Machine learning accelerates discovery of solar-cell perovsk

An EPFL research project has developed a method based on machine learning to quickly and accurately search large databases, leading to the discovery of 14 new materials for solar cells.

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Shanghai , China , United States , American , Haiyuan Wang , Alfredo Pasquarello , Journal Of The American Chemical Society , American Chemical , Density Functional Theory , High Quality Data Enabling Universality , Band Gap Descriptor , Photovoltaic Perovskites , American Chemical Society ,