Overreact, an in silico lab: Automative quantum chemical microkinetic simulations for complex chemical reactions
Abstract
Today's demand for precisely predicting chemical reactions from first principles requires research to go beyond Gibbs' free energy diagrams and consider other effects such as concentrations and quantum tunneling. The present work introduces overreact, a novel Python package for propagating chemical reactions over time using data from computational chemistry only. The overreact code infers all differential equations and parameters from a simple input that consists of a set of chemical equations and quantum chemistry package outputs for each chemical species. We evaluate some applications from the literature: gas‐phase eclipsed‐staggered isomerization of ethane, gas‐phase umbrella inversion of ammonia, gas‐phase degradation of methane by chlorine radical, and three solvation‐phase reactions. Furthermore, we comment on a simple solvation‐phase acid–base equilibrium. We show how it is possible to achieve reaction profiles and information matching experiments.
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Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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