Article

A Transferable Active-Learning Strategy for Reactive Molecular Force Fields

2021-04-20

Abstract excerpt

Predictive simulations of dynamic processes in molecular systems require fast, accurate and reactive interatomic potentials. Machine learning offers a promising approach to construct force-field models for large-scale molecular simulation by fitting to high-level quantum-mechanical data. However, machine-learned force fields generally require considerable human intervention and data volume. Here we show that, by l...

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Literature Corpus work: 99db629d-675e-5056-b4b7-d35b3436ecdf
DOI: 10.26434/chemrxiv.13856123.v2

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