Results 301 to 310 of about 617,908 (340)

IDENTIFYING CHEMICAL REACTION NETWORK MODELS

IFAC Proceedings Volumes, 2007
In this work, an automated chemical reaction network identification procedure using a genetic algorithm (GA) is introduced. The GA uses chemical species concentration data obtained from batch reactors during process experimentation to build ordinary differential equation (ODE) models that represent the chemical reactions occurring.
SC Burnham, AR Wright, Mark J. Willis
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Dynamic Modeling of Chemical Reaction Systems with Neural Networks and Hybrid Models

Chemical Engineering & Technology, 1999
A common problem in kinetic modeling of complex chemical reactions is that a rigorous description of the reaction system, e.g., based on elementary reactions, is not possible. This is because either the reaction involves too many reactions and intermediates or the reaction mechanism is not known in sufficient detail. Alternative data-driven modeling, e.
Hans-Jörg Zander, Roland Dittmeyer, Josef Wagenhuber   +2 more
openaire   +3 more sources

Inference of Chemical Reaction Networks Using Hybrid S-system Models

Chemical Product and Process Modeling, 2007
This article demonstrates, using simulations, the potential of the S-system formalism for the inference of unknown chemical reaction networks from simple experimental data, such as that typically obtained from laboratory scale reaction vessels. Virtually no prior knowledge of the products and reactants is assumed.
Simon J. Horne, Dominic P. Searson, Mark J. Willis, AR Wright   +3 more
openaire   +3 more sources

Optimization of the numerical treatment of the Darcy–Forchheimer flow of Ree–Eyring fluid with chemical reaction by using artificial neural networks

International Journal for Numerical Methods in Fluids, 2022
In this study, Darcy Forchheimer flow paradigm, which is a useful paradigm in fields such as petroleum engineering where high flow velocity effects are common, has been analyzed with artificial intelligence approach.
Anum Shafiq, A. B. Çolak, T. Sindhu
semanticscholar   +1 more source

Advancing molecular graphs with descriptors for the prediction of chemical reaction yields

Journal of Computational Chemistry, 2022
Chemical yield is the percentage of the reactants converted to the desired products. Chemists use predictive algorithms to select high‐yielding reactions and score synthesis routes, saving time and reagents.
Dzvenymyra Yarish, Sofiya Garkot, O. Grygorenko, D. Radchenko, Yurii S. Moroz, O. Gurbych   +5 more
semanticscholar   +1 more source

Cholesterol photo-oxidation: A chemical reaction network for kinetic modeling

Steroids, 2016
In this work we studied the effect of polyunsaturated fatty acids (PUFAs) methyl esters on cholesterol photo-induced oxidation. The oxidative routes were modeled with a chemical reaction network (CRN), which represents the first application of CRN to the oxidative degradation of a food-related lipid matrix.
C. Barnaba, RODRIGUEZ ESTRADA, MARIA TERESA, LERCKER, GIOVANNI, H. S. García, I. G. Medina Meza   +4 more
openaire   +3 more sources

Instability in a chemical network system as a model of reaction cascades

Zeitschrift f�r Physik B Condensed Matter, 1990
A chemical network system for use in the study of reaction cascades is described by the nonlinear rate equation\(\dot x = \varphi \left( x \right) \simeq - k_1 x - k_2 x^3 \), in which ϕ(x) is derived from the −∂G/∂x of Taylor's expansion of the order parameterx of the thermodynamic potential, Gibbs' functionG(T,P,x), at about the critical pointC(T C ...
Yoshiko Yamaguchi, Kotaro Shirane, Osamu Tanimoto   +2 more
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Machine Learning for Chemical Reactions.

Chemical Reviews, 2021
Machine learning (ML) techniques applied to chemical reactions have a long history. The present contribution discusses applications ranging from small molecule reaction dynamics to computational platforms for reaction planning. ML-based techniques can be
M. Meuwly
semanticscholar   +1 more source

Biochemical Reaction Network Modeling:  Predicting Metabolism of Organic Chemical Mixtures

Environmental Science & Technology, 2005
All organisms are exposed to multiple xenobiotics, through food, environmental contamination, and drugs. These xenobiotics often undergo biotransformation, a complex process that plays a critical role in xenobiotic elimination or bioactivation to toxic metabolites.
Raymond S. H. Yang, Brad Reisfeld, Arthur N. Mayeno   +2 more
openaire   +3 more sources