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The authors computed bandgaps and formation energy values of more than 1100 crystalline materials using Density Functional Theory (DFT) with HSE and PBE approximations of the pseudopotentials. They analyzed accuracies of HSE and PBE approximations among different classes of materials. They also built a multi-fidelity machine learning model to predict the bandgap at HSE accuracy when a material's PBE bandgap is known. The new high-throughput DFT (HSE, PBE) data of more than 1100 materials and the predicted HSE bandgap data of more than 21,000 materials are available publicly via a dedicated web app.
Liu et al. (Tue,) studied this question.
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