Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model.

作者: Matthew P. Kroonblawd , Fabio Pietrucci , Antonino Marco Saitta , Nir Goldman

DOI: 10.1021/ACS.JCTC.7B01266

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摘要: We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using theory (DFT) is a highly accurate approach generate surfaces reactions, but extreme computational cost often limits scales and range thermodynamic states that can feasibly be studied. In contrast, DFTB semiempirical method affords up thousandfold reduction recover DFT-level accuracy. Here, we show force-matched model aqueous glycine condensation reactions yields are consistent with experimental observations reaction energetics. Convergence analysis reveals multiple nanoseconds combined trajectory needed reach steady-fluctuating estimate condensation. Predictive accuracy force-match...

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