Advancing nonadiabatic molecular dynamics simulations in solids with E(3) equivariant deep neural hamiltonians
Abstract Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool for investigating excited-state dynamics in solids. In this work, we propose a general framework, N2AMD (Neural-Network Non-Adiabatic Molecular Dynamics), which employs an E(3)-equivariant deep neural Hami...
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| Principais autores: | , , , , , , , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Nature Portfolio
2025-02-01
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| Serier: | Nature Communications |
| Online adgang: | https://doi.org/10.1038/s41467-025-57328-1 |
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