High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications

Broberg, Danny; Bystrom, Kyle; Srivastava, Shivani; Dahliah, Diana; Williamson, Benjamin A. D.; Weston, Leigh; Scanlon, David O.; Rignanese, Gian-Marco; Dwaraknath, Shyam; Varley, Joel; Persson, Kristin A.; Asta, Mark; Hautier, Geoffroy

doi:10.1038/s41524-023-01015-6

Title: High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications

Journal Article · 03 May 2023 · npj Computational Materials

DOI: https://doi.org/10.1038/s41524-023-01015-6 · OSTI ID:1972498

Broberg, Danny;

; Srivastava, Shivani; Dahliah, Diana; Williamson, Benjamin A. D.; Weston, Leigh;

;

; Varley, Joel;

; Asta, Mark; Hautier, Geoffroy

Abstract Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE)

Grant/Contract Number:: AC02-05CH11231; AC52-07NA27344

OSTI ID:: 1972498

Report Number(s):: LLNL--JRNL-818693; 72; PII: 1015

Journal Information:: npj Computational Materials, Journal Name: npj Computational Materials Journal Issue: 1 Vol. 9; ISSN 2057-3960

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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