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  Numerical quality control for DFT-based materials databases

Carbogno, C., Thygesen, K. S., Bieniek, B., Draxl, C., Ghiringhelli, L. M., Gulans, A., et al. (2022). Numerical quality control for DFT-based materials databases. npj Computational Materials, 8: 69. doi:10.1038/s41524-022-00744-4.

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 Creators:
Carbogno, Christian1, Author              
Thygesen, Kristian Sommer2, Author
Bieniek, Björn1, Author              
Draxl, Claudia1, 3, Author              
Ghiringhelli, Luca M.1, Author              
Gulans, Andris3, Author
Hofmann, Oliver T.4, Author
Jacobsen, Karsten W.2, Author
Lubeck, Sven3, Author
Mortensen, Jens Jørgen2, Author
Strange, Mikkel2, Author
Wruss, Elisabeth4, Author
Scheffler, Matthias, Author              
Affiliations:
1NOMAD, Fritz Haber Institute, Max Planck Society, ou_3253022              
2Center for Atomic-scale Materials Design (CAMD), Department of Physics, Technical University of Denmark, Fysikvej 1 2800 Kgs. Lyngby, Denmark, ou_persistent22              
3Physics Department and IRIS Adlershof, Humboldt-Universität zu Berlin, Zum Großen Windkanal 6, D-12489 Berlin, Germany, ou_persistent22              
4Institute of Solid State Physics, Graz University of Technology, NAWI Graz, Petergasse 16, 8010 Graz, Austria, ou_persistent22              

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Free keywords: Physics, Computational Physics, physics.comp-ph, Condensed Matter, Materials Science, cond-mat.mtrl-sci
 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 crystals. 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 elemental 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.

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Language(s): eng - English
 Dates: 2020-08-242020-08-242022-03-062022-04-19
 Publication Status: Published online
 Pages: 8
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Project name : NoMaD - The Novel Materials Discovery Laboratory
Grant ID : 676580
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)
Project name : TEC1p - Big-Data Analytics for the Thermal and Electrical Conductivity of Materials from First Principles
Grant ID : 740233
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: npj Computational Materials
  Abbreviation : npj Comput. Mater.
Source Genre: Journal
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Publ. Info: London : Springer Nature
Pages: 8 Volume / Issue: 8 Sequence Number: 69 Start / End Page: - Identifier: ISSN: 2057-3960
CoNE: https://pure.mpg.de/cone/journals/resource/2057-3960