model were solved using the OVERFLOW code. The experimental fluorescence data used for comparison consists of qualitative two-dimensional visualization images, qualitative reconstructed three-dimensional flow structures, and quantitative two-dimensional distributions of streamwise velocity. Through modeling of the fluorescence signal equation, computational flow images were produced and directly compared to the qualitative fluorescence 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

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.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

Modular rate laws for enzymatic reactions: thermodynamics, elasticities and implementation.

PubMed

Liebermeister, Wolfram; Uhlendorf, Jannis; Klipp, Edda

2010-06-15

Standard rate laws are a key requisite for systematically turning metabolic networks into kinetic models. They should provide simple, general and biochemically plausible formulae for reaction velocities and reaction elasticities. At the same time, they need to respect thermodynamic relations between the kinetic constants and the metabolic fluxes and concentrations. We present a family of reversible rate laws for reactions with arbitrary stoichiometries and various types of regulation, including mass-action, Michaelis-Menten and uni-uni reversible Hill kinetics as special cases. With a thermodynamically safe parameterization of these rate laws, parameter sets obtained by model fitting, sampling or optimization are guaranteed to lead to consistent chemical equilibrium states. A reformulation using saturation values yields simple formulae for rates and elasticities, which can be easily adjusted to the given stationary flux distributions. Furthermore, this formulation highlights the role of chemical potential differences as thermodynamic driving forces. We compare the modular rate laws to the thermodynamic-kinetic modelling formalism and discuss a simplified rate law in which the reaction rate directly depends on the reaction affinity. For automatic handling of modular rate laws, we propose a standard syntax and semantic annotations for the Systems Biology Markup Language. An online tool for inserting the rate laws into SBML models is freely available at www.semanticsbml.org. Supplementary data are available at Bioinformatics online.

Structural and practical identifiability analysis of S-system.

PubMed

Zhan, Choujun; Li, Benjamin Yee Shing; Yeung, Lam Fat

2015-12-01

In the field of systems biology, biological reaction networks are usually modelled by ordinary differential equations. A sub-class, the S-systems representation, is a widely used form of modelling. Existing S-systems identification techniques assume that the system itself is always structurally identifiable. However, due to practical limitations, biological reaction networks are often only partially measured. In addition, the captured data only covers a limited trajectory, therefore data can only be considered as a local snapshot of the system responses with respect to the complete set of state trajectories over the entire state space. Hence the estimated model can only reflect partial system dynamics and may not be unique. To improve the identification quality, the structural and practical identifiablility of S-system are studied. The S-system is shown to be identifiable under a set of assumptions. Then, an application on yeast fermentation pathway was conducted. Two case studies were chosen; where the first case is based on a larger state trajectories and the second case is based on a smaller one. By expanding the dataset which span a relatively larger state space, the uncertainty of the estimated system can be reduced. The results indicated that initial concentration is related to the practical identifiablity.

Molybdenum Enzymes, Cofactors, and Model Systems.

ERIC Educational Resources Information Center

Burgmayer, S. J. N; Stiefel, E. I.

1985-01-01

Discusses: (l) molybdoenzymes (examining their distribution and metabolic role, composition and redox strategy, cofactors, substrate reactions, and mechanistic possibilities); (2) structural information on molybdenum (Mo) centers; (3) modeling studies (Mo-co models, nitrogenase models, and the MO-S duo); and (4) the copper-molybdenum antagonism.…

Formation, aggregation and reactivity of amorphous ferric oxyhydroxides on dissociation of Fe(III)-organic complexes in dilute aqueous suspensions

NASA Astrophysics Data System (ADS)

Bligh, Mark W.; Waite, T. David

2010-10-01

While chemical reactions that take place at the surface of amorphous ferric oxides (AFO) are known to be important in aquatic systems, incorporation of these reactions into kinetic models is hindered by a lack of ability to reliably quantify the reactivity of the surface and the changes in reactivity that occur over time. Long term decreases in the reactivity of iron oxides may be considered to result from changes in the molecular structure of the solid, however, over shorter time scales where substantial aggregation may occur, the mechanisms of reactivity loss are less clear. Precipitation of AFO may be described as a combination of homogeneous and heterogeneous reactions, however, despite its potentially significant role, the latter reaction is usually neglected in kinetic models of aquatic processes. Here, we investigate the role of AFO in scavenging dissolved inorganic ferric (Fe(III)) species (Fe') via the heterogeneous precipitation reaction during the net dissociation of organically complexed Fe(III) in seawater. Using sulfosalicylic acid (SSA) as a model ligand, AFO was shown to play a significant role in inducing the net dissociation of the Fe-SSA complexes with equations describing both the heterogeneous precipitation reaction and the aging of AFO being required to adequately describe the experimental data. An aggregation based mechanism provided a good description of AFO aging over the short time scale of the experiments. The behaviour of AFO described here has implications for the bioavailability of iron in natural systems as a result of reactions involving AFO which are recognised to occur over time scales of minutes, including adsorption of Fe' and AFO dissolution, precipitation and ageing.

Monte-Carlo Modeling of the Central Carbon Metabolism of Lactococcus lactis: Insights into Metabolic Regulation

PubMed Central

Murabito, Ettore; Verma, Malkhey; Bekker, Martijn; Bellomo, Domenico; Westerhoff, Hans V.; Teusink, Bas; Steuer, Ralf

2014-01-01

Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges are governed by multiple interdependencies between enzyme properties, reactions rates, and substrate levels. Understanding the dynamics arising from such a network can be greatly enhanced by the construction of a computational model that embodies the properties of the respective system. Such models aim to incorporate mechanistic details of cellular interactions to mimic the temporal behavior of the biochemical reaction system and usually require substantial knowledge of kinetic parameters to allow meaningful conclusions. Several approaches have been suggested to overcome the severe data requirements of kinetic modeling, including the use of approximative kinetics and Monte-Carlo sampling of reaction parameters. In this work, we employ a probabilistic approach to study the response of a complex metabolic system, the central metabolism of the lactic acid bacterium Lactococcus lactis, subject to perturbations and brief periods of starvation. Supplementing existing methodologies, we show that it is possible to acquire a detailed understanding of the control properties of a corresponding metabolic pathway model that is directly based on experimental observations. In particular, we delineate the role of enzymatic regulation to maintain metabolic stability and metabolic recovery after periods of starvation. It is shown that the feedforward activation of the pyruvate kinase by fructose-1,6-bisphosphate qualitatively alters the bifurcation structure of the corresponding pathway model, indicating a crucial role of enzymatic regulation to prevent metabolic collapse for low external concentrations of glucose. We argue that similar probabilistic methodologies will help our understanding of dynamic properties of small-, medium- and large-scale metabolic networks models. PMID:25268481

Generalized binomial τ-leap method for biochemical kinetics incorporating both delay and intrinsic noise

NASA Astrophysics Data System (ADS)

Leier, André; Marquez-Lago, Tatiana T.; Burrage, Kevin

2008-05-01

The delay stochastic simulation algorithm (DSSA) by Barrio et al. [Plos Comput. Biol. 2, 117(E) (2006)] was developed to simulate delayed processes in cell biology in the presence of intrinsic noise, that is, when there are small-to-moderate numbers of certain key molecules present in a chemical reaction system. These delayed processes can faithfully represent complex interactions and mechanisms that imply a number of spatiotemporal processes often not explicitly modeled such as transcription and translation, basic in the modeling of cell signaling pathways. However, for systems with widely varying reaction rate constants or large numbers of molecules, the simulation time steps of both the stochastic simulation algorithm (SSA) and the DSSA can become very small causing considerable computational overheads. In order to overcome the limit of small step sizes, various τ-leap strategies have been suggested for improving computational performance of the SSA. In this paper, we present a binomial τ-DSSA method that extends the τ-leap idea to the delay setting and avoids drawing insufficient numbers of reactions, a common shortcoming of existing binomial τ-leap methods that becomes evident when dealing with complex chemical interactions. The resulting inaccuracies are most evident in the delayed case, even when considering reaction products as potential reactants within the same time step in which they are produced. Moreover, we extend the framework to account for multicellular systems with different degrees of intercellular communication. We apply these ideas to two important genetic regulatory models, namely, the hes1 gene, implicated as a molecular clock, and a Her1/Her 7 model for coupled oscillating cells.

