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A new MaterialGo database and its comparison with other high-throughput electronic structure databases for their predicted energy band gaps

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Abstract

Recently, many high-throughput calculation materials databases have been constructed and found wide applications. However, a database is only useful if its content is reliable and sufficiently accurate. It is thus of paramount importance to gauge the reliabilities and accuracies of these databases. Although many properties have been predicted accurately in these databases, electronic band gap is well known to be underestimated by traditional density functional theory (DFT) calculations under local density approximation (LDA), which becomes a challenging problem for materials database building. Here, we introduce MaterialGo (http://www.pkusam.com/data-base.html), a new database calculating the band structures of crystals using both Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and Heyd-Scuseria-Ernzerhof (HSE) hybrid functional}. {tiComparing different PBE databases, it is found that their band gaps are consistent when no U parameter is used for transition metal d-state or heavy element f-state to correct their self-interaction error, but rather different when PBE+U are used, mostly because of the different values of U used in different database. HSE calculations under standard parameters will give larger band gaps that are closer to experiment. Based on the high-throughput HSE calculations over 10000 crystal structures, we might have a better understanding of the relationship between crystal structures and electronic structures, which will help us to further explore material genome science and engineering.

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Correspondence to Feng Pan or LinWang Wang.

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11431_2019_9514_MOESM1_ESM.doc

A new MaterialGo database and its comparison with other high-throughput electronic structure databases for their predicted energy band gaps

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Jie, J., Weng, M., Li, S. et al. A new MaterialGo database and its comparison with other high-throughput electronic structure databases for their predicted energy band gaps. Sci. China Technol. Sci. 62, 1423–1430 (2019). https://doi.org/10.1007/s11431-019-9514-5

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