Unlocking phonon properties of a large and diverse set of cubic crystals by indirect bottom-up machine learning approach
Abstract Although first principles based anharmonic lattice dynamics is one of the most common methods to obtain phonon properties, such method is impractical for high-throughput search of target thermal materials. We develop an elemental spatial density neural network force field as a bottom-up app...
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| Autors principals: | , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Portfolio
2023-08-01
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| Col·lecció: | Communications Materials |
| Accés en línia: | https://doi.org/10.1038/s43246-023-00390-3 |
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