Researchers at the University of California, Davis College of Engineering are using machine learning to identify new materials for high-efficiency solar cells. Using high-throughput experiments and machine learning-based algorithms, they have found it is possible to forecast the materials’ dynamic behavior with very high accuracy, without the need to perform as many experiments.

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Tropical rainforests store 25%-40% of global soil carbon, though they occupy only 7% of Earth’s land area. By functioning as a carbon sink, tropical forests prevent more severe effects from climate change.

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