npj Computational Materials (Apr 2022)

Numerical quality control for DFT-based materials databases

  • Christian Carbogno,
  • Kristian Sommer Thygesen,
  • Björn Bieniek,
  • Claudia Draxl,
  • Luca M. Ghiringhelli,
  • Andris Gulans,
  • Oliver T. Hofmann,
  • Karsten W. Jacobsen,
  • Sven Lubeck,
  • Jens Jørgen Mortensen,
  • Mikkel Strange,
  • Elisabeth Wruss,
  • Matthias Scheffler

DOI
https://doi.org/10.1038/s41524-022-00744-4
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 8

Abstract

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Abstract Electronic-structure theory is a strong pillar of materials science. Many different computer codes that employ different approaches are used by the community to solve various scientific problems. Still, the precision of different packages has only been scrutinized thoroughly not long ago, focusing on a specific task, namely selecting a popular density functional, and using unusually high, extremely precise numerical settings for investigating 71 monoatomic crystals1. Little is known, however, about method- and code-specific uncertainties that arise under numerical settings that are commonly used in practice. We shed light on this issue by investigating the deviations in total and relative energies as a function of computational parameters. Using typical settings for basis sets and k-grids, we compare results for 71 elemental1 and 63 binary solids obtained by three different electronic-structure codes that employ fundamentally different strategies. On the basis of the observed trends, we propose a simple, analytical model for the estimation of the errors associated with the basis-set incompleteness. We cross-validate this model using ternary systems obtained from the Novel Materials Discovery (NOMAD) Repository and discuss how our approach enables the comparison of the heterogeneous data present in computational materials databases.