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William Bowman1 Amith Darbal2 Peter Crozier3

1, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
2, AppFive LLC, Tempe, Arizona, United States
3, Arizona State University, Tempe, Arizona, United States

High ionic conductivity is desired to optimize electrolyte performance, though it is significantly degraded by grain boundaries (GBs), which act as blocking layers in polycrystalline electrolytes. Given the rich diversity in GB types, and the complex interplay between structure, composition, and chemistry at the atomic and nanoscale [1-3], there is considerable opportunity to elucidate fundamental science and performance optimization of GBs. Hence, studies should rely on GB datasets correlated across many length scales, with the aim of generalizing high spatial resolution observations to an entire GB population. This should facilitate bottom-up design of GBs with optimized properties, which remains a considerable challenge. By combining suitable modeling approaches with experimental measurements interrogating materials over different length scales, it becomes possible to estimate the electrical properties of individual GBs.

Here a novel correlated approach is employed combining precession electron nanodiffraction (PED) orientation imaging and electron energy-loss spectroscopy (EELS) in an aberration-corrected scanning TEM to elucidate the GB transport properties in oxygen-conducting Gd0.11Pr0.04Ce0.85O2-δ [3]. Nanoscale EELS measurements of GB solute segregation are generalized to the entire boundary population via GB character determined using PED. Composition data are used to estimate carrier concentration and migration activation energy, which enables prediction and mapping of the distribution of GB ionic conductivity. The applicability of conventional GB models—used widely to predict defect distribution and transport properties—to the presented data is also evaluated.

Acknowledgements
NSF Graduate Research Fellowship (DGE-1211230), NSF grant DMR-1308085, ASU’s John M. Cowley Center for High Resolution EM.

References
[1] W.J. Bowman, J. Zhu, R. Sharma, P.A. Crozier. Solid State Ion. 272 (2015) 9-17.
[2] W.J. Bowman, M.N. Kelly, G.S. Rohrer, C.A. Hernandez, P.A. Crozier. Nanoscale (2017).
[3] W.J. Bowman, A.D. Darbal, P.A. Crozier. (Submitted).

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