Published May 26, 2023 | Version v1
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How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

  • 1. Institut de Ciència de Materials de Barcelona, ICMAB-CSIC, Campus UAB, 08193 Bellaterra, Spain
  • 2. Univ. Grenoble-Alpes, CEA, IRIG-MEM-L Sim, 38000 Grenoble, France
  • 3. Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
  • 4. Institute for Materials Chemistry, Technical University of Vienna, Getreidemarkt 9/165-TC, A-1060 Vienna, Austria
  • 5. Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, D-52425 Jülich, Germany
  • 6. Institute for Advanced Simulation, Materials Data Science and Informatics (IAS-9), Forschungszentrum Jülich, D-52425 Jülich, Germany
  • 7. Department of Electromechanical, Systems and Metal Engineering, Ghent University, Belgium
  • 8. Center for Molecular Modeling (CMM), Ghent University, Belgium
  • 9. Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei 10617, Taiwan
  • 10. Norwegian EuroHPC Competence Center, Sigma2 AS, Norway
  • 11. SINTEF Industry, Materials Physics, Oslo, Norway
  • 12. Department of Physics and Science of Advanced Materials Program, Central Michigan University, Mount Pleasant, Michigan 48859, USA
  • 13. Institut de la Matière Condensée et des Nanosciences (IMCN), Université catholique de Louvain, Chemin des Étoiles 8, Louvain-la-Neuve 1348, Belgium
  • 14. National Centre of Competence in Research (NCCR) Catalysis, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland
  • 15. Center for Catalysis Theory (Cattheory), Department of Physics, Technical University of Denmark (DTU), 2800 Kongens Lyngby, Denmark
  • 16. Laboratory for Materials Simulations (LMS), Paul Scherrer Institut (PSI), CH-5232 Villigen PSI, Switzerland
  • 17. University of Vienna, Faculty of Physics and Center for Computational Materials Science, Kolingasse 14-16, A-1090 Vienna, Austria
  • 18. VASP Software GmbH, Sensengasse 8, A-1090 Vienna, Austria
  • 19. Center for Advanced Systems Understanding (CASUS) and Helmholtz-Zentrum Dresden-Rossendorf, D-02826 Görlitz, Germany
  • 20. Paderborn Center for Parallel Computing (PC2) and Center for Sustainable Systems Design, University of Paderborn, D-33098 Paderborn, Germany
  • 21. OCAS NV/ArcelorMittal Global R&D Gent, Pres. J. F. Kennedylaan 3, Zelzate B-9060, Belgium
  • 22. Dynamics of Condensed Matter, Chair of Theoretical Chemistry, University of Paderborn, D-33098 Paderborn, Germany
  • 23. HPE HPC EMEA Research Lab, CH-4051 Basel, Switzerland
  • 24. Department of Materials Science & Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, United Kingdom
  • 25. Advanced Institute for Materials Research, Tohoku University 2-1-1 Katahira, Aoba, Sendai, 980-8577, Japan
  • 26. Department of Materials Science and Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8, Canada
  • 27. ePotentia, Frans van Dijckstraat 59, 2100 Deurne Antwerpen, Belgium
  • 28. Institute for Materials Research (IMO-IMOMEC), UHasselt - Hasselt University, Belgium
  • 29. Swiss Federal Laboratories for Materials Science and Technology (Empa), nanotech@surfaces laboratory, CH-8600 Dübendorf, Switzerland
  • 30. Department of Chemistry, University College London, 20 Gordon St, Bloomsbury, London WC1H 0AJ, United Kingdom
  • 31. The Faraday Institution, Didcot OX11 0RA, United Kingdom

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Description

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). This data entry contains all data to reproduce the results, as well as the resulting curated all-electron dataset and the scripts to generate the figures of the paper.

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References

Journal reference (Journal paper)
E. Bosoni et al., How to verify the precision of density-functional-theory implementations via reproducible and universal workflows, Nat. Rev. Phys. 6, 45 (2024), doi: 10.1038/s42254-023-00655-3

Website (Interactive visualization of the data generated in the paper)
E. Bosoni et al., Verification of the precision of DFT implementations via AiiDA common workflows, Materials Cloud (2023)

Materials Cloud sections using these data