Data-driven discovery of multiscale chemical reactions governed by the law of mass action
Journal of Computational Physics(2022)
Abstract
•We propose a data-driven method to discover multiscale chemical reactions governed by the law of mass action.•We propose a partial-parameters-freezing (PPF) technique to learn the multiscale reactions.•We use a single matrix to represent the stoichiometric coefficients for a system without catalysis reactions.
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Key words
Chemical reactions,Multiscale,Machine learning,Nonlinear regression,Ordinary differential equations
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