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Machine learning in nuclear materials research

dc.contributor.authorMorgan, Dane
dc.contributor.authorPilania, Ghanshyam
dc.contributor.authorCouet, Adrien
dc.contributor.authorUberuaga, Blas P
dc.contributor.authorSun, Cheng
dc.contributor.authorLi, Ju
dc.date.accessioned2023-01-20T15:01:13Z
dc.date.available2023-01-20T15:01:13Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/1721.1/147584
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionof10.1016/J.COSSMS.2021.100975en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcearXiven_US
dc.titleMachine learning in nuclear materials researchen_US
dc.typeArticleen_US
dc.identifier.citationMorgan, Dane, Pilania, Ghanshyam, Couet, Adrien, Uberuaga, Blas P, Sun, Cheng et al. 2022. "Machine learning in nuclear materials research." Current Opinion in Solid State and Materials Science, 26 (2).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineeringen_US
dc.relation.journalCurrent Opinion in Solid State and Materials Scienceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2023-01-20T14:43:50Z
dspace.orderedauthorsMorgan, D; Pilania, G; Couet, A; Uberuaga, BP; Sun, C; Li, Jen_US
dspace.date.submission2023-01-20T14:43:58Z
mit.journal.volume26en_US
mit.journal.issue2en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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