Renewed Energy Frontier Research to water crises.
And it could help with decarbonizing the grid and provide many new jobs.”
Chan and Mannodi-Kanakkithodi are betting that machine learning will play a vital role in realizing that lofty goal. A form of artificial intelligence , machine learning uses a combination of large data sets and algorithms to imitate the way that humans learn. It learns from training with sample data and past experience to make ever better predictions.scientists discovered new materials by the laborious process of trial and error with many different candidates until one works.
At present, the primary absorber in solar cells is either silicon or cadmium telluride. Such cells are now commonplace. But they remain fairly expensive and energy intensive to manufacture. The team used their machine learning method to assess the solar energy properties of a class of material called halide perovskites. Over the past decade, many researchers have been studying perovskites because of their remarkable efficiency in converting sunlight to electricity. They also offer the prospect of much lower cost and energy input for material preparation and cell building.
The team trained their method with data for a few hundred halide perovskite compositions, then applied it to over 18,000 compositions as a test case. The method evaluated these compositions for key properties such as stability, ability to absorb sunlight, structure that does not break easily due to defects, and more. The computations agreed well with relevant data in the scientific literature. Also, the findings whittled down the number of compositions worthy of further study to about 400.
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