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

Duncan, Andrew, E-mail: a.duncan@imperial.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk; Zygalakis, Konstantinos, E-mail: k.zygalakis@ed.ac.uk

Stochasticity plays a fundamental role in various biochemical processes, such as cell regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be modelled as Markov processes, typically simulated using the Gillespie Stochastic Simulation Algorithm (SSA) [25]. While easy to implement and exact, the computational cost of using the Gillespie SSA to simulate such systems can become prohibitive as the frequency of reaction events increases. This has motivated numerous coarse-grained schemes, where the “fast” reactions are approximated either using Langevin dynamics or deterministically. While such approaches provide a good approximation when all reactants are abundant, the approximation breaks down when onemore » or more species exist only in small concentrations and the fluctuations arising from the discrete nature of the reactions become significant. This is particularly problematic when using such methods to compute statistics of extinction times for chemical species, as well as simulating non-equilibrium systems such as cell-cycle models in which a single species can cycle between abundance and scarcity. In this paper, a hybrid jump-diffusion model for simulating well-mixed stochastic kinetics is derived. It acts as a bridge between the Gillespie SSA and the chemical Langevin equation. For low reactant reactions the underlying behaviour is purely discrete, while purely diffusive when the concentrations of all species are large, with the two different behaviours coexisting in the intermediate region. A bound on the weak error in the classical large volume scaling limit is obtained, and three different numerical discretisations of the jump-diffusion model are described. The benefits of such a formalism are illustrated using computational examples.« less

Simulation of physiological systems in order to evaluate and predict the human condition in a space flight

NASA Technical Reports Server (NTRS)

Verigo, V. V.

1979-01-01

Simulation models were used to study theoretical problems of space biology and medicine. The reaction and adaptation of the main physiological systems to the complex effects of space flight were investigated. Mathematical models were discussed in terms of their significance in the selection of the structure and design of biological life support systems.

Hybrid stochastic simulation of reaction-diffusion systems with slow and fast dynamics

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

Strehl, Robert; Ilie, Silvana, E-mail: silvana@ryerson.ca

2015-12-21

In this paper, we present a novel hybrid method to simulate discrete stochastic reaction-diffusion models arising in biochemical signaling pathways. We study moderately stiff systems, for which we can partition each reaction or diffusion channel into either a slow or fast subset, based on its propensity. Numerical approaches missing this distinction are often limited with respect to computational run time or approximation quality. We design an approximate scheme that remedies these pitfalls by using a new blending strategy of the well-established inhomogeneous stochastic simulation algorithm and the tau-leaping simulation method. The advantages of our hybrid simulation algorithm are demonstrated onmore » three benchmarking systems, with special focus on approximation accuracy and efficiency.« less

Enzymatic synthesis of esculin ester in ionic liquids buffered with organic solvents.

PubMed

Hu, Yifan; Guo, Zheng; Lue, Bena-Marie; Xu, Xuebing

2009-05-13

The enzymatic esterification of esculin catalyzed by Candida antarctica lipase B (Novozym 435) was carried out in ionic liquid (IL)-organic solvent mixed systems in comparison with individual systems. The reaction behaviors in IL-organic solvents were systemically evaluated using acetone as a model solvent. With organic solvents as media, the esterification rates of esculin depended mainly on its solubility in solvents; for the reactions in ILs, the reaction rates were generally low, and the anion part of the IL played a critical role in enzyme activity. Therefore, the esterification of esculin in IL-acetone mixtures made it possible to improve the solubility of esculin while the effects of ILs on lipase activity were minimized. Following the benignity of ILs to lipase activity, the anions of ILs were ranked in the order as [Tf(2)N](-) > [PF(6)](-) > [BF(4)](-) > [CF(3)SO(3)](-) > [C(4)F(9)SO(3)](-) > [TAF](-) > [MDEGSO(4)](-) > [OctSO(4)](-) > [ES](-) = [DMP](-) = [OTs](- )= Cl(-). The reaction behaviors differed in different systems and largely depended on the properties of the ILs and organic solvents. In general, improvements were observed in terms of both solubility and reaction efficiency. The knowledge acquired in this work gives a better understanding of multiple interactions in IL-organic solvent systems, which provide guidance for system design and optimization.

Hybrid approaches for multiple-species stochastic reaction-diffusion models

NASA Astrophysics Data System (ADS)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

PubMed

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K; Byrne, Helen

2015-10-15

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

The Arrhenius equation revisited.

PubMed

Peleg, Micha; Normand, Mark D; Corradini, Maria G

2012-01-01

The Arrhenius equation has been widely used as a model of the temperature effect on the rate of chemical reactions and biological processes in foods. Since the model requires that the rate increase monotonically with temperature, its applicability to enzymatic reactions and microbial growth, which have optimal temperature, is obviously limited. This is also true for microbial inactivation and chemical reactions that only start at an elevated temperature, and for complex processes and reactions that do not follow fixed order kinetics, that is, where the isothermal rate constant, however defined, is a function of both temperature and time. The linearity of the Arrhenius plot, that is, Ln[k(T)] vs. 1/T where T is in °K has been traditionally considered evidence of the model's validity. Consequently, the slope of the plot has been used to calculate the reaction or processes' "energy of activation," usually without independent verification. Many experimental and simulated rate constant vs. temperature relationships that yield linear Arrhenius plots can also be described by the simpler exponential model Ln[k(T)/k(T(reference))] = c(T-T(reference)). The use of the exponential model or similar empirical alternative would eliminate the confusing temperature axis inversion, the unnecessary compression of the temperature scale, and the need for kinetic assumptions that are hard to affirm in food systems. It would also eliminate the reference to the Universal gas constant in systems where a "mole" cannot be clearly identified. Unless proven otherwise by independent experiments, one cannot dismiss the notion that the apparent linearity of the Arrhenius plot in many food systems is due to a mathematical property of the model's equation rather than to the existence of a temperature independent "energy of activation." If T+273.16°C in the Arrhenius model's equation is replaced by T+b, where the numerical value of the arbitrary constant b is substantially larger than T and T(reference), the plot of Ln k(T) vs. 1/(T+b) will always appear almost perfectly linear. Both the modified Arrhenius model version having the arbitrary constant b, Ln[k(T)/k(T(reference)) = a[1/ (T(reference)+b)-1/ (T+b)], and the exponential model can faithfully describe temperature dependencies traditionally described by the Arrhenius equation without the assumption of a temperature independent "energy of activation." This is demonstrated mathematically and with computer simulations, and with reprocessed classical kinetic data and published food results.

Incorporating reaction-rate dependence in reaction-front models of wellbore-cement/carbonated-brine systems

DOE PAGES

Iyer, Jaisree; Walsh, Stuart D. C.; Hao, Yue; ...

2017-03-08

Contact between wellbore cement and carbonated brine produces reaction zones that alter the cement's chemical composition and its mechanical properties. The reaction zones have profound implications on the ability of wellbore cement to serve as a seal to prevent the flow of carbonated brine. Under certain circumstances, the reactions may cause resealing of leakage pathways within the cement or at cement-interfaces; either due to fracture closure in response to mechanical weakening or due to the precipitation of calcium carbonate within the fracture. In prior work, we showed how mechanical sealing can be simulated using a diffusion-controlled reaction-front model that linksmore » the growth of the cement reaction zones to the mechanical response of the fracture. Here, we describe how such models may be extended to account for the effects of the calcite reaction-rate. We discuss how the relative rates of reaction and diffusion within the cement affect the precipitation of calcium carbonate within narrow leakage pathways, and how such behavior relates to the formation of characteristic reaction modes in the direction of flow. In addition, we compare the relative impact of precipitation and mechanical deformation on fracture sealing for a range of flow conditions and fracture apertures. Here, we conclude by considering how the prior leaching of calcium from cement may influence the sealing behavior of fractures, and the implication of prior leaching on the ability of laboratory tests to predict long-term sealing.« less

Incorporating reaction-rate dependence in reaction-front models of wellbore-cement/carbonated-brine systems

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

Iyer, Jaisree; Walsh, Stuart D. C.; Hao, Yue

Contact between wellbore cement and carbonated brine produces reaction zones that alter the cement's chemical composition and its mechanical properties. The reaction zones have profound implications on the ability of wellbore cement to serve as a seal to prevent the flow of carbonated brine. Under certain circumstances, the reactions may cause resealing of leakage pathways within the cement or at cement-interfaces; either due to fracture closure in response to mechanical weakening or due to the precipitation of calcium carbonate within the fracture. In prior work, we showed how mechanical sealing can be simulated using a diffusion-controlled reaction-front model that linksmore » the growth of the cement reaction zones to the mechanical response of the fracture. Here, we describe how such models may be extended to account for the effects of the calcite reaction-rate. We discuss how the relative rates of reaction and diffusion within the cement affect the precipitation of calcium carbonate within narrow leakage pathways, and how such behavior relates to the formation of characteristic reaction modes in the direction of flow. In addition, we compare the relative impact of precipitation and mechanical deformation on fracture sealing for a range of flow conditions and fracture apertures. Here, we conclude by considering how the prior leaching of calcium from cement may influence the sealing behavior of fractures, and the implication of prior leaching on the ability of laboratory tests to predict long-term sealing.« less

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

Partial molar enthalpies and reaction enthalpies from equilibrium molecular dynamics simulation

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

Schnell, Sondre K.; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720; Department of Chemistry, Faculty of Natural Science and Technology, Norwegian University of Science and Technology, 4791 Trondheim

2014-10-14

We present a new molecular simulation technique for determining partial molar enthalpies in mixtures of gases and liquids from single simulations, without relying on particle insertions, deletions, or identity changes. The method can also be applied to systems with chemical reactions. We demonstrate our method for binary mixtures of Weeks-Chandler-Anderson particles by comparing with conventional simulation techniques, as well as for a simple model that mimics a chemical reaction. The method considers small subsystems inside a large reservoir (i.e., the simulation box), and uses the construction of Hill to compute properties in the thermodynamic limit from small-scale fluctuations. Results obtainedmore » with the new method are in excellent agreement with those from previous methods. Especially for modeling chemical reactions, our method can be a valuable tool for determining reaction enthalpies directly from a single MD simulation.« less

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

Study of ring influence and electronic response to proton transfer reactions. Reaction electronic flux analysis.

