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dc.contributor.authorFujikake, Soen
dc.contributor.authorDeringer, Volkeren
dc.contributor.authorLee, Taehoonen
dc.contributor.authorKrynski, Marcinen
dc.contributor.authorElliott, Stephenen
dc.contributor.authorCsányi, Gáboren
dc.date.accessioned2018-02-27T17:23:19Z
dc.date.available2018-02-27T17:23:19Z
dc.date.issued2018-06en
dc.identifier.issn0021-9606
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/273598
dc.description.abstractWe demonstrate how machine-learning based interatomic potentials can be used to model guest atoms in host structures. Specifically, we generate Gaussian approximation potential (GAP) models for the interaction of lithium atoms with graphene, graphite, and disordered carbon nanostructures, based on reference density functional theory data. Rather than treating the full Li-C system, we demonstrate how the energy and force differences arising from Li intercalation can be modeled and then added to a (prexisting and unmodified) GAP model of pure elemental carbon. Furthermore, we show the benefit of using an explicit pair potential fit to capture "effective" Li-Li interactions and to improve the performance of the GAP model. This provides proof-of-concept for modeling guest atoms in host frameworks with machine-learning based potentials and in the longer run is promising for carrying out detailed atomistic studies of battery materials.
dc.format.mediumPrinten
dc.languageengen
dc.titleGaussian approximation potential modeling of lithium intercalation in carbon nanostructures.en
dc.typeArticle
prism.issueIdentifier24en
prism.publicationDate2018en
prism.publicationNameThe Journal of chemical physicsen
prism.startingPage241714
prism.volume148en
dc.identifier.doi10.17863/CAM.20669
dcterms.dateAccepted2018-02-17en
rioxxterms.versionofrecord10.1063/1.5016317en
rioxxterms.versionAM*
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-06en
dc.contributor.orcidDeringer, Volker [0000-0001-6873-0278]
dc.contributor.orcidKrynski, Marcin [0000-0003-1593-0369]
dc.identifier.eissn1089-7690
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idEPSRC (EP/K014560/1)
pubs.funder-project-idIsaac Newton Trust (1624(n))
pubs.funder-project-idEPSRC (EP/P022596/1)
pubs.funder-project-idIsaac Newton Trust (17.08(c))
pubs.funder-project-idLeverhulme Trust (ECF-2017-278)
datacite.issupplementedby.urlhttps://doi.org/10.17863/CAM.54720


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