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Structure of an Ult...
Structure of an Ultrathin Oxide on Pt3Sn(111) Solved by Machine Learning Enhanced Global Optimization.
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- Merte, Lindsay R. (författare)
- Malmö universitet,Institutionen för materialvetenskap och tillämpad matematik (MTM)
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- Bisbo, Malthe Kjær (författare)
- Center for Interstellar Catalysis Department of Physics and Astronomy Aarhus University 8000 Aarhus Denmark
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- Sokolović, Igor (författare)
- Institute of Applied Physics TU Wien 1040 Vienna Austria
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- Setvín, Martin (författare)
- Institute of Applied Physics TU Wien 1040 Vienna Austria; Department of Surface and Plasma Science Faculty of Mathematics and Physics Charles University 180 00 Prague 8 Czech Republic
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- Hagman, Benjamin (författare)
- Div. of Synchrotron Radiation Research Lund University 22100 Lund Sweden
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- Shipilin, Mikhail (författare)
- Div. of Synchrotron Radiation Research Lund University 22100 Lund Sweden
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- Schmid, Michael (författare)
- Institute of Applied Physics TU Wien 1040 Vienna Austria
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- Diebold, Ulrike (författare)
- Institute of Applied Physics TU Wien 1040 Vienna Austria
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- Lundgren, Edvin (författare)
- Div. of Synchrotron Radiation Research Lund University 22100 Lund Sweden
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- Hammer, Bjørk (författare)
- Center for Interstellar Catalysis Department of Physics and Astronomy Aarhus University 8000 Aarhus Denmark
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(creator_code:org_t)
- 2022-04-21
- 2022
- Engelska.
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Ingår i: Angewandte Chemie. - : John Wiley & Sons. - 0044-8249 .- 1521-3757. ; 134:25, s. e202204244-
- Relaterad länk:
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https://mau.diva-por... (primary) (Raw object)
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Abstract
Ämnesord
Stäng
- Determination of the atomic structure of solid surfaces typically depends on comparison of measured properties with simulations based on hypothesized structural models. For simple structures, the models may be guessed, but for more complex structures there is a need for reliable theory-based search algorithms. So far, such methods have been limited by the combinatorial complexity and computational expense of sufficiently accurate energy estimation for surfaces. However, the introduction of machine learning methods has the potential to change this radically. Here, we demonstrate how an evolutionary algorithm, utilizing machine learning for accelerated energy estimation and diverse population generation, can be used to solve an unknown surface structure-the (4×4) surface oxide on Pt3Sn(111)-based on limited experimental input. The algorithm is efficient and robust, and should be broadly applicable in surface studies, where it can replace manual, intuition based model generation.
Ämnesord
- NATURVETENSKAP -- Kemi -- Teoretisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Theoretical Chemistry (hsv//eng)
Nyckelord
- Density Functional Calculations
- Machine Learning
- Structure Elucidation
- Surface Chemistry
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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Till lärosätets databas
- Av författaren/redakt...
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Merte, Lindsay R ...
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Bisbo, Malthe Kj ...
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Sokolović, Igor
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Setvín, Martin
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Hagman, Benjamin
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Shipilin, Mikhai ...
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visa fler...
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Schmid, Michael
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Diebold, Ulrike
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Lundgren, Edvin
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Hammer, Bjørk
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visa färre...
- Om ämnet
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- NATURVETENSKAP
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NATURVETENSKAP
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och Kemi
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och Teoretisk kemi
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Angewandte Chemi ...
- Av lärosätet
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Malmö universitet