Abstract

Yttria-stabilized zirconia (YSZ) is widely used as a fast oxygen ion conductor in solid oxide fuel cells. Over the years several studies have probed the effect of different cation arrangements on the O2− ion hopping behavior at the atomistic scale. However, an analytical model that can predict the macroscopic ionic conductivity using both the atomic scale hopping behavior as well as the spatial arrangement of cations at the mesoscopic length scale is lacking. A novel mesoscale model is constructed as a step towards addressing this gap. First, using a kinetic Monte Carlo (KMC) model for YSZ we find evidence of a fast ion conducting percolation network being present. The tortuous network, which consists of connected regions spanning the material structure, mainly contributes to the ionic conduction as O2− ion movement in other regions is relatively slow. The topology, composition and O2− ion movement in the network are analyzed. Next, the shortest path lengths in the network are identified with the help of the Dijsktra algorithm. Finally, a diffusion model is developed that relates the atomic scale hopping rates and shortest path lengths (a mesoscale feature) to the macroscale ionic conductivity. Estimates for ionic conductivity from the diffusion model are in excellent agreement with the KMC model. Changes within the percolation network with increasing Y2O3 content can describe the maximum observed in ionic conductivity.

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