Predicting Solar Cell Behavior With Machine Learning

Researchers at the University of California, Davis College of Engineering, have used machine learning to predict solar cell behavior and discover high-efficiency materials with fewer experiments. Hybrid perovskites have gained attention as a renewable energy source due to their organic-inorganic composition. However, identifying perovskites that are both efficient and can resist degradation from moisture, oxygen, […]

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