Fast prediction of anharmonic vibrational spectra for complex organic molecules
Interpreting Raman and IR vibrational spectra in complex organic molecules lacking symmetries poses a formidable challenge. In this study, we propose an innovative approach for simulating vibrational spectra and attributing observed peaks to molecular motions, even when highly anharmonic, without the need for computationally expensive ab initio calculations. Our approach stems from the time-dependent stochastic self-consistent harmonic approximation to capture quantum nuclear fluctuations in atom dynamics while describing interatomic interaction through state-of-the-art reactive machine-learning force fields. Finally, we employ an isotropic charge model and a bond capacitor model trained on ab initio data to predict the intensity of IR and Raman signals.
Authors
- Mattia Miotto (ORCID: https://orcid.org/0000-0002-0043-8921)
- Lorenzo Monacelli (ORCID: https://orcid.org/0000-0002-6381-3741)
Institutions
- Italian Institute of Technology (IT)
- École Polytechnique Fédérale de Lausanne (CH)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- npj Computational Materials
- Published
- 2024-10-10
- DOI
- https://doi.org/10.1038/s41524-024-01400-9
- Citations
- 8
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.94
Funders
- European Commission
- Horizon 2020 Framework Programme