Record link: 
http://hdl.handle.net/20.500.12708/139774
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Title: 
Neural-network-backed evolutionary search for SrTiO₃(110) surface reconstructions
en
Citation: 
Wanzenböck, R., Arrigoni, M., Bichelmaier, S., Buchner, F., Carrete, J., & Madsen, G. K. H. (2022). Neural-network-backed evolutionary search for SrTiO₃(110) surface reconstructions. Digital Discovery, 1(5), 703–710. https://doi.org/10.1039/d2dd00072e
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Publisher DOI: 
10.1039/d2dd00072e
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Publication Type: 
Article - Original Research Article
en
Language: 
English
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Authors: 
Wanzenböck, Ralf 
Arrigoni, Marco 
Bichelmaier, Sebastian 
Buchner, Florian 
Carrete, Jesús 
Madsen, Georg K H 
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Organisational Unit: 
E165-03-1 - Forschungsgruppe Theoretische Materialchemie 
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Journal: 
Digital Discovery 
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Date (published): 
1-Oct-2022
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Number of Pages: 
8
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Publisher: 
Royal Society of Chemistry (RSC)
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Peer reviewed: 
Yes
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Keywords: 
density functional theory; rich phase diagram; CMA-ES
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Research Areas: 
Quantum Modeling and Simulation: 20%
Materials Characterization: 40%
Computational Materials Science: 40%
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Science Branch: 
1040 - Chemie: 100%
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