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dc.contributor.authorLevämäki, H.
dc.contributor.authorKuisma, Mikael
dc.contributor.authorKokko, K.
dc.date.accessioned2019-03-05T12:00:21Z
dc.date.available2020-02-02T22:35:27Z
dc.date.issued2019
dc.identifier.citationLevämäki, H., Kuisma, M., & Kokko, K. (2019). Space partitioning of exchange-correlation functionals with the projector augmented-wave method. <i>Journal of Chemical Physics</i>, <i>150</i>(5), Article 054101. <a href="https://doi.org/10.1063/1.5078432" target="_blank">https://doi.org/10.1063/1.5078432</a>
dc.identifier.otherCONVID_28904607
dc.identifier.otherTUTKAID_80560
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/63031
dc.description.abstractWe implement a Becke fuzzy cells type space partitioning scheme for the purposes of exchange-correlation within the GPAW projector augmented-wave method based density functional theory code. Space partitioning is needed in the situation where one needs to treat different parts of a combined system with different exchange-correlation functionals. For example, bulk and surface regions of a system could be treated with functionals that are specifically designed to capture the distinct physics of those regions. Here, we use the space partitioning scheme to implement the quasi-nonuniform exchange-correlation scheme, which is a useful practical approach for calculating metallic alloys on the generalized gradient approximation level. We also confirm the correctness of our implementation with a set of test calculations.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherAIP Publishing LLC
dc.relation.ispartofseriesJournal of Chemical Physics
dc.rightsIn Copyright
dc.subject.otherVoronoi diagrams
dc.subject.othergeneralized gradient approximations
dc.subject.otherprojector augmented wave method
dc.subject.otherexchange correlation functionals
dc.subject.otherDensity functional theory
dc.subject.otherPartitions (building)
dc.titleSpace partitioning of exchange-correlation functionals with the projector augmented-wave method
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201902261652
dc.contributor.laitosKemian laitosfi
dc.contributor.laitosDepartment of Chemistryen
dc.contributor.oppiaineFysikaalinen kemiafi
dc.contributor.oppiaineNanoscience Centerfi
dc.contributor.oppiainePhysical Chemistryen
dc.contributor.oppiaineNanoscience Centeren
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2019-02-26T10:15:12Z
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0021-9606
dc.relation.numberinseries5
dc.relation.volume150
dc.type.versionpublishedVersion
dc.rights.copyright© 2019 Authors.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber295602
dc.subject.ysotiheysfunktionaaliteoria
dc.subject.ysoapproksimointi
dc.subject.ysometalliseokset
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p28852
jyx.subject.urihttp://www.yso.fi/onto/yso/p4982
jyx.subject.urihttp://www.yso.fi/onto/yso/p4519
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1063/1.5078432
dc.relation.funderSuomen Akatemiafi
dc.relation.funderAcademy of Finlanden
jyx.fundingprogramTutkijatohtori, SAfi
jyx.fundingprogramPostdoctoral Researcher, AoFen
jyx.fundinginformationM.K. acknowledges the Academy of Finland (Grant No. 295602). The computer resources of the Finnish IT Center for Science (CSC) and the Finnish Grid and Cloud Infrastructure (FGCI) project (Finland), and the Swedish National Infrastructure for Computing (SNIC) at the High Performance Computing Center North (HPC2N) are acknowledged.
dc.type.okmA1


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