Machine learning-enhanced band gaps prediction for low-symmetry double and layered perovskites
Density functional theory (DFT) calculations are widely used for material property prediction, but their computational cost can hinder the discovery of novel perovskites. This work explores machine learning (ML) as a faster alternative for predicting band gaps in complex perovskites, focusing on low...
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| Published in: | Scientific reports Vol. 14; no. 1; pp. 26736 - 13 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
London
Nature Publishing Group UK
05.11.2024
Nature Publishing Group Nature Portfolio |
| Subjects: | |
| ISSN: | 2045-2322, 2045-2322 |
| Online Access: | Get full text |
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