Aim

This model is a multif-fidelity MEGNet band gap model for 89 elements of the periodic table. It contains the band gap for most of materials with 4 fidelities ("0": PBE, "1": GLLB-SC, "2": HSE, "3": SCAN). This is essentially a retrained version of the MEGNet band gap model originally implemented in tensorflow.

Training dataset

MP-2019.4.1: Materials Project band gap as of 2019.4.1.

Training set size: 48912
Validation set size: 879

Performance metrics

MAE of band gap in eV

Training: 0.075 eV
Validation: 0.314 eV

References

Chen, C.; Zuo, Y.; Ye, W.; Li, X.; Ong, S. P. Learning Properties of Ordered and Disordered Materials from
Multi-Fidelity Data. Nature Computational Science 2021, 1, 46–53. https://doi.org/10.1038/s43588-020-00002-x.

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