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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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Main Authors: | , , , , , , |
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Formato: | Artigo |
Idioma: | Inglês |
Publicado em: |
Nature Portfolio
2022-05-01
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Colecção: | npj Computational Materials |
Acesso em linha: | https://doi.org/10.1038/s41524-022-00773-z |
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