Atomic orbits in molecules and materials for improving machine learning force fields

The accurate representation of atoms within their environment forms the backbone of any reliable machine learning force field (MLFF). While modern MLFFs treat atoms of the same type as indistinguishable, their identities can be further resolved by accounting for the composition of their chemical env...

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Podrobná bibliografie

Hlavní autoři:	Anton Charkin-Gorbulin, Artem Kokorin, Huziel E Sauceda, Stefan Chmiela, Claudio Quarti, David Beljonne, Alexandre Tkatchenko, Igor Poltavsky
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IOP Publishing 2025-01-01
Edice:	Machine Learning: Science and Technology
Témata:	force fields machine learning atomistic simulations molecular dynamics symmetry search perovskites
On-line přístup:	https://doi.org/10.1088/2632-2153/adea0b
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!