PubMed

Herrera, Barbara

2011-05-01

In this article, a theoretical study of 1-5 proton transfers is presented. Two model systems which represent 1-5 proton transfer, 3-hidroxy-2-propenimine and salicyldenaniline have been studied as shown in Fig. 1. For this purpose, a DFT/B3LYP/6-311+G**, reaction force and reaction electronic flux analysis is made. The obtained results indicate that both proton transfers exhibit energetic and electronic differences emphasizing the role of the neighbor ring and the impact of conjugation on electronic properties.

PHYSICOCHEMICAL PROPERTY CALCULATIONS

EPA Science Inventory

Computer models have been developed to estimate a wide range of physical-chemical properties from molecular structure. The SPARC modeling system approaches calculations as site specific reactions (pKa, hydrolysis, hydration) and `whole molecule' properties (vapor pressure, boilin...

Reaction-diffusion systems coupled at the boundary and the Morse-Smale property

NASA Astrophysics Data System (ADS)

Broche, Rita de Cássia D. S.; de Oliveira, Luiz Augusto F.

We study an one-dimensional nonlinear reaction-diffusion system coupled on the boundary. Such system comes from modeling problems of temperature distribution on two bars of same length, jointed together, with different diffusion coefficients. We prove the transversality property of unstable and stable manifolds assuming all equilibrium points are hyperbolic. To this end, we write the system as an equation with noncontinuous diffusion coefficient. We then study the nonincreasing property of the number of zeros of a linearized nonautonomous equation as well as the Sturm-Liouville properties of the solutions of a linear elliptic problem.

Cooperation of catalysts and templates

NASA Technical Reports Server (NTRS)

White, D. H.; Kanavarioti, A.; Nibley, C. W.; Macklin, J. W.

1986-01-01

In order to understand how self-reproducing molecules could have originated on the primitive Earth or extraterrestrial bodies, it would be useful to find laboratory models of simple molecules which are able to carry out processes of catalysis and templating. Furthermore, it may be anticipated that systems in which several components are acting cooperatively to catalyze each other's synthesis will have different behavior with respect to natural selection than those of purely replicating systems. As the major focus of this work, laboratory models are devised to study the influence of short peptide catalysts on template reactions which produce oligonucleotides or additional peptides. Such catalysts could have been the earliest protoenzymes of selective advantage produced by replicating oligonucleotides. Since this is a complex problem, simpler systems are also studied which embody only one aspect at a time, such as peptide formation with and without a template, peptide catalysis of nontemplated peptide synthesis, and model reactions for replication of the type pioneered by Orgel.

Chemical reaction path modeling of hydrothermal processes on Mars: Preliminary results

NASA Technical Reports Server (NTRS)

Plumlee, Geoffrey S.; Ridley, W. Ian

1992-01-01

Hydrothermal processes are thought to have had significant roles in the development of surficial mineralogies and morphological features on Mars. For example, a significant proportion of the Martian soil could consist of the erosional products of hydrothermally altered impact melt sheets. In this model, impact-driven, vapor-dominated hydrothermal systems hydrothermally altered the surrounding rocks and transported volatiles such as S and Cl to the surface. Further support for impact-driven hydrothermal alteration on Mars was provided by studies of the Ries crater, Germany, where suevite deposits were extensively altered to montmorillonite clays by inferred low-temperature (100-130 C) hydrothermal fluids. It was also suggested that surface outflow from both impact-driven and volcano-driven hydrothermal systems could generate the valley networks, thereby eliminating the need for an early warm wet climate. We use computer-driven chemical reaction path calculation to model chemical processes which were likely associated with postulated Martian hydrothermal systems.

Non-Archimedean reaction-ultradiffusion equations and complex hierarchic systems

NASA Astrophysics Data System (ADS)

Zúñiga-Galindo, W. A.

2018-06-01

We initiate the study of non-Archimedean reaction-ultradiffusion equations and their connections with models of complex hierarchic systems. From a mathematical perspective, the equations studied here are the p-adic counterpart of the integro-differential models for phase separation introduced by Bates and Chmaj. Our equations are also generalizations of the ultradiffusion equations on trees studied in the 1980s by Ogielski, Stein, Bachas, Huberman, among others, and also generalizations of the master equations of the Avetisov et al models, which describe certain complex hierarchic systems. From a physical perspective, our equations are gradient flows of non-Archimedean free energy functionals and their solutions describe the macroscopic density profile of a bistable material whose space of states has an ultrametric structure. Some of our results are p-adic analogs of some well-known results in the Archimedean setting, however, the mechanism of diffusion is completely different due to the fact that it occurs in an ultrametric space.

A Light-Induced Reaction with Oxygen Leads to Chromophore Decomposition and Irreversible Photobleaching in GFP-Type Proteins.

PubMed

Grigorenko, Bella L; Nemukhin, Alexander V; Polyakov, Igor V; Khrenova, Maria G; Krylov, Anna I

2015-04-30

Photobleaching and photostability of proteins of the green fluorescent protein (GFP) family are crucially important for practical applications of these widely used biomarkers. On the basis of simulations, we propose a mechanism for irreversible bleaching in GFP-type proteins under intense light illumination. The key feature of the mechanism is a photoinduced reaction of the chromophore with molecular oxygen (O2) inside the protein barrel leading to the chromophore's decomposition. Using quantum mechanics/molecular mechanics (QM/MM) modeling we show that a model system comprising the protein-bound Chro(-) and O2 can be excited to an electronic state of the intermolecular charge-transfer (CT) character (Chro(•)···O2(-•)). Once in the CT state, the system undergoes a series of chemical reactions with low activation barriers resulting in the cleavage of the bridging bond between the phenolic and imidazolinone rings and disintegration of the chromophore.

Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems.

PubMed

Winkelmann, Stefanie; Schütte, Christof

2017-09-21

Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems

NASA Astrophysics Data System (ADS)

Winkelmann, Stefanie; Schütte, Christof

2017-09-01

Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

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.

A general moment expansion method for stochastic kinetic models

NASA Astrophysics Data System (ADS)

Ale, Angelique; Kirk, Paul; Stumpf, Michael P. H.

2013-05-01

Moment approximation methods are gaining increasing attention for their use in the approximation of the stochastic kinetics of chemical reaction systems. In this paper we derive a general moment expansion method for any type of propensities and which allows expansion up to any number of moments. For some chemical reaction systems, more than two moments are necessary to describe the dynamic properties of the system, which the linear noise approximation is unable to provide. Moreover, also for systems for which the mean does not have a strong dependence on higher order moments, moment approximation methods give information about higher order moments of the underlying probability distribution. We demonstrate the method using a dimerisation reaction, Michaelis-Menten kinetics and a model of an oscillating p53 system. We show that for the dimerisation reaction and Michaelis-Menten enzyme kinetics system higher order moments have limited influence on the estimation of the mean, while for the p53 system, the solution for the mean can require several moments to converge to the average obtained from many stochastic simulations. We also find that agreement between lower order moments does not guarantee that higher moments will agree. Compared to stochastic simulations, our approach is numerically highly efficient at capturing the behaviour of stochastic systems in terms of the average and higher moments, and we provide expressions for the computational cost for different system sizes and orders of approximation. We show how the moment expansion method can be employed to efficiently quantify parameter sensitivity. Finally we investigate the effects of using too few moments on parameter estimation, and provide guidance on how to estimate if the distribution can be accurately approximated using only a few moments.

Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.

PubMed

Rappoport, Dmitrij; Galvin, Cooper J; Zubarev, Dmitry Yu; Aspuru-Guzik, Alán

2014-03-11

While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.

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

Master Equation Analysis of Thermal and Nonthermal Microwave Effects.

