Grain boundary segregation and phase separation in ceria-zirconia from atomistic simulation
Tom L. Underwood, Susanna Vigorito, Marco Molinari, John Purton, Nigel, B. Wilding, John T. S. Irvine, Stephen C. Parker

TL;DR
This paper introduces a computational method to predict phase separation and grain boundary segregation in ceria-zirconia, revealing complex behaviors and transitions at the atomic scale relevant for catalytic materials.
Contribution
A semi-grand canonical Monte Carlo approach is developed to accurately predict phase separation and segregation patterns in metal oxide solid solutions.
Findings
Most grain boundaries show increased Zr segregation with doping
Segregation reduces grain boundary formation enthalpies
Evidence of first-order complexion transitions in some boundaries
Abstract
Doping is the most common strategy employed in the development of new and improved materials. However, predicting the effects of doping on the atomic-scale structure of a material is often difficult or limited to high-end experimental techniques. Doping can induce phase separation in a material, undermining the material's stability. A further complication is that dopant atoms can segregate to interfaces in a material such as grain boundaries (GBs), with consequences for key macroscopic properties of the material such as its conductivity. Here, we describe a computational methodology based on semi-grand canonical Monte Carlo which can be used to probe these phenomena at the atomic scale for metal oxide solid solutions. The methodology can provide precise predictions of the thermodynamic conditions at which phase separation occurs. It can also provide the segregation patterns exhibited by…
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Taxonomy
TopicsCatalytic Processes in Materials Science · Metal Extraction and Bioleaching · Advancements in Solid Oxide Fuel Cells
