Machine learning-based prediction of fluorescence lifetimes of zero-dimensional antimony halides
This paper proposes an innovative machine learning-based approach for predicting fluorescence lifetimes of zero-dimensional antimony halides, which is for the purpose of establishing relationships between material structures and emission properties.
Authors
- Zihan Yang (ORCID: https://orcid.org/0000-0003-1409-4725)
- Xiangfu Wang (ORCID: https://orcid.org/0000-0003-2365-3357)
Institutions
- Nanjing University of Posts and Telecommunications (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5tc00499c
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00