The exceptionally large height of the potential barrier at the grain boundary of a LaGaO3-based solid solution deduced from a linear diffusion model
Literature Information
Chih-Yuan S. Chang, Igor Lubomirsky, Sangtae Kim
The extent of the influence of space charge on the electric current through the grain boundary in solid electrolytes can be parameterized by the grain boundary potential, i.e. the height of the potential barrier formed at the grain boundary. Previously the value of this parameter has been estimated exclusively by the ratio of the grain boundary resistivity to the bulk counterpart over several decades. We recently demonstrated that it can be alternatively determined by analyzing the current–voltage characteristic of the grain boundary. Furthermore, we theoretically justified that the conventional method is in fact a subset of the new method, therefore, the latter is a more reliable and comprehensive approach to determine the grain boundary potential. Here, we present the experimental results that verify our theoretical justification. The values of the grain boundary potential determined for 1 mol% Sr-doped LaGaO3 (LSG1) employing both methods are in excellent agreement with one another. Such a consistency has not been reported for other solid electrolytes to date and we provide an explanation for it. Our data also indicate that for the case of LSG1, the Nernst–Einstein relation is preserved at the electric field exceeding 900 kV cm−1.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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