IrO2 surface complexions identified through machine learning and surface investigations

J. Timmermann, F. Kraushofer, N. Resch, P. Li, Y. Wang, Z. Mao, M. Riva, Y. Lee, C. Staacke, M. Schmid, C. Scheurer, G. S. Parkinson, U. Diebold, K. Reuter

Institut für Angewandte Physik, TU Wien, 1040 Wien, Austria

Phys. Rev. Lett. 125 (2020) 206101

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.

Corresponding author: Karsten Reuter. Reprints also available from Michael Schmid (schmid at iap_tuwien_ac_at).

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