Computational Vibrational Spectroscopy.
Machine Learning
Molecular Dynamics
Quantitative Simulations
Vibrational Spectroscopy
Journal
Chimia
ISSN: 0009-4293
Titre abrégé: Chimia (Aarau)
Pays: Switzerland
ID NLM: 0373152
Informations de publication
Date de publication:
29 Jun 2022
29 Jun 2022
Historique:
received:
11
04
2022
accepted:
03
05
2022
medline:
29
6
2022
pubmed:
29
6
2022
entrez:
9
12
2023
Statut:
epublish
Résumé
Vibrational spectroscopy is a powerful technique to characterize the near-equilibrium dynamics of molecules in the gas and the condensed phase. This contribution summarizes efforts from computer-based methods to gain insight into the relationship between structure and spectroscopic response. Methods for this purpose include physics-based and machine-learned energy functions, and methods that separate sampling conformational space and determining the data for spectral analysis such as map-based techniques.
Identifiants
pubmed: 38069730
doi: 10.2533/chimia.2022.589
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
589-593Subventions
Organisme : Swiss National Science Foundation
ID : 200021-188724
Pays : Switzerland
Informations de copyright
Copyright 2022 Markus Meuwly. License: This work is licensed under a Creative Commons Attribution 4.0 International License.