Design and prediction of high optical density photovoltaic polymers using machine learning-DFT studies

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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Bibliographic Details
Main Authors: Aljaafreh Mamduh J., Hassan Abrar U.
Format: Article
Language:English
Published: De Gruyter 2025-07-01
Series:Open Physics
Subjects:
polymer design
machine learning
dft
shap
transformer assisted orientation
sali
Online Access:https://doi.org/10.1515/phys-2025-0172
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