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dc.contributor.authorVitale, Valerio
dc.contributor.authorPizzi, Giovanni
dc.contributor.authorMarrazzo, Antimo
dc.contributor.authorYates, Jonathan R.
dc.contributor.authorMarzari, Nicola
dc.contributor.authorMostofi, Arash A.
dc.date.accessioned2021-02-12T17:31:08Z
dc.date.available2021-02-12T17:31:08Z
dc.date.issued2020-06-01
dc.date.submitted2019-08-30
dc.identifier.others41524-020-0312-y
dc.identifier.other312
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/317572
dc.descriptionFunder: European Union's Horizon 2020 research and innovation program (project E-CAM). Grant agreement no. 676531
dc.descriptionFunder: NCCR MARVEL of the Swiss National Science Foundation and the European Union’s Centre of Excellence MaX “Materials design at the Exascale”. Grant no. 824143
dc.description.abstractAbstract: Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high-throughput (HT) computational materials design is an emergent field that promises to accelerate reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space. We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations. Finally, we provide a downloadable virtual machine that can be used to reproduce the results of this paper, including all first-principles and atomistic simulations as well as the computational workflows.
dc.languageen
dc.publisherNature Publishing Group UK
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectArticle
dc.subject/639/301/1034/1037
dc.subject/639/301/119
dc.subjectarticle
dc.titleAutomated high-throughput Wannierisation
dc.typeArticle
dc.date.updated2021-02-12T17:31:07Z
prism.issueIdentifier1
prism.publicationNamenpj Computational Materials
prism.volume6
dc.identifier.doi10.17863/CAM.64685
dcterms.dateAccepted2020-03-18
rioxxterms.versionofrecord10.1038/s41524-020-0312-y
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidVitale, Valerio [0000-0003-2714-8585]
dc.contributor.orcidPizzi, Giovanni [0000-0002-3583-4377]
dc.contributor.orcidMarrazzo, Antimo [0000-0003-2053-9962]
dc.contributor.orcidYates, Jonathan R. [0000-0002-1896-0101]
dc.contributor.orcidMostofi, Arash A. [0000-0002-6883-8278]
dc.identifier.eissn2057-3960
pubs.funder-project-idThomas Young Centre (London Centre for the Theory and Simulation of Materials) (TYC-101, TYC-101)


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)