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This document reviews the application of machine learning (ML) in the development of perovskite solar cells (PSCs) and their component materials, highlighting the advantages of ML over traditional experimental and computational methods. It discusses key technologies, data sources, and challenges faced in integrating ML into PSC research, emphasizing the importance of high-quality data for effective ML model training. The review also outlines future prospects for ML applications in enhancing the design and e

Author

bekimizoha93671

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EN