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  IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations

Timmermann, J., Kraushofer, F., Resch, N., Li, P., Wang, Y., Mao, Z., et al. (2020). IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations. Physical Review Letters, 125(20): 206101. doi:10.1103/PhysRevLett.125.206101.

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PhysRevLett.125.206101.pdf (Publisher version), 2MB
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PhysRevLett.125.206101.pdf
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 Creators:
Timmermann, Jakob1, Author
Kraushofer, Florian2, Author
Resch, Nikolaus2, Author
Li, Peigang3, Author
Wang, Yu4, Author
Mao, Zhiqiang3, 4, Author
Riva, Michele2, Author
Lee, Yonghyuk1, Author
Staacke, Carsten1, Author
Schmid, Michael2, Author
Scheurer, Christoph1, Author
Parkinson, Gareth S.2, Author
Diebold, Ulrike2, Author
Reuter, Karsten5, Author           
Affiliations:
1Chair for Theoretical Chemistry and Catalysis Research Center, Technical University of Munich, Lichtenbergstrasse 4, D-85747 Garching, Germany, ou_persistent22              
2Institute of Applied Physics, Technical University of Vienna, Wiedner Hauptstrasse 8-10/134, A-1040 Vienna, Austria, ou_persistent22              
3Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, USA, ou_persistent22              
4Department of Physics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA, ou_persistent22              
5Theory, Fritz Haber Institute, Max Planck Society, ou_634547              

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 Abstract: A Gaussian approximation potential was trained using density-functional theory data to enable a globalgeometry optimization of low-index rutile IrO2 facets through simulated annealing.Ab initiothermo-dynamics identifies (101) and (111) (1×1) terminations competitive with (110) in reducing environments.Experiments on single crystals find that (101) facets dominate and exhibit the theoretically predicted(1×1) periodicity and x-ray photoelectron spectroscopy core-level shifts. The obtained structures areanalogous to the complexions discussed in the context of ceramic battery materials.

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Language(s): eng - English
 Dates: 2020-07-052020-09-222020-11-102020-11-13
 Publication Status: Issued
 Pages: 6
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1103/PhysRevLett.125.206101
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Title: Physical Review Letters
  Abbreviation : Phys. Rev. Lett.
Source Genre: Journal
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Publ. Info: Woodbury, N.Y. : American Physical Society
Pages: 6 Volume / Issue: 125 (20) Sequence Number: 206101 Start / End Page: - Identifier: ISSN: 0031-9007
CoNE: https://pure.mpg.de/cone/journals/resource/954925433406_1