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Detecting stable adsorbates of (1S)-camphor on Cu(111) with Bayesian optimization

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Jarvi, Jari
dc.contributor.author Rinke, Patrick
dc.contributor.author Todorovic, Milica
dc.date.accessioned 2020-11-30T08:18:33Z
dc.date.available 2020-11-30T08:18:33Z
dc.date.issued 2020-10-19
dc.identifier.citation Jarvi , J , Rinke , P & Todorovic , M 2020 , ' Detecting stable adsorbates of (1S)-camphor on Cu(111) with Bayesian optimization ' , Beilstein Journal of Nanotechnology , vol. 11 , pp. 1577-1589 . https://doi.org/10.3762/bjnano.11.140 en
dc.identifier.issn 2190-4286
dc.identifier.other PURE UUID: b67b5c5d-4719-402d-ac29-d2e7b12f2278
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/detecting-stable-adsorbates-of-1scamphor-on-cu111-with-bayesian-optimization(b67b5c5d-4719-402d-ac29-d2e7b12f2278).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/52797905/J_rvi_Detecting.2190_4286_11_140_1.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/61785
dc.description.abstract Identifying the atomic structure of organic-inorganic interfaces is challenging with current research tools. Interpreting the structure of complex molecular adsorbates from microscopy images can be difficult, and using atomistic simulations to find the most stable structures is limited to partial exploration of the potential energy surface due to the high-dimensional phase space. In this study, we present the recently developed Bayesian Optimization Structure Search ( BOSS) method as an efficient solution for identifying the structure of non-planar adsorbates. We apply BOSS with density-functional theory simulations to detect the stable adsorbate structures of (1S)-camphor on the Cu(111) surface. We identify the optimal structure among eight unique types of stable adsorbates, in which camphor chemisorbs via oxygen (global minimum) or physisorbs via hydrocarbons to the Cu(111) surface. This study demonstrates that new cross-disciplinary tools, such as BOSS, facilitate the description of complex surface structures and their properties, and ultimately allow us to tune the functionality of advanced materials. en
dc.format.extent 13
dc.format.extent 1577-1589
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Beilstein-Institut Zur Forderung der Chemischen Wissenschaften
dc.relation.ispartofseries Beilstein Journal of Nanotechnology en
dc.relation.ispartofseries Volume 11 en
dc.rights openAccess en
dc.title Detecting stable adsorbates of (1S)-camphor on Cu(111) with Bayesian optimization en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Applied Physics
dc.contributor.department Computational Electronic Structure Theory
dc.subject.keyword Bayesian optimization
dc.subject.keyword camphor
dc.subject.keyword Cu(111)
dc.subject.keyword density-functional theory
dc.subject.keyword electronic structure
dc.subject.keyword organic surface adsorbates
dc.subject.keyword physical chemistry
dc.subject.keyword structure search
dc.subject.keyword surface science
dc.subject.keyword ATOMIC-FORCE MICROSCOPY
dc.subject.keyword SURFACE
dc.subject.keyword MOLECULES
dc.subject.keyword SEARCH
dc.identifier.urn URN:NBN:fi:aalto-2020113020630
dc.identifier.doi 10.3762/bjnano.11.140
dc.type.version publishedVersion


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