IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations

Jakob Timmermann; Florian Kraushofer; Nikolaus Resch; Peigang Li; Yu Wang; Zhiqiang Mao; Michele Riva; Yonghyuk Lee; Carsten Staacke; Michael Schmid; Christoph Scheurer; Gareth S. Parkinson; Ulrike Diebold; Karsten Reuter

doi:10.1103/PhysRevLett.125.206101

IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations

Jakob Timmermann, Florian Kraushofer, Nikolaus Resch, Peigang Li, Yu Wang, Zhiqiang Mao, Michele Riva, Yonghyuk Lee, Carsten Staacke, Michael Schmid, Christoph Scheurer, Gareth S. Parkinson, Ulrike Diebold, Karsten Reuter

Research output: Contribution to journal › Article › peer-review

36 Scopus citations

Abstract

A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics 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 are analogous to the complexions discussed in the context of ceramic battery materials.

Original language	English (US)
Article number	206101
Journal	Physical review letters
Volume	125
Issue number	20
DOIs	https://doi.org/10.1103/PhysRevLett.125.206101
State	Published - Nov 10 2020

All Science Journal Classification (ASJC) codes

General Physics and Astronomy

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10.1103/PhysRevLett.125.206101

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title = "IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations",

abstract = "A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics 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 are analogous to the complexions discussed in the context of ceramic battery materials.",

author = "Jakob Timmermann and Florian Kraushofer and Nikolaus Resch and Peigang Li and Yu Wang and Zhiqiang Mao and Michele Riva and Yonghyuk Lee and Carsten Staacke and Michael Schmid and Christoph Scheurer and Parkinson, {Gareth S.} and Ulrike Diebold and Karsten Reuter",

note = "Publisher Copyright: {\textcopyright} 2020 American Physical Society.",

year = "2020",

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doi = "10.1103/PhysRevLett.125.206101",

language = "English (US)",

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T1 - IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations

AU - Timmermann, Jakob

AU - Kraushofer, Florian

AU - Resch, Nikolaus

AU - Li, Peigang

AU - Wang, Yu

AU - Mao, Zhiqiang

AU - Riva, Michele

AU - Lee, Yonghyuk

AU - Staacke, Carsten

AU - Schmid, Michael

AU - Scheurer, Christoph

AU - Parkinson, Gareth S.

AU - Diebold, Ulrike

AU - Reuter, Karsten

PY - 2020/11/10

Y1 - 2020/11/10

N2 - A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics 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 are analogous to the complexions discussed in the context of ceramic battery materials.

AB - A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics 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 are analogous to the complexions discussed in the context of ceramic battery materials.

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IrO2 Surface Complexions Identified through Machine Learning and Surface Investigations

Abstract

All Science Journal Classification (ASJC) codes

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