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Data-driven design of high-performance MASnxPb1-xI3 perovskite materials by machine learning and experimental realization
- Source :
- Light: Science & Applications, Vol 11, Iss 1, Pp 1-12 (2022)
- Publication Year :
- 2022
- Publisher :
- Nature Publishing Group, 2022.
-
Abstract
- The forward-reverse framework based on machine learning for MASnxPb1-xI3 perovskite solar cells is reported. The practicability of bandgap model revealing asymmetrically-bowing shape and optimized Sn:Pb ratio are verified by experiments.
- Subjects :
- Applied optics. Photonics
TA1501-1820
Optics. Light
QC350-467
Subjects
Details
- Language :
- English
- ISSN :
- 20477538
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Light: Science & Applications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0c5c284c0f58493db12a0824022345bf
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41377-022-00924-3