Predicting Molecular Laser Properties from First-Principles Using Machine Learning-Based Nuclear Ensemble Approach Spectra
screening of candidate laser compounds but also offers deeper physical insight into the behavior of novel laser materials.
Authors
- Antonio Francés‐Monerris (ORCID: https://orcid.org/0000-0001-8232-4989)
- Daniel Roca‐Sanjuán (ORCID: https://orcid.org/0000-0001-6495-2770)
- Michael G. S. Londesborough (ORCID: https://orcid.org/0000-0002-6161-6592)
Institutions
- Consejo Superior de Investigaciones Científicas (ES)
- Universitat de València (ES)
- Czech Academy of Sciences, Institute of Inorganic Chemistry (CZ)
- Unidades Centrales Científico-Técnicas (ES)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2026-04-14
- DOI
- https://doi.org/10.1021/acs.jctc.5c01866
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministerio de Ciencia, Innovación y Universidades
- Grantová Agentura České Republiky
- Generalitat Valenciana
- European Regional Development Fund
- European Social Fund