Predicting band gap with neural networks
Researchers from Kyoto University developed a machine learning model to predict the band gap of novel semiconductor materials.
Using data from almost 2,000 semiconductor materials, the team tested six different neural networks. They found that the incorporation of conditional generative adversarial networks (CGAN) and message passing neural networks ...
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