An all-chemistries comprehensive verification of all-electron and pseudopotential DFT codes via universal common workflows

ORAL

Abstract

In the past decades many DFT methods and codes have been developed, but only in 2016 their precision was first systematically assessed [1] on elemental compounds. We now define a greatly expanded protocol to test precision and transferability across all chemistries. For each element (Z=1-96) we characterize 10 prototypical compounds (4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states). The first outcome is a reference dataset of 960 equations of state (EOS) cross-checked between two all-electron codes, then used to verify (and improve) ten pseudopotential methods. Such effort is achieved by deploying AiiDA common workflows that provide automatic input parameter selection, identical input/output interface across codes, and full reproducibility. We finally discuss to which extent results can be reused for different goals (e.g., formation energies), and plans to extend common workflow interfaces to more properties (bands, phonons).

*MARVEL NCCR funded by the SNSF (grant agreement ID 51NF40-182892).PRACE for awarding us access to Piz Daint at CSCS, Switzerland (proposal no. 2020225458).H2020 MaX CoE no. 824143.H2020 Intersect project through Grant No. 814487.

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Publication: S.P. Huber, E. Bosoni, M. Bercx, et al., Common workflows for computing material properties using different quantum engines. npj Comput Mater 7, 136 (2021). https://doi.org/10.1038/s41524-021-00594-6

Presenters

  • Marnik Bercx

    • THEOS, EPFL; NCCR MARVEL

Authors

  • Marnik Bercx

    • THEOS, EPFL; NCCR MARVEL

  • Emanuele Bosoni

    • ICMAB-CSIC, Spain

  • Peter Blaha

    • Vienna Univ of Technology

  • Jens Bröder

    • Forschungszentrum Jülich, Germany

  • Martin Callsen

    • Institute of Atomic and Molecular Sciences, Academia Sinica

  • Stefaan Cottenier

    • Ghent University, Belgium

  • Augustin Degomme

    • Univ. Grenoble-Alpes, CEA, France

  • Espen Flage-Larsen

    • SINTEF Industry, Norway

  • Marco Fornari

    • Central Michigan University

  • Alberto Garcia

    • ICMAB-CSIC, Spain

  • Bonan Zhu

    • University College London, United Kingdom
    • University College London

  • Gian-Marco Rignanese

    • Universite catholique de Louvain

  • Georg Kastlunger

    • Technical University of Denmark

  • Chris J Pickard

    • Department of Materials Science & Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, United Kingdom
    • University of Cambridge, United Kingdom

  • Matthias Krack

    • Paul Scherrer Institut, Switzerland

  • Daniel Wortmann

    • Forschungszentrum Jülich, Germany
    • Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany

  • Tiziano M Müller

    • HPE HPC/AI Research Lab, Switzerland

  • Thomas D Kuhne

    • University of Paderborn, Germany

  • Aliaksandr V Yakutovich

    • Empa, Switzerland

  • Oleg Rubel

    • McMaster University, Canada

  • Michael Wolloch

    • University of Vienna, Austria

  • Sebastiaan P Huber

    • Microsoft Azure Quantum

  • Nicola Marzari

    • Ecole Polytechnique Federale de Lausanne
    • THEOS, EPFL; NCCR MARVEL; LMS, Paul Scherrer Institute
    • THEOS, EPFL; NCCR MARVEL; LMS, Paul Scherrer Institut
    • THEOS, EPFL; NCCR, MARVEL; LMS, Paul Scherrer Institut
    • THEOS, EPFL
    • THEOS, EPFL; NCCR MARVEL; LSM Paul Scherrer Insitut
    • THEOS, EPFL; LMS, Paul Scherrer Institut; NCCR MARVEL

  • Giovanni Pizzi

    • THEOS, EPFL; NCCR MARVEL; LMS, Paul Scherrer Institute
    • THEOS, EPFL; NCCR, MARVEL; LMS, Paul Scherrer Institut
    • THEOS, EPFL; NCCR MARVEL; LMS, Paul Scherrer Institut