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Hammett neural networks: prediction of frontier orbital energies of tungsten–benzylidyne photoredox complexes

The successful application of Hammett parameters as input features for regressive machine learning models is demonstrated and applied to predict energies of frontier orbitals of highly reducing tungsten–benzylidyne complexes of the form W([triple bond, length as m-dash]CArR)L(4)X. Using a reference...

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Detalles Bibliográficos
Autores principales: Chang, Alexander M., Freeze, Jessica G., Batista, Victor S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal Society of Chemistry 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6657405/
https://www.ncbi.nlm.nih.gov/pubmed/31391907
http://dx.doi.org/10.1039/c9sc02339a