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

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2021 Belgium English Publisher:Royal Society of Chemistry (RSC)Journal:Physical Chemistry Chemical Physics, volume 23, pages 19,781-19,789 (issn: 1463-9076, eissn: 1463-9084,

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Authors: Tom Vermeyen; Jure Brence; Robin Van Echelpoel; Roy Aerts; Guillaume Acke; Patrick Bultinck; Wouter Herrebout;

doi: 10.1039/d1cp02428k , 10.5281/zenodo.8142819 , 10.5281/zenodo.8142818

pmid: 34524304

handle: 10067/1802900151162165141 , 1854/LU-8722174

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

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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.

Country

Belgium

Related Organizations

University of Antwerp
Belgium
Jožef Stefan International Postgraduate School
Slovenia
Ghent University
Belgium

Keywords

INFRARED-SPECTRA, SPECTROSCOPY, IDENTIFICATION, PREDICTION, Physics, General Physics and Astronomy, SHIFTS, CLASSIFICATION, Chemistry, RAMAN, Physics and Astronomy, SYSTEMS, SIMULATION, REGRESSION, Physical and Theoretical Chemistry

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