A machine learning approach to predict tight-binding parameters for point defects via the projected density of states
Abstract Calculating the impact of point defects on the macroscopic properties of technologically relevant semiconductors remains a considerable challenge. Semi-empirical approaches, such as the tight-binding method, are very efficient in calculating the electronic structure of large supercells cont...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-025-01634-1 |
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