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Fast Predictions of Liquid-Phase Acid-Catalyzed Reaction Rates Using Molecular Dynamics Simulations and Convolutional Neural Networks

By Alex Chew and others
The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the atomistic configurations of reactant-solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to... Show more
May 4, 2020
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Fast Predictions of Liquid-Phase Acid-Catalyzed Reaction Rates Using Molecular Dynamics Simulations and Convolutional Neural Networks
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