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IrO2 Surface Complexions Identified Through Machine Learning and Surface Investigations
- Source :
- Physical Review Letters
- Publication Year :
- 2020
- Publisher :
- arXiv, 2020.
-
Abstract
- A Gaussian Approximation Potential (GAP) 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) (1x1)-terminations competitive with (110) in reducing environments. Experiments on single crystals find that (101) facets dominate, and exhibit the theoretically predicted (1x1) periodicity and X-ray photoelectron spectroscopy (XPS) core level shifts. The obtained structures are analogous to the complexions discussed in the context of ceramic battery materials.<br />Comment: 13 pages 2 figures
Details
- Database :
- OpenAIRE
- Journal :
- Physical Review Letters
- Accession number :
- edsair.doi.dedup.....e900a35c24d0f5177759a8268a35a6fc
- Full Text :
- https://doi.org/10.48550/arxiv.2009.11569