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Machine learning meets mechanistic modelling for accurate prediction of experimental activation energies
Accurate prediction of chemical reactions in solution is challenging for current state-of-the-art approaches based on transition state modelling with density functional theory. Models based on machine learning have emerged as a promising alternative to address these problems, but these models curren...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society of Chemistry
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9528810/ https://www.ncbi.nlm.nih.gov/pubmed/36299676 http://dx.doi.org/10.1039/d0sc04896h |