Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential

Hydrogen has multiple molecular phases which are challenging to explore computationally. The authors develop a machine-learning approach, learning from reference ab initio molecular dynamics simulations, to derive a transferable hierarchical force model that provides insight into high pressure phase...

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Autores principales: Hongxiang Zong, Heather Wiebe, Graeme J. Ackland
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/8847e5d5db8d47119e4a8c692d3ed252
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