PubMed

Ma, Jianyi

2016-10-11

Master equation is a successful model to describe the conventional heating reaction, it is expanded to capture the "microwave effect" in this work. The work equation of "microwave effect" included master equation presents the direct heating, indirect heating, and nonthermal effect about the microwave field. The modified master equation provides a clear physics picture to the nonthermal microwave effect: (1) The absorption and the emission of the microwave, which is dominated by the transition dipole moment between two corresponding states and the intensity of the microwave field, provides a new path to change the reaction rate constants. (2) In the strong microwave field, the distribution of internal states of the molecules will deviate from the equilibrium distribution, and the system temperature defined in the conventional heating reaction is no longer available. According to the general form of "microwave effect" included master equation, a two states model for unimolecular dissociation is proposed and is used to discuss the microwave nonthermal effect particularly. The average rate constants can be increased up to 2400 times for some given cases without the temperature changed in the two states model. Additionally, the simulation of a model system was executed using our State Specified Master Equation package. Three important conclusions can be obtained in present work: (1) A reasonable definition of the nonthermal microwave effect is given in the work equation of "microwave effect" included master equation. (2) Nonthermal microwave effect possibly exists theoretically. (3) The reaction rate constants perhaps can be changed obviously by the microwave field for the non-RRKM and the mode-specified reactions.

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.

The oleic acid-ozone heterogeneous reaction system: products, kinetics, secondary chemistry, and atmospheric implications of a model system a review

NASA Astrophysics Data System (ADS)

Zahardis, J.; Petrucci, G. A.

2006-11-01

The heterogeneous processing of organic aerosols by trace oxidants has many implications to atmospheric chemistry and climate regulation. This review covers a model heterogeneous reaction system (HRS): the oleic acid-ozone HRS and other reaction systems featuring fatty acids, and their derivatives. The analysis of the primary products of ozonolysis (azelaic acid, nonanoic acid, 9-oxononanoic acid, nonanal) is described. Anomalies in the relative product yields are noted and explained by the observation of secondary chemical reactions. The secondary reaction products arising from reactive Criegee intermediates are mainly peroxidic, notably secondary ozonides and α-acyloxyalkyl hydroperoxide polymers. These highly oxygenated products are of low volatility and hydrophilic which may enhance the ability of particles to act as cloud condensation nuclei. The kinetic description of this HRS is critically reviewed. Most kinetic studies suggest this oxidative processing is either a near surface reaction that is limited by the diffusion of ozone or a surface based reaction. Internally mixed particles and coatings represent the next stage in the progression towards more realistic proxies of tropospheric organic aerosols and a description of the products and the kinetics resulting from the ozonolysis of these proxies, which are based on fatty acids or their derivatives, is presented. Finally, a series of atmospheric implications of oxidative processing of particulate containing fatty acids is presented. These implications include the extended lifetime of unsaturated species in the troposphere facilitated by the presence of solids, semisolids or viscous phases, and an enhanced rate of ozone uptake by particulate unsaturates compared to corresponding gas phase organics. Ozonolysis of oleic acid enhances its CCN activity, which implies that oxidatively processed particulate may contribute to indirect forcing of radiation. Other effects, including the potential role of aldehydic products of ozonolysis in increasing the oxidative capacity of the troposphere, are also discussed.

The oleic acid-ozone heterogeneous reaction system: products, kinetics, secondary chemistry, and atmospheric implications of a model system - a review

NASA Astrophysics Data System (ADS)

Zahardis, J.; Petrucci, G. A.

2007-02-01

The heterogeneous processing of organic aerosols by trace oxidants has many implications to atmospheric chemistry and climate regulation. This review covers a model heterogeneous reaction system (HRS): the oleic acid-ozone HRS and other reaction systems featuring fatty acids, and their derivatives. The analysis of the commonly observed aldehyde and organic acid products of ozonolysis (azelaic acid, nonanoic acid, 9-oxononanoic acid, nonanal) is described. The relative product yields are noted and explained by the observation of secondary chemical reactions. The secondary reaction products arising from reactive Criegee intermediates are mainly peroxidic, notably secondary ozonides and α-acyloxyalkyl hydroperoxide oligomers and polymers, and their formation is in accord with solution and liquid-phase ozonolysis. These highly oxygenated products are of low volatility and hydrophilic which may enhance the ability of particles to act as cloud condensation nuclei (CCN). The kinetic description of this HRS is critically reviewed. Most kinetic studies suggest this oxidative processing is either a near surface reaction that is limited by the diffusion of ozone or a surface based reaction. Internally mixed particles and coatings represent the next stage in the progression towards more realistic proxies of tropospheric organic aerosols and a description of the products and the kinetics resulting from the ozonolysis of these proxies, which are based on fatty acids or their derivatives, is presented. Finally, the main atmospheric implications of oxidative processing of particulate containing fatty acids are presented. These implications include the extended lifetime of unsaturated species in the troposphere facilitated by the presence of solids, semi-solids or viscous phases, and an enhanced rate of ozone uptake by particulate unsaturates compared to corresponding gas-phase organics. Ozonolysis of oleic acid enhances its CCN activity, which implies that oxidatively processed particulate may contribute to indirect forcing of radiation.

Theory of bi-molecular association dynamics in 2D for accurate model and experimental parameterization of binding rates

PubMed Central

Yogurtcu, Osman N.; Johnson, Margaret E.

2015-01-01

The dynamics of association between diffusing and reacting molecular species are routinely quantified using simple rate-equation kinetics that assume both well-mixed concentrations of species and a single rate constant for parameterizing the binding rate. In two-dimensions (2D), however, even when systems are well-mixed, the assumption of a single characteristic rate constant for describing association is not generally accurate, due to the properties of diffusional searching in dimensions d ≤ 2. Establishing rigorous bounds for discriminating between 2D reactive systems that will be accurately described by rate equations with a single rate constant, and those that will not, is critical for both modeling and experimentally parameterizing binding reactions restricted to surfaces such as cellular membranes. We show here that in regimes of intrinsic reaction rate (ka) and diffusion (D) parameters ka/D > 0.05, a single rate constant cannot be fit to the dynamics of concentrations of associating species independently of the initial conditions. Instead, a more sophisticated multi-parametric description than rate-equations is necessary to robustly characterize bimolecular reactions from experiment. Our quantitative bounds derive from our new analysis of 2D rate-behavior predicted from Smoluchowski theory. Using a recently developed single particle reaction-diffusion algorithm we extend here to 2D, we are able to test and validate the predictions of Smoluchowski theory and several other theories of reversible reaction dynamics in 2D for the first time. Finally, our results also mean that simulations of reactive systems in 2D using rate equations must be undertaken with caution when reactions have ka/D > 0.05, regardless of the simulation volume. We introduce here a simple formula for an adaptive concentration dependent rate constant for these chemical kinetics simulations which improves on existing formulas to better capture non-equilibrium reaction dynamics from dilute to dense systems. PMID:26328828

Spatiotemporal pattern formation in a prey-predator model under environmental driving forces

NASA Astrophysics Data System (ADS)

Sirohi, Anuj Kumar; Banerjee, Malay; Chakraborti, Anirban

2015-09-01

Many existing studies on pattern formation in the reaction-diffusion systems rely on deterministic models. However, environmental noise is often a major factor which leads to significant changes in the spatiotemporal dynamics. In this paper, we focus on the spatiotemporal patterns produced by the predator-prey model with ratio-dependent functional response and density dependent death rate of predator. We get the reaction-diffusion equations incorporating the self-diffusion terms, corresponding to random movement of the individuals within two dimensional habitats, into the growth equations for the prey and predator population. In order to have the noise added model, small amplitude heterogeneous perturbations to the linear intrinsic growth rates are introduced using uncorrelated Gaussian white noise terms. For the noise added system, we then observe spatial patterns for the parameter values lying outside the Turing instability region. With thorough numerical simulations we characterize the patterns corresponding to Turing and Turing-Hopf domain and study their dependence on different system parameters like noise-intensity, etc.

Partitioned coupling of advection-diffusion-reaction systems and Brinkman flows

NASA Astrophysics Data System (ADS)

Lenarda, Pietro; Paggi, Marco; Ruiz Baier, Ricardo

2017-09-01

We present a partitioned algorithm aimed at extending the capabilities of existing solvers for the simulation of coupled advection-diffusion-reaction systems and incompressible, viscous flow. The space discretisation of the governing equations is based on mixed finite element methods defined on unstructured meshes, whereas the time integration hinges on an operator splitting strategy that exploits the differences in scales between the reaction, advection, and diffusion processes, considering the global system as a number of sequentially linked sets of partial differential, and algebraic equations. The flow solver presents the advantage that all unknowns in the system (here vorticity, velocity, and pressure) can be fully decoupled and thus turn the overall scheme very attractive from the computational perspective. The robustness of the proposed method is illustrated with a series of numerical tests in 2D and 3D, relevant in the modelling of bacterial bioconvection and Boussinesq systems.

