Machine learning molecular dynamics for the simulation of infrared spectra
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Artificial neural networks are combined with molecular dynamics to simulate molecular infrared spectra including anharmonicities and temperature effects.
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- Authors
- Gastegger, M., Behler, J., & Marquetand, P.
- Affiliations
- University of Vienna (AT)
- University of Göttingen (DE)
- Corresponding author
- Marquetand, Philipp
- Venue
- Chemical Science
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2017
- Volume
- 8
- Issue
- 10
- Pages
- 6924-6935
- ISSN
- 2041-6520 (ISSN-L)
- 2041-6539
- PMC
- PMC5636952
- OpenAlex
- W2614157797
- Cited by
- 556
- References
- 64
- Citations by year
- 2026: 40 · 2025: 72 · 2024: 57 · 2023: 68 · 2022: 58 · 2021: 86 · 2020: 78 · 2019: 54 · 2018: 37 · 2017: 3 · 2012: 1
- FWCI
- 20.07
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Chemical Science (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Phaidra (Universität Wien) (submittedVersion, cc-by-nc-nd)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
- arXiv (Cornell University)
- Funders
- Deutsche Forschungsgemeinschaft (Be3264/11-1)
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Spectroscopy and Quantum Chemical Studies
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Keywords
- machine learning molecular dynamics, infrared spectra simulation, artificial neural networks, anharmonicity, temperature effects, vibrational spectra
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