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Accurate and efficient molecular dynamics based on machine learning and non von Neumann architecture

Abstract Force field-based classical molecular dynamics (CMD) is efficient but its potential energy surface (PES) prediction error can be very large. Density functional theory (DFT)-based ab-initio molecular dynamics (AIMD) is accurate but computational cost limits its applications to small systems....

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Detalhes bibliográficos
Main Authors: Pinghui Mo, Chang Li, Dan Zhao, Yujia Zhang, Mengchao Shi, Junhua Li, Jie Liu
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Portfolio 2022-05-01
Colecção:npj Computational Materials
Acesso em linha:https://doi.org/10.1038/s41524-022-00773-z
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