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- All Subjects: Grain boundaries
- Creators: Bowman, William John
Description
Because of their favorable ionic and/or electronic conductivity, non-stoichiometric oxides are utilized for energy storage, energy conversion, sensing, catalysis, gas separation, and information technologies, both potential and commercialized. Charge transport in these materials is influenced strongly by grain boundaries, which exhibit fluctuations in composition, chemistry and atomic structure within Ångstroms or nanometers. Here, studies are presented that elucidate the interplay between macroscopic electrical conductivity, microscopic character, and local composition and electronic structure of grain boundaries in polycrystalline ceria-based (CeO2) solid solutions. AC impedance spectroscopy is employed to measure macroscopic electrical conductivity of grain boundaries, and electron energy-loss spectroscopy (EELS) in the aberration-correction scanning transmission electron microscope (AC-STEM) is used to quantify local composition and electronic structure. Electron diffraction orientation imaging microscopy is employed to assess microscopic grain boundary character, and links these macro- and nanoscopic techniques across length scales.
A model system, CaxCe1-xO2-x-δ, is used to systematically investigate relationships between nominal Ca2+ concentration, grain boundary ionic conductivity, microscale character, and local solute concentration. Grain boundary conductivity varied by several orders of magnitude over the composition range, and assessment of grain boundary character highlighted the critical influence of local composition on conductivity. Ceria containing Gd3+ and Pr3+/4+ was also investigated following previous theoretical work predicting superior ionic conductivity relative to state-of-the-art GdxCe1-xO2-x/2-δ. The grain boundary conductivity was nearly 100 times greater than expected and a factor four enrichment of Pr concentration was observed at the grain boundary, which suggested electronic conduction that was cited as the origin of the enhanced conductivity. This finding inspired the development of two EELS-based experimental approaches to elucidate the effect of Pr enrichment on grain boundary conductivity. One employed ultra-high energy resolution (~10 meV) monochromated EELS to characterize Pr inter-bandgap electronic states. Alternatively, STEM nanodiffraction orientation imaging coupled with AC-STEM EELS was employed to estimate the composition of the entire grain boundary population in a polycrystalline material. These compositional data were the input to a thermodynamic model used to predict electrical properties of the grain boundary population. These results suggest improved DC ionic conduction and enhanced electronic conduction under AC conditions.
A model system, CaxCe1-xO2-x-δ, is used to systematically investigate relationships between nominal Ca2+ concentration, grain boundary ionic conductivity, microscale character, and local solute concentration. Grain boundary conductivity varied by several orders of magnitude over the composition range, and assessment of grain boundary character highlighted the critical influence of local composition on conductivity. Ceria containing Gd3+ and Pr3+/4+ was also investigated following previous theoretical work predicting superior ionic conductivity relative to state-of-the-art GdxCe1-xO2-x/2-δ. The grain boundary conductivity was nearly 100 times greater than expected and a factor four enrichment of Pr concentration was observed at the grain boundary, which suggested electronic conduction that was cited as the origin of the enhanced conductivity. This finding inspired the development of two EELS-based experimental approaches to elucidate the effect of Pr enrichment on grain boundary conductivity. One employed ultra-high energy resolution (~10 meV) monochromated EELS to characterize Pr inter-bandgap electronic states. Alternatively, STEM nanodiffraction orientation imaging coupled with AC-STEM EELS was employed to estimate the composition of the entire grain boundary population in a polycrystalline material. These compositional data were the input to a thermodynamic model used to predict electrical properties of the grain boundary population. These results suggest improved DC ionic conduction and enhanced electronic conduction under AC conditions.
ContributorsBowman, William John (Author) / Crozier, Peter A. (Thesis advisor) / Chan, Candace K. (Committee member) / McCartney, Martha (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2016