| Autor: |
Sina Stocker, Gábor Csányi, Karsten Reuter, Johannes T. Margraf |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Nature Communications, Vol 11, Iss 1, Pp 1-11 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-020-19267-x |
| Popis: |
Application of machine-learning approaches to exploring chemical reaction networks is challenging due to need of including open-shell reaction intermediates. Here the authors introduce a density functional theory database of closed and open-shell molecules for machine-learning predictions of reaction energies. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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