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.
journal_name
Sci Datajournal_title
Scientific dataauthors
Kim S,Lee M,Hong C,Yoon Y,An H,Lee D,Jeong W,Yoo D,Kang Y,Youn Y,Han Sdoi
10.1038/s41597-020-00723-8subject
Has Abstractpub_date
2020-11-11 00:00:00pages
387issue
1issn
2052-4463pii
10.1038/s41597-020-00723-8journal_volume
7pub_type
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