npj Computational Materials (May 2023)

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

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

DOI
https://doi.org/10.1038/s41524-023-01015-6
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 12

Abstract

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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.