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dc.contributor.authorHuber, Sebastiaan P.
dc.contributor.authorBosoni, Emanuele
dc.contributor.authorBercx, Marnik
dc.contributor.authorBröder, Jens
dc.contributor.authorDegomme, Augustin
dc.contributor.authorDikan, Vladimir
dc.contributor.authorEimre, Kristjan
dc.contributor.authorFlage-Larsen, Espen
dc.contributor.authorGarcia, Alberto
dc.contributor.authorGenovese, Luigi
dc.contributor.authorGresch, Dominik
dc.contributor.authorJohnston, Conrad
dc.contributor.authorPetretto, Guido
dc.contributor.authorPoncé, Samuel
dc.contributor.authorRignanese, Gian-Marco
dc.contributor.authorSewell, Christopher J.
dc.contributor.authorSmit, Berend
dc.contributor.authorTseplyaev, Vasily
dc.contributor.authorUhrin, Martin
dc.contributor.authorWortmann, Daniel
dc.contributor.authorYakutovich, Aliaksandr V.
dc.contributor.authorZadoks, Austin
dc.contributor.authorZarabadi-Poor, Pezhman
dc.contributor.authorZhu, Bonan
dc.contributor.authorMarzari, Nicola
dc.contributor.authorPizzi, Giovanni
dc.date.accessioned2022-08-10T08:13:48Z
dc.date.available2022-08-10T08:13:48Z
dc.date.created2021-09-03T15:49:02Z
dc.date.issued2021
dc.identifier.citationnpj Computational Materials. 2021, 7 (1), .en_US
dc.identifier.issn2057-3960
dc.identifier.urihttps://hdl.handle.net/11250/3011002
dc.description.abstractThe prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.en_US
dc.language.isoengen_US
dc.publisherNature Portfolioen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleCommon workflows for computing material properties using different quantum enginesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© The Author(s) 2021en_US
dc.source.pagenumber12en_US
dc.source.volume7en_US
dc.source.journalnpj Computational Materialsen_US
dc.source.issue1en_US
dc.identifier.doi10.1038/s41524-021-00594-6
dc.identifier.cristin1931234
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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