Exploring machine learning methods for absolute configuration determination with vibrational circular dichroism-Reference-Cited by-同舟云学术

Exploring machine learning methods for absolute configuration determination with vibrational circular dichroism

Published:2021 Issue:35 Volume:23 Page:19781-19789
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Vermeyen Tom¹²^ORCID,Brence Jure³⁴,Van Echelpoel Robin¹^ORCID,Aerts Roy¹^ORCID,Acke Guillaume²^ORCID,Bultinck Patrick²^ORCID,Herrebout Wouter¹^ORCID

Affiliation:

1. Department of Chemistry, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp, Belgium

2. Department of Chemistry, Ghent University, Krijgslaan 281, B-9000 Ghent, Belgium

3. Department of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia

4. Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000 Ljubljana, Slovenia

Abstract

The capabilities of machine learning models to extract the absolute configuration of a series of compounds from their vibrational circular dichroism spectra have been demonstrated. The important spectral areas are identified.

Funder

Fonds Wetenschappelijk Onderzoek

Universiteit Antwerpen

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2021/CP/D1CP02428K

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