Estimation of parameters in rational reaction rates of molecular biological systems via weighted least squares

NASA Astrophysics Data System (ADS)

Wu, Fang-Xiang; Mu, Lei; Shi, Zhong-Ke

2010-01-01

The models of gene regulatory networks are often derived from statistical thermodynamics principle or Michaelis-Menten kinetics equation. As a result, the models contain rational reaction rates which are nonlinear in both parameters and states. It is challenging to estimate parameters nonlinear in a model although there have been many traditional nonlinear parameter estimation methods such as Gauss-Newton iteration method and its variants. In this article, we develop a two-step method to estimate the parameters in rational reaction rates of gene regulatory networks via weighted linear least squares. This method takes the special structure of rational reaction rates into consideration. That is, in the rational reaction rates, the numerator and the denominator are linear in parameters. By designing a special weight matrix for the linear least squares, parameters in the numerator and the denominator can be estimated by solving two linear least squares problems. The main advantage of the developed method is that it can produce the analytical solutions to the estimation of parameters in rational reaction rates which originally is nonlinear parameter estimation problem. The developed method is applied to a couple of gene regulatory networks. The simulation results show the superior performance over Gauss-Newton method.

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.

Multi-fluid CFD analysis in Process Engineering

NASA Astrophysics Data System (ADS)

Hjertager, B. H.

2017-12-01

An overview of modelling and simulation of flow processes in gas/particle and gas/liquid systems are presented. Particular emphasis is given to computational fluid dynamics (CFD) models that use the multi-dimensional multi-fluid techniques. Turbulence modelling strategies for gas/particle flows based on the kinetic theory for granular flows are given. Sub models for the interfacial transfer processes and chemical kinetics modelling are presented. Examples are shown for some gas/particle systems including flow and chemical reaction in risers as well as gas/liquid systems including bubble columns and stirred tanks.

Exploring Novel Tools for Assessing High School Students' Meaningful Understanding of Organic Reactions

ERIC Educational Resources Information Center

Vachliotis, Theodoros; Salta, Katerina; Vasiliou, Petroula; Tzougraki, Chryssa

2011-01-01

Systemic assessment questions (SAQs) are novel assessment tools used in the context of the Systemic Approach to Teaching and Learning (SATL) model. The purpose of this model is to enhance students' meaningful understanding of scientific concepts by use of constructivist concept mapping procedures, which emphasize the development of systems…

Thermodynamics of random reaction networks.

PubMed

Fischer, Jakob; Kleidon, Axel; Dittrich, Peter

2015-01-01

Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha) and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa -1.5 for linear and -1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks.

Thermodynamics of Random Reaction Networks

PubMed Central

Fischer, Jakob; Kleidon, Axel; Dittrich, Peter

2015-01-01

Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha) and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa −1.5 for linear and −1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks. PMID:25723751

Magnetic field effects on exciplex-forming systems: the effect on the locally excited fluorophore and its dependence on free energy.

PubMed

Kattnig, Daniel R; Rosspeintner, Arnulf; Grampp, Günter

2011-02-28

This study addresses magnetic field effects in exciplex forming donor-acceptor systems. For moderately exergonic systems, the exciplex and the locally excited fluorophore emission are found to be magneto-sensitive. A previously introduced model attributing this finding to excited state reversibility is confirmed. Systems characterised by a free energy of charge separation up to approximately -0.35 eV are found to exhibit a magnetic field effect on the fluorophore. A simple three-state model of the exciplex is introduced, which uses the reaction distance and the asymmetric electron transfer reaction coordinate as pertinent variables. Comparing the experimental emission band shapes with those predicted by the model, a semi-quantitative picture of the formation of the magnetic field effect is developed based on energy hypersurfaces. The model can also be applied to estimate the indirect contribution of the exchange interaction, even if the perturbative approach fails. The energetic parameters that are essential for the formation of large magnetic field effects on the exciplex are discussed.

Effects of certain polyphenols and extracts on furans and acrylamide formation in model system, and total furans during storage.

PubMed

Oral, Rasim Alper; Dogan, Mahmut; Sarioglu, Kemal

2014-01-01

Using a glucose-glycine and asparagine-fructose system as a Maillard reaction model, the effects of seven polyphenols and solid phase extracts of three plants on the formation of furans and acrylamide were investigated. The polyphenols and extracts were used in biscuit formulation and acrylamide formation was observed. They were used for the storage of the glycine-glucose model system at three different temperatures. The addition of some of the extracts and polyphenols significantly decreased furan formation to different extents. All phenolic compounds and plant extracts decreased in the range of 30.8-85% in the model system except for oleuropein, and all of them decreased in the range of 10.3-19.2% in biscuit. Total furan formation was inhibited by caffeic acid, punicalagin, epicatechin, ECE and PPE during storage. This study evaluated and found the inhibitory effect on the formation of furans and acrylamide in Maillard reactions by the use of some plant extracts and polyphenols. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

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.

Temperature-programmed natural convection for micromixing and biochemical reaction in a single microfluidic chamber.

PubMed

Kim, Sung-Jin; Wang, Fang; Burns, Mark A; Kurabayashi, Katsuo

2009-06-01

Micromixing is a crucial step for biochemical reactions in microfluidic networks. A critical challenge is that the system containing micromixers needs numerous pumps, chambers, and channels not only for the micromixing but also for the biochemical reactions and detections. Thus, a simple and compatible design of the micromixer element for the system is essential. Here, we propose a simple, yet effective, scheme that enables micromixing and a biochemical reaction in a single microfluidic chamber without using any pumps. We accomplish this process by using natural convection in conjunction with alternating heating of two heaters for efficient micromixing, and by regulating capillarity for sample transport. As a model application, we demonstrate micromixing and subsequent polymerase chain reaction (PCR) for an influenza viral DNA fragment. This process is achieved in a platform of a microfluidic cartridge and a microfabricated heating-instrument with a fast thermal response. Our results will significantly simplify micromixing and a subsequent biochemical reaction that involves reagent heating in microfluidic networks.

A biocatalytic cascade with several output signals—towards biosensors with different levels of confidence

PubMed Central

Guz, Nataliia; Halámek, Jan; Rusling, James F.; Katz, Evgeny

2014-01-01

The biocatalytic cascade based on enzyme-catalyzed reactions activated by several biomolecular input signals and producing output signal after each reaction step was developed as an example of a logically reversible information processing system. The model system was designed to mimic the operation of concatenated AND logic gates with optically readable output signals generated at each step of the logic operation. Implications include concurrent bioanalyses and data interpretation for medical diagnostics. PMID:24748446

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

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

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. In this work, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We demonstratemore » the modeling approach with the example of chalcopyrite Cu(InGa)(SeS){sub 2} thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS){sub 2} thin films arises and persists. We believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

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

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. Here, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We also demonstrate themore » modeling approach with the example of chalcopyrite Cu(InGa)(SeS) 2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS) 2 thin films arises and persists. Finally, we believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

A stochastic model of solid state thin film deposition: Application to chalcopyrite growth

DOE PAGES

Lovelett, Robert J.; Pang, Xueqi; Roberts, Tyler M.; ...

2016-04-01

Developing high fidelity quantitative models of solid state reaction systems can be challenging, especially in deposition systems where, in addition to the multiple competing processes occurring simultaneously, the solid interacts with its atmosphere. Here, we develop a model for the growth of a thin solid film where species from the atmosphere adsorb, diffuse, and react with the film. The model is mesoscale and describes an entire film with thickness on the order of microns. Because it is stochastic, the model allows us to examine inhomogeneities and agglomerations that would be impossible to characterize with deterministic methods. We also demonstrate themore » modeling approach with the example of chalcopyrite Cu(InGa)(SeS) 2 thin film growth via precursor reaction, which is a common industrial method for fabricating thin film photovoltaic modules. The model is used to understand how and why through-film variation in the composition of Cu(InGa)(SeS) 2 thin films arises and persists. Finally, we believe that the model will be valuable as an effective quantitative description of many other materials systems used in semiconductors, energy storage, and other fast-growing industries.« less

An internally consistent inverse model to calculate ridge-axis hydrothermal fluxes

NASA Astrophysics Data System (ADS)

Coogan, L. A.; Dosso, S.

