Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning

• Published in: npj computational materials Vol. 6; no. 1
• Main Authors: Borlido, Pedro, Schmidt, Jonathan, Huran, Ahmad W., Tran, Fabien, Marques, Miguel A. L., Botti, Silvana
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.07.2020; Nature Publishing Group
• Subjects: 639/301/1034/1038; 639/766/119/995; Approximation; Benchmarks; Characterization and Evaluation of Materials; Chemistry and Materials Science; Computational Intelligence; Computer applications; Density functional theory; Energy gap; Exchanging; Learning algorithms; Machine learning; Materials information; Materials Science; Mathematical and Computational Engineering; Mathematical and Computational Physics; Mathematical Modeling and Industrial Mathematics; Parameter identification; Theoretical

We conducted a large-scale density-functional theory study on the influence of the exchange-correlation functional in the calculation of electronic band gaps of solids. First, we use the large materials data set that we have recently proposed to benchmark 21 different functionals, with a particular...