| Autor: |
Jonathan Vandermause, Yu Xie, Jin Soo Lim, Cameron J. Owen, Boris Kozinsky |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Nature Communications, Vol 13, Iss 1, Pp 1-12 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-022-32294-0 |
| Popis: |
Uncertainty-aware machine learning models are used to automate the training of reactive force fields. The method is used here to simulate hydrogen turnover on a platinum surface with unprecedented accuracy. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full text from SpringerLink