2010-12-01

Fluid and chemical fluxes from high-temperature, on-axis, hydrothermal systems at mid-ocean ridges have been estimated in a number of ways. These generally use simple mass balances based on either vent fluid compositions or the compositions of altered sheeted dikes. Here we combine these approaches in an internally consistent model. Seawater is assumed to enter the crust and react with the sheeted dike complex at high temperatures. Major element fluxes for both the rock and fluid are calculated from balanced stoichiometric reactions. These reactions include end-member components of the minerals plagioclase, pyroxene, amphibole, chlorite and epidote along with pure anhydrite, quartz, pyrite, pyrrhotite, titanite, magnetite, ilmenite and ulvospinel and the fluid species H2O, Mg2+, Ca2+, Fe2+, Na+, Si4+, H2S, H+ and H2. Trace element abundances (Li, B, K, Rb, Cs, Sr, Ba, U, Tl, Mn, Cu, Zn, Co, Ni, Pb and Os) and isotopic ratios (Li, B, O, Sr, Tl, Os) are calculated from simple mass balance of a fluid-rock reaction. A fraction of the Cu, Zn, Pb, Co, Ni, Os and Mn in the fluid after fluid-rock reaction is allowed to precipitate during discharge before the fluid reaches the seafloor. S-isotopes are tied to mineralogical reactions involving S-bearing phases. The free parameters in the model are the amounts of each mineralogical reaction that occurs, the amounts of the metals precipitated during discharge, and the water-to-rock ratio. These model parameters, and their uncertainties, are constrained by: (i) mineral abundances and mineral major element compositions in altered dikes from ODP Hole 504B and the Pito and Hess Deep tectonic windows (EPR crust); (ii) changes in dike bulk-rock trace element and isotopic compositions from these locations relative to fresh MORB glass compositions; and (iii) published vent fluid compositions from basalt-hosted high-temperature ridge axis hydrothermal systems. Using a numerical inversion algorithm, the probability density of different model parameter sets has been computed and thus the probability of different fluid and chemical fluxes. Most data can be fit by the model within their uncertainty. The entire dataset is best-fit with a water-to-rock mass ratio between 1.3 and 2.1 (~1 to 1.5 x10**13 kg yr-1) implying a substantial fraction of the magmatic (latent) heat available to drive the axial hydrothermal system is extracted by these systems. Many element fluxes are better constrained than in previous studies (e.g., Sr: 2 to 7 x10**8 moles yr-1; Ca: 2 to 7 x10**11 moles yr-1). Future developments will use experimental data to further constrain the model.

Feedback, Mass Conservation and Reaction Kinetics Impact the Robustness of Cellular Oscillations

PubMed Central

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

2016-01-01

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

Thermochemical and Kinetics of Hydrazine Dehydrogenation by an Oxygen Atom in Hydrazine-Rich Systems: A Dimer Model.

PubMed

Spada, Rene F K; Ferrão, Luiz F A; Roberto-Neto, Orlando; Lischka, Hans; Machado, Francisco B C

2015-12-24

The kinetics of the reaction of N2H4 with oxygen depends sensitively on the initial conditions used. In oxygen-rich systems, the rate constant shows a conventional positive temperature dependence, while in hydrazine-rich setups the dependence is negative in certain temperature ranges. In this study, a theoretical model is presented that adequately reproduces the experimental results trend and values for hydrazine-rich environment, consisting of the hydrogen abstraction from the hydrazine (N2H4) dimer by an oxygen atom. The thermochemical properties of the reaction were computed using two quantum chemical approaches, the coupled cluster theory with single, double, and noniterative triple excitations (CCSD(T)) and the M06-2X DFT approach with the aug-cc-pVTZ and the maug-cc-pVTZ basis sets, respectively. The kinetic data were calculated with the improved canonical variational theory (ICVT) using a dual-level methodology to build the reaction path. The tunneling effects were considered by means of the small curvature tunneling (SCT) approximation. Potential wells on both sides of the reaction ((N2H4)2 + O → N2H4···N2H3 + OH) were determined. A reaction path with a negative activation energy was found leading, in the temperature range of 250-423 K, to a negative dependence of the rate constant on the temperature, which is in good agreement with the experimental measurements. Therefore, the consideration of the hydrazine dimer model provides significantly improved agreement with the experimental data and should be included in the mechanism of the global N2H4 combustion process, as it can be particularly important in hydrazine-rich systems.

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.

Resonances in the cumulative reaction probability for a model electronically nonadiabatic reaction

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

Qi, J.; Bowman, J.M.

1996-05-01

The cumulative reaction probability, flux{endash}flux correlation function, and rate constant are calculated for a model, two-state, electronically nonadiabatic reaction, given by Shin and Light [S. Shin and J. C. Light, J. Chem. Phys. {bold 101}, 2836 (1994)]. We apply straightforward generalizations of the flux matrix/absorbing boundary condition approach of Miller and co-workers to obtain these quantities. The upper adiabatic electronic potential supports bound states, and these manifest themselves as {open_quote}{open_quote}recrossing{close_quote}{close_quote} resonances in the cumulative reaction probability, at total energies above the barrier to reaction on the lower adiabatic potential. At energies below the barrier, the cumulative reaction probability for themore » coupled system is shifted to higher energies relative to the one obtained for the ground state potential. This is due to the effect of an additional effective barrier caused by the nuclear kinetic operator acting on the ground state, adiabatic electronic wave function, as discussed earlier by Shin and Light. Calculations are reported for five sets of electronically nonadiabatic coupling parameters. {copyright} {ital 1996 American Institute of Physics.}« less

Development of a Computational Chemical Vapor Deposition Model: Applications to Indium Nitride and Dicyanovinylaniline

NASA Technical Reports Server (NTRS)

Cardelino, Carlos

1999-01-01

A computational chemical vapor deposition (CVD) model is presented, that couples chemical reaction mechanisms with fluid dynamic simulations for vapor deposition experiments. The chemical properties of the systems under investigation are evaluated using quantum, molecular and statistical mechanics models. The fluid dynamic computations are performed using the CFD-ACE program, which can simulate multispecies transport, heat and mass transfer, gas phase chemistry, chemistry of adsorbed species, pulsed reactant flow and variable gravity conditions. Two experimental setups are being studied, in order to fabricate films of: (a) indium nitride (InN) from the gas or surface phase reaction of trimethylindium and ammonia; and (b) 4-(1,1)dicyanovinyl-dimethylaminoaniline (DCVA) by vapor deposition. Modeling of these setups requires knowledge of three groups of properties: thermodynamic properties (heat capacity), transport properties (diffusion, viscosity, and thermal conductivity), and kinetic properties (rate constants for all possible elementary chemical reactions). These properties are evaluated using computational methods whenever experimental data is not available for the species or for the elementary reactions. The chemical vapor deposition model is applied to InN and DCVA. Several possible InN mechanisms are proposed and analyzed. The CVD model simulations of InN show that the deposition rate of InN is more efficient when pulsing chemistry is used under conditions of high pressure and microgravity. An analysis of the chemical properties of DCVA show that DCVA dimers may form under certain conditions of physical vapor transport. CVD simulations of the DCVA system suggest that deposition of the DCVA dimer may play a small role in the film and crystal growth processes.

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.

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.

Liquid phase products and solid deposit formation from thermally stressed model jet fuels

NASA Technical Reports Server (NTRS)

Kim, W. S.; Bittker, D. A.

1984-01-01

The relationship between solid deposit formation and liquid degradation product concentration was studied for the high temperature (400 C) stressing of three hydrocarbon model fuels. A Jet Fuel Thermal Oxidation Tester was used to simulate actual engine fuel system conditions. The effects of fuel type, dissolved oxygen concentration, and hot surface contact time (reaction time) were studied. Effects of reaction time and removal of dissolved oxygen on deposit formation were found to be different for n-dodecane and for 2-ethylnaphthalene. When ten percent tetralin is added to n-dodecane to give a simpler model of an actual jet fuel, the tetralin inhibits both the deposit formation and the degradation of n-dodecane. For 2-ethylnaphthalene primary product analyses indicate a possible self-inhibition at long reaction times of the secondary reactions which form the deposit precursors. The mechanism of the primary breakdown of these fuels is suggested and the primary products which participate in these precursor-forming reactions are identified. Some implications of the results to the thermal degradation of real jet fuels are given.

Incomplete Mixing and Reactions - A Lagrangian Approach in a Pure Shear Flow

NASA Astrophysics Data System (ADS)

Paster, A.; Aquino, T.; Bolster, D.

2014-12-01

Incomplete mixing of reactive solutes is well known to slow down reaction rates relative to what would be expected from assuming perfect mixing. As reactions progress in a system and deplete reactant concentrations, initial fluctuations in the concentrations of reactions can be amplified relative to mean background concentrations and lead to spatial segregation of reactants. As the system evolves, in the absence of sufficient mixing, this segregation will increase, leading to a persistence of incomplete mixing that fundamentally changes the effective rate at which overall reactions will progress. On the other hand, non-uniform fluid flows are known to affect mixing between interacting solutes. Thus a natural question arises: Can non-uniform flows sufficiently enhance mixing to suppress incomplete mixing effects, and if so, under what conditions? In this work we address this question by considering one of the simplest possible flows, a laminar pure shear flow, which is known to significantly enhance mixing relative to diffusion alone. To study this system we adapt a novel Lagrangian particle-based random walk method, originally designed to simulate reactions in purely diffusive systems, to the case of advection and diffusion in a shear flow. To interpret the results we develop a semi-analytical solution, by proposing a closure approximation that aims to capture the effect of incomplete mixing. The results obtained via the Lagrangian model and the semi-analytical solutions consistently highlight that if shear effects in the system are not sufficiently strong, incomplete mixing effects initially similar to purely diffusive systems will occur, slowing down the overall reaction rate. Then, at some later time, dependent on the strength of the shear, the system will return to behaving as if it were well-mixed, but represented by a reduced effective reaction rate. If shear effects are sufficiently strong, the incomplete mixing regime never emerges and the system can behave as well-mixed at all times.

