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A machine learning correction for DFT non-covalent interactions based on the S22, S66 and X40 benchmark databases
BACKGROUND: Non-covalent interactions (NCIs) play critical roles in supramolecular chemistries; however, they are difficult to measure. Currently, reliable computational methods are being pursued to meet this challenge, but the accuracy of calculations based on low levels of theory is not satisfacto...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855356/ https://www.ncbi.nlm.nih.gov/pubmed/27148408 http://dx.doi.org/10.1186/s13321-016-0133-7 |