qsGW quasiparticle and GW-BSE excitation energies of 133,885 molecules
Abstract Machine learning applications in the chemical sciences, especially when based on neural networks, critically depend on the availability of large quantities of high-quality data. As they provide excellent accuracy for both charged and neutral excitations, a large dataset containing quasipart...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Portfolio
2026-03-01
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| Col·lecció: | Scientific Data |
| Accés en línia: | https://doi.org/10.1038/s41597-026-07018-4 |
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