Incomplete Mixing and Reactions - A Lagrangian Approach in a Pure Shear Flow

NASA Astrophysics Data System (ADS)

Paster, Amir; Bolster, Diogo; Aquino, Tomas

2015-04-01

Incomplete mixing of reactive solutes is well known to slow down reaction rates relative to what would be expected from assuming perfect mixing. As reactions progress in a system and deplete reactant concentrations, initial fluctuations in the concentrations of reactions can be amplified relative to mean background concentrations and lead to spatial segregation of reactants. As the system evolves, in the absence of sufficient mixing, this segregation will increase, leading to a persistence of incomplete mixing that fundamentally changes the effective rate at which overall reactions will progress. On the other hand, nonuniform fluid flows are known to affect mixing between interacting solutes. Thus a natural question arises: Can non-uniform flows sufficiently enhance mixing to suppress incomplete mixing effects, and if so, under what conditions? In this work we address this question by considering one of the simplest possible flows, a laminar pure shear flow, which is known to significantly enhance mixing relative to diffusion alone. To study this system we adapt a novel Lagrangian particle-based random walk method, originally designed to simulate reactions in purely diffusive systems, to the case of advection and diffusion in a shear flow. To interpret the results we develop a semi-analytical solution, by proposing a closure approximation that aims to capture the effect of incomplete mixing. The results obtained via the Lagrangian model and the semi-analytical solutions consistently highlight that if shear effects in the system are not sufficiently strong, incomplete mixing effects initially similar to purely diffusive systems will occur, slowing down the overall reaction rate. Then, at some later time, dependent on the strength of the shear, the system will return to behaving as if it were well-mixed, but represented by a reduced effective reaction rate. If shear effects are sufficiently strong, the incomplete mixing regime never emerges and the system can behave as well-mixed at all times.

On site experiments of the slanted soil treatment systems for domestic gray water.

PubMed

Itayama, Tomoaki; Kiji, Masato; Suetsugu, Aya; Tanaka, Nobuyuki; Saito, Takeshi; Iwami, Norio; Mizuochi, Motoyuki; Inamori, Yuhei

2006-01-01

In order to make a breakthrough for the acute problem of water shortage in the world, the key words "decentralization and re-use" are very important for new sustainable sanitation systems that will be developed. Therefore, we focused on a new treatments system called "a slanted soil treatment system" which combines a biotoilet system with a domestic grey water treatment system. Because this system is a low cost and compact system, the system can be easily introduced to homes in urban areas or in the suburbs of cities in many developing countries. In this study, we performed on site experiments carried out on Shikoku Island, Japan, for several years. We obtained the following results. The slanted soil treatment system could remove organic pollutants and total nitrogen and total phosphorus in grey water effectively. Furthermore, the system performance became high in the case of the high concentration of the influent water. The nitrification reaction and denitrification reaction were speculated to exist due to aerobic zones and anaerobic zones present in the slanted soil treatment system. The slanted soil treatment system could perform for approximately 3 years with zero maintenance. The plug flow model of 1st order reaction kinetics could describe the reaction in the slanted soil treatment system. However, it is necessary to improve the system to maintain the performance in all seasons.

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.

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

Stochastic hybrid systems for studying biochemical processes.

PubMed

Singh, Abhyudai; Hespanha, João P

2010-11-13

Many protein and mRNA species occur at low molecular counts within cells, and hence are subject to large stochastic fluctuations in copy numbers over time. Development of computationally tractable frameworks for modelling stochastic fluctuations in population counts is essential to understand how noise at the cellular level affects biological function and phenotype. We show that stochastic hybrid systems (SHSs) provide a convenient framework for modelling the time evolution of population counts of different chemical species involved in a set of biochemical reactions. We illustrate recently developed techniques that allow fast computations of the statistical moments of the population count, without having to run computationally expensive Monte Carlo simulations of the biochemical reactions. Finally, we review different examples from the literature that illustrate the benefits of using SHSs for modelling biochemical processes.

About the Barriers to Reaction of CCl4 with HFeOH and FeCl2

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

Ginovska-Pangovska, Bojana; Camaioni, Donald M.; Dupuis, Michel

2011-08-11

The reactivity of iron nanoparticles in aqueous environments has received considerable attention due to their potential utilization in environmental remediation technologies. As part of a broader program aiming at an improved understanding of the mechanisms involved in the degradation of harmful chlorocarbons, joint experimental and computational studies of model systems were initiated. We previously reported on the reaction of one and two Fe atoms reactions with carbon tetrachloride (CCl4) in direct mimic of “atom-dropping” experiments, with insights into the formation of novel iron-carbon-chlorine complexes, their structures and possible reaction mechanisms. Increasing the level of complexity, we report here on themore » modeling of the reaction of HFeOH and CCl4 as companion research of recent ultra high vacuum experiments of the reaction of Fe with water and CCl4. HFeOH is a stable molecular species formed in the reaction of Fe with H2O. Experimentally the (Fe, H2O, CCl4) system showed no reactivity up to the desorption temperature of CCl4. Electron correlated CCSD(T) calculations (at DFT(B3LYP) optimized structures) indicated an energy barrier to reactivity of 24.5 kcal/mol following the formation of a stable ( 7.5 kcal/mol) long-range precursor complex. This finding is consistent with the lack of experimentally detected reaction products. This work was supported by the US Department of Energy Basic Energy Sciences' Chemical Sciences, Geosciences & Biosciences Division. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy.« less

Effects of pH on the formation of 4(5)-Methylimidazole in glucose/ammonium sulfate and glucose/ammonium sulfite caramel model reactions.

PubMed

Wu, Xinlan; Kong, Fansheng; Huang, Minghui; Yu, Shujuan

2015-10-01

The objective of the present study was to detail the change of 4(5)-Methylimidazole (4-MI) in sulfite and sulfate reactions with different initial pH values. Glucose/ammonium sulfate and glucose/ammonium sulfite reaction systems with initial pH conditions 4.9, 5.9, 6.9, 8.0 and 8.6, were heated at 100°C for 2h, respectively. Higher concentration of methylglyoxal (MGO) and 4-MI was detected in thermal treated glucose/ammonium sulfite reaction system than that in sulfate system. The SO 3 2- reacting with MGO and other precursors of 4-MI at higher pH conditions prevented 4-MI formation. However, no inhibition of 4-MI was found at lower pH conditions due to higher reactivity of the nucleophilic NH 4 + than SO 3 2- . The browning intensity of the sulfite system changed scarcely at higher pH values, which was possibly caused by the polyreaction between SO 3 2- and carbonyl, instead of the intermolecular polymerisation of carbonyl in the advanced stage of the Maillard reaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Stochastic thermodynamics and entropy production of chemical reaction systems

NASA Astrophysics Data System (ADS)

Tomé, Tânia; de Oliveira, Mário J.

2018-06-01

We investigate the nonequilibrium stationary states of systems consisting of chemical reactions among molecules of several chemical species. To this end, we introduce and develop a stochastic formulation of nonequilibrium thermodynamics of chemical reaction systems based on a master equation defined on the space of microscopic chemical states and on appropriate definitions of entropy and entropy production. The system is in contact with a heat reservoir and is placed out of equilibrium by the contact with particle reservoirs. In our approach, the fluxes of various types, such as the heat and particle fluxes, play a fundamental role in characterizing the nonequilibrium chemical state. We show that the rate of entropy production in the stationary nonequilibrium state is a bilinear form in the affinities and the fluxes of reaction, which are expressed in terms of rate constants and transition rates, respectively. We also show how the description in terms of microscopic states can be reduced to a description in terms of the numbers of particles of each species, from which follows the chemical master equation. As an example, we calculate the rate of entropy production of the first and second Schlögl reaction models.

Detailed mechanism of the NO + CO reaction on Rh(1 0 0) and Rh(1 1 1): A first-principles study

NASA Astrophysics Data System (ADS)

Tan, Lu; Huang, Liangliang; Liu, Yingchun; Wang, Qi

2018-06-01

Through DFT calculations, the detailed mechanism of the catalytic NO + CO reaction, a prototypical system with great practical applications especially in the automobile-exhaust aftertreatment, was determined on Rh(1 0 0) and Rh(1 1 1). The elementary steps and their energy evolution were revealed. These steps include NO dissociation, N2 formation through N recombination, CO2 formation, and N2O formation, transformation, and dissociation. The reaction steps of NO2 formation and direct reaction between NO and CO were also studied, and were verified to be relatively insignificant in this reaction system. Results shed light on the atomic-level origin why Rh(1 0 0) is more active for this reaction system and more selective for the production of N2 versus N2O compared with Rh(1 1 1). Meanwhile, the preference between the two routes for N2 production, i.e., N atoms recombination and N2O as intermediate, was found to be dependent on the distribution of surface species and the interaction among them intricately. This work provides a basis for further kinetic modeling to investigate the catalytic properties on a realistic scale.

