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- W3105152113 abstract "Abstract Semiconducting inorganic materials with band gaps ranging between 0 and 5 eV constitute major components in electronic, optoelectronic and photovoltaic devices. Since the band gap is a primary material property that affects the device performance, large band-gap databases are useful in selecting optimal materials in each application. While there exist several band-gap databases that are theoretically compiled by density-functional-theory calculations, they suffer from computational limitations such as band-gap underestimation and metastable magnetism. In this data descriptor, we present a computational database of band gaps for 10,481 materials compiled by applying a hybrid functional and considering the stable magnetic ordering. For benchmark materials, the root-mean-square error in reference to experimental data is 0.36 eV, significantly smaller than 0.75–1.05 eV in the existing databases. Furthermore, we identify many small-gap materials that are misclassified as metals in other databases. By providing accurate band gaps, the present database will be useful in screening materials in diverse applications." @default.
- W3105152113 created "2020-11-23" @default.
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- W3105152113 date "2020-11-11" @default.
- W3105152113 modified "2023-10-14" @default.
- W3105152113 title "A band-gap database for semiconducting inorganic materials calculated with hybrid functional" @default.
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- W3105152113 doi "https://doi.org/10.1038/s41597-020-00723-8" @default.
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