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

Chang, Alexander M.; Freeze, Jessica G.; Batista, Victor S.

doi:10.1039/c9sc02339a

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

Journal Article · 12 June 2019 · Chemical Science

DOI: https://doi.org/10.1039/c9sc02339a · OSTI ID:1577578

^[1];

^[1]; Batista, Victor S. ^[1]

Yale Univ., New Haven, CT (United States)

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($$\equiv$$]CArR)L₄X. Using a reference molecular framework and the meta- and para-substituent Hammett parameters of the ligands, the models predict energies of frontier orbitals that correlate with redox potentials. The regressive models capture the multivariate character of electron-donating trends as influenced by multiple substituents even for non-aryl ligands, harnessing the breadth of Hammett parameters in a generalized model. We find a tungsten catalyst with tetramethylethylenediamine (tmeda) equatorial ligands and axial methoxyl substituents that should attract significant experimental interest since it is predicted to be highly reducing when photoactivated with visible light. The utilization of Hammett parameters in this study presents a generalizable and compact representation for exploring the effects of ligand substitutions.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

Sponsoring Organization:: USDOE Office of Science (SC); US Air Force Office of Scientific Research (AFOSR)

Grant/Contract Number:: FA9550-17-0198

OSTI ID:: 1577578

Journal Information:: Chemical Science, Vol. 10, Issue 28; ISSN 2041-6520

Publisher:: Royal Society of ChemistryCopyright Statement

Country of Publication:: United States

Language:: English

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