Using Multiscale Modeling to Study Coupled Flow, Transport, Reaction and Biofilm Growth Processes in Porous Media

NASA Astrophysics Data System (ADS)

Valocchi, A. J.; Laleian, A.; Werth, C. J.

2017-12-01

Perturbation of natural subsurface systems by fluid inputs may induce geochemical or microbiological reactions that change porosity and permeability, leading to complex coupled feedbacks between reaction and transport processes. Some examples are precipitation/dissolution processes associated with carbon capture and storage and biofilm growth associated with contaminant transport and remediation. We study biofilm growth due to mixing controlled reaction of multiple substrates. As biofilms grow, pore clogging occurs which alters pore-scale flow paths thus changing the mixing and reaction. These interactions are challenging to quantify using conventional continuum-scale porosity-permeability relations. Pore-scale models can accurately resolve coupled reaction, biofilm growth and transport processes, but modeling at this scale is not feasible for practical applications. There are two approaches to address this challenge. Results from pore-scale models in generic pore structures can be used to develop empirical relations between porosity and continuum-scale parameters, such as permeability and dispersion coefficients. The other approach is to develop a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled by a suitable method that ensures continuity of flux across the interface. Thus, regions of high reactivity where flow alteration occurs are resolved at the pore scale for accuracy while regions of low reactivity are resolved at the continuum scale for efficiency. This approach thus avoids the need for empirical upscaling relations in regions with strong feedbacks between reaction and porosity change. We explore and compare these approaches for several two-dimensional cases.

Experimental study of 38Ar+α reaction cross sections relevant to the 41Ca abundance in the solar system

NASA Astrophysics Data System (ADS)

Talwar, R.; Bojazi, M. J.; Mohr, P.; Auranen, K.; Avila, M. L.; Ayangeakaa, A. D.; Harker, J.; Hoffman, C. R.; Jiang, C. L.; Kuvin, S. A.; Meyer, B. S.; Rehm, K. E.; Santiago-Gonzalez, D.; Sethi, J.; Ugalde, C.; Winkelbauer, J. R.

2018-05-01

In massive stars, the 41Ca(n ,α )38Ar and 41K(p ,α )38Ar reactions have been identified as the key reactions governing the abundance of 41Ca, which is considered as a potential chronometer for solar system formation. So far, due to experimental limitations, the 41Ca(n ,α )38Ar reaction rate is solely based on statistical model calculations. In the present study, we have measured the time-inverse 38Ar(α ,n )41Ca and 38Ar(α ,p )41K reactions using an active target detector. The reactions were studied in inverse kinematics using a 133-MeV 38Ar beam and 4He as the active-gas target. Both excitation functions were measured simultaneously in the energy range of 6.8 ≤Ec .m .≤9.3 MeV. Using detailed balance the 41Ca(n ,α )38Ar and 41K(p ,α )38Ar reaction rates were determined, which suggested a 20% increase in the 41Ca yield from massive stars.

Lagrangian descriptors of driven chemical reaction manifolds.

PubMed

Craven, Galen T; Junginger, Andrej; Hernandez, Rigoberto

2017-08-01

The persistence of a transition state structure in systems driven by time-dependent environments allows the application of modern reaction rate theories to solution-phase and nonequilibrium chemical reactions. However, identifying this structure is problematic in driven systems and has been limited by theories built on series expansion about a saddle point. Recently, it has been shown that to obtain formally exact rates for reactions in thermal environments, a transition state trajectory must be constructed. Here, using optimized Lagrangian descriptors [G. T. Craven and R. Hernandez, Phys. Rev. Lett. 115, 148301 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.148301], we obtain this so-called distinguished trajectory and the associated moving reaction manifolds on model energy surfaces subject to various driving and dissipative conditions. In particular, we demonstrate that this is exact for harmonic barriers in one dimension and this verification gives impetus to the application of Lagrangian descriptor-based methods in diverse classes of chemical reactions. The development of these objects is paramount in the theory of reaction dynamics as the transition state structure and its underlying network of manifolds directly dictate reactivity and selectivity.

Simulating Salt Movement and Transformation using a Coupled Reactive Transport Model in Variably-Saturated Groundwater Systems

NASA Astrophysics Data System (ADS)

Tavakoli Kivi, S.; Bailey, R. T.; Gates, T.

2016-12-01

Salinization is one of the major concerns in irrigated agricultural landscapes. Increasing salinity concentrations are due principally to evaporative concentration; dissolution of salts from weathered minerals and bedrock; and a high water table that results from excessive irrigation, canal seepage, and a lack of efficient drainage systems; leading to decreasing crop yield. High groundwater salinity loading to nearby river systems also impacts downstream areas, with saline river water diverted for application on irrigated fields. In this study, a solute transport model coupled with equilibrium chemistry reactions has been developed to simulate transport of individual salt ions in regional-scale aquifer systems and thereby investigate strategies for salinity remediation. The physically-based numerical model is based on the UZF-RT3D variably-saturated, multi-species groundwater reactive transport modeling code, and accounts for advection, dispersion, carbon and nitrogen cycling, oxidation-reduction reactions, and salt ion equilibrium chemistry reactions such as complexation, ion exchange, and precipitation/dissolution. Each major salt ion (sulfate, chloride, bicarbonate, calcium, sodium, magnesium, potassium) is included. The model has been tested against measured soil salinity at a small scale (soil profile) and against soil salinity, groundwater salinity, and groundwater salinity loading to surface water at the regional scale (500 km2) in the Lower Arkansas River Valley (LARV) in southeastern Colorado, an area acutely affected by salinization for many decades and greatly influenced by gypsum deposits. Preliminary results of using the model in scenario analysis suggest that increasing irrigation efficiency, sealing earthen canals, and rotational fallowing of land can decrease the groundwater salt load to the Arkansas River by 50 to 70% and substantially lower soil salinity in the root zone.

Benchmarking density functional tight binding models for barrier heights and reaction energetics of organic molecules.

PubMed

Gruden, Maja; Andjeklović, Ljubica; Jissy, Akkarapattiakal Kuriappan; Stepanović, Stepan; Zlatar, Matija; Cui, Qiang; Elstner, Marcus

2017-09-30

Density Functional Tight Binding (DFTB) models are two to three orders of magnitude faster than ab initio and Density Functional Theory (DFT) methods and therefore are particularly attractive in applications to large molecules and condensed phase systems. To establish the applicability of DFTB models to general chemical reactions, we conduct benchmark calculations for barrier heights and reaction energetics of organic molecules using existing databases and several new ones compiled in this study. Structures for the transition states and stable species have been fully optimized at the DFTB level, making it possible to characterize the reliability of DFTB models in a more thorough fashion compared to conducting single point energy calculations as done in previous benchmark studies. The encouraging results for the diverse sets of reactions studied here suggest that DFTB models, especially the most recent third-order version (DFTB3/3OB augmented with dispersion correction), in most cases provide satisfactory description of organic chemical reactions with accuracy almost comparable to popular DFT methods with large basis sets, although larger errors are also seen for certain cases. Therefore, DFTB models can be effective for mechanistic analysis (e.g., transition state search) of large (bio)molecules, especially when coupled with single point energy calculations at higher levels of theory. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Application of Bogolyubov's theory of weakly nonideal Bose gases to the A+A, A+B, B+B reaction-diffusion system

NASA Astrophysics Data System (ADS)

Konkoli, Zoran

2004-01-01

Theoretical methods for dealing with diffusion-controlled reactions inevitably rely on some kind of approximation, and to find the one that works on a particular problem is not always easy. Here the approximation used by Bogolyubov to study a weakly nonideal Bose gas, referred to as the weakly nonideal Bose gas approximation (WBGA), is applied in the analysis of three reaction-diffusion models: (i) A+A→Ø, (ii) A+B→Ø, and (iii) A+A,B+B,A+B→Ø (the ABBA model). Two types of WBGA are considered, the simpler WBGA-I and the more complicated WBGA-II. All models are defined on the lattice to facilitate comparison with computer experiment (simulation). It is found that the WBGA describes the A+B reaction well, it reproduces the correct d/4 density decay exponent. However, it fails in the case of the A+A reaction and the ABBA model. (To cure the deficiency of WBGA in dealing with the A+A model, a hybrid of the WBGA and Kirkwood superposition approximations is suggested.) It is shown that the WBGA-I is identical to the dressed-tree calculation suggested by Lee [J. Phys. A 27, 2633 (1994)], and that the dressed-tree calculation does not lead to the d/2 density decay exponent when applied to the A+A reaction, as normally believed, but it predicts the d/4 decay exponent. Last, the usage of the small n0 approximation suggested by Mattis and Glasser [Rev. Mod. Phys. 70, 979 (1998)] is questioned if used beyond the A+B reaction-diffusion model.