Design and prediction of high optical density photovoltaic polymers using machine learning-DFT studies
This research provides a machine learning (ML) method to predict the optical density of photovoltaic (PV) polymers. The results show that extra gradient boosting regressor and random forest regressor are the best-performing models among all the tested ML models, whose good R-squared (R...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-07-01
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| Series: | Open Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/phys-2025-0172 |
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