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    Machine Learning Predicts How to Develop High-Performing Solar Cells

    Article obtained from Photonics RSS Feed.

    To determine the best way to optimize the materials used to build perovskite solar cells, a research team at the University of Central Florida turned to machine learning techniques. The researchers reviewed more than 2000 peer-reviewed publications about perovskites and collected more than 300 data points and then fed these into an artificial intelligence system developed by the team.

    The system analyzed the information and predicted which recipe for spray-on perovskite solar technology would work best. The machine learning approach considered how to optimize material composition and predicted the best design strategies and potential performance of perovskite solar cells. The machine learning predictions corresponded with the…

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    Dec, 17 2019 |

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