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dc.contributor.authorKärkkäinen, Tommi
dc.contributor.authorHäkkinen, Hannu
dc.contributor.authorMalola, Sami
dc.contributor.authorPihlajamäki, Antti
dc.coverage.temporal2022-09-01 - 2023-06-06
dc.date.accessioned2023-06-07T12:21:22Z
dc.date.available2023-06-07T12:21:22Z
dc.date.issued2023
dc.identifier.citationPihlajamäki, Antti; Kärkkäinen, Tommi; Malola, Sami; Häkkinen, Hannu. <i>Kernels and Graphs on M25 + H</i>. V. 31.3.2023. University of Jyväskylä. 10.17011/jyx/dataset/87521
dc.identifier.otherjyu-resd.183437874
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/87521
dc.description.abstractCodes related to article "Graphs and Kernelized Learning Applied to Interactions of Hydrogen with Doped Gold Nanoparticle Electrocatalysts". There are two main types of codes: codes to transform a catalytic system of protected gold nanoparticle and a single hydrogen atom into a graph-based representation, and codes to run kernel-based machine learning methods to predict interaction energies between the nanoparticle and the hydrogen atom. This is a snapshot of the code dataset that has been taken on 06.06.2023. A more detailed description of the data and the address to the GitLab repository for the latest version of the code can be found from the parent dataset of this data publication.en
dc.language.isoeng
dc.publisherUniversity of Jyväskyläen
dc.relation.ispartofPihlajamäki, Antti; Kärkkäinen, Tommi; Malola, Sami; Häkkinen, Hannu. (2023). <i>Kernels and Graphs on M25 + H (parent repository)</i>. University of Jyväskylä. <a href="https://doi.org/10.17011/jyx/dataset/87525">https://doi.org/10.17011/jyx/dataset/87525</a>
dc.rightsCreative Commons Attribution 4.0 International
dc.titleKernels and Graphs on M25 + Hen
dc.typedataset
dc.identifier.urnURN:NBN:fi:jyu-202306073595
dc.contributor.tiedekuntaMatemaattis-luonnontieteellinen tiedekunta
dc.contributor.tiedekuntaFaculty of Mathematics and Science
dc.contributor.tiedekuntaInformaatioteknologian tiedekunta
dc.contributor.tiedekuntaFaculty of Information Technology
dc.contributor.laitosDepartment of Physics
dc.contributor.laitosFysiikan laitos
dc.contributor.yliopistoJyväskylän yliopisto
dc.contributor.yliopistoUniversity of Jyväskylä
dc.type.urihttp://purl.org/coar/resource_type/c_ddb1
dc.identifier.doi10.17011/jyx/dataset/87521
dc.rights.copyrightPihlajamäki, Antti and University of Jyväskylä
dc.rights.accesslevelopenAccess
dc.relation.grantnumber351579
dc.relation.grantnumber351583
dc.relation.grantnumber351582
dc.subject.ysomachine learningen
dc.subject.ysonanoparticlesen
dc.subject.ysocatalystsen
dc.subject.ysonanosciencesen
dc.subject.ysocatalysisen
dc.subject.ysonanomaterialsen
dc.subject.ysonanomateriaalitfi
dc.subject.ysokoneoppiminenfi
dc.subject.ysonanohiukkasetfi
dc.subject.ysokatalyytitfi
dc.subject.ysonanotieteetfi
dc.subject.ysokatalyysifi
jyx.subject.urihttp://www.yso.fi/onto/yso/p23451
jyx.subject.urihttp://www.yso.fi/onto/yso/p22976
jyx.subject.urihttp://www.yso.fi/onto/yso/p8704
jyx.subject.urihttp://www.yso.fi/onto/yso/p6228
jyx.subject.urihttp://www.yso.fi/onto/yso/p15480
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.funderSuomen Akatemia
dc.relation.funderAcademy of Finland
jyx.fundingprogramOthers, AoF
jyx.fundingprogramMuut, SA


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