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Article: Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

TitleNeuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport
Authors
Fan, ZZeng, ZZhang, CWang, YSong, KDong, HChen, YAla-Nissila, T
Issue Date2021
Citation
Physical Review B, 2021, v. 104 n. 10, p. 104309 How to Cite?
Persistent Identifierhttp://hdl.handle.net/10722/314692

 

DC FieldValueLanguage
dc.contributor.authorFan, Z-
dc.contributor.authorZeng, Z-
dc.contributor.authorZhang, C-
dc.contributor.authorWang, Y-
dc.contributor.authorSong, K-
dc.contributor.authorDong, H-
dc.contributor.authorChen, Y-
dc.contributor.authorAla-Nissila, T-
dc.date.accessioned2022-08-05T09:32:52Z-
dc.date.available2022-08-05T09:32:52Z-
dc.date.issued2021-
dc.identifier.citationPhysical Review B, 2021, v. 104 n. 10, p. 104309-
dc.identifier.urihttp://hdl.handle.net/10722/314692-
dc.languageeng-
dc.relation.ispartofPhysical Review B-
dc.titleNeuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport-
dc.typeArticle-
dc.identifier.emailChen, Y: yuechen@hku.hk-
dc.identifier.authorityChen, Y=rp01925-
dc.identifier.hkuros334983-
dc.identifier.volume104-
dc.identifier.issue10-
dc.identifier.spage104309-
dc.identifier.epage104309-

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