| Autor: |
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-022-30999-w |
| Popis: |
The authors introduce a diabatic neural network to accelerate excitedstate, non-adiabatic simulations of azobenzene derivatives. The model predicts quantum yields for unseen species that are correlated with experiment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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