Engineers apply physics-informed machine learning to solar cell production

(University of Texas at Austin, Texas Advanced Computing Center) Organic photovoltaics max out at 15%-20% efficiency. Lehigh University researchers are using physics-informed machine learning to improve this efficiency. Their findings suggest a machine learning model, trained on coarse grained molecular models, can identify the optimal parameters for manufacturing in much less time than traditional methods. The researchers are currently exploring alternative materials for solar cells and will use their machine learning framework to optimize the production of such materials.
Source: EurekAlert! - Biology - Category: Biology Source Type: news