Physically inspired deep learning of molecular excitations and photoemission spectra-Reference-Cited by-同舟云学术

Physically inspired deep learning of molecular excitations and photoemission spectra

Published:2021 Issue:32 Volume:12 Page:10755-10764
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Westermayr Julia¹^ORCID,Maurer Reinhard J.¹^ORCID

Affiliation:

1. Department of Chemistry, University of Warwick, Gibbet Hill Road, Coventry, CV4 7AL, UK

Abstract

A physically-inspired machine learning model for orbital energies is developed that can be augmented with delta learning to obtain photoemission spectra, ionization potentials, and electron affinities with experimental accuracy.

Funder

Engineering and Physical Sciences Research Council

UK Research and Innovation

Austrian Science Fund

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/SC/D1SC01542G

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