Double layer capacitance of anode/solid-electrolyte interfaces
Literature Information
The double layer of electrode/electrolyte interfaces plays a fundamental role in determining the performance of solid state electrochemical cells. The double layer capacitance is one of the most-studied descriptors of the double layer. This work examines a case study on lanthanum strontium vanadate (LSV)/yttria-stabilized zirconia (YSZ) interfaces exposed in solid oxide fuel cell anode environment. The apparent double layer capacitance is obtained from impedance spectroscopy. The intrinsic double layer capacitance is evaluated based on Stern's method in conjunction with the Volta potential analysis across LSV/YSZ interfaces. Both the apparent and the intrinsic double layer capacitances exhibit right-skewed volcano patterns, when the interfaces are subjected to anodic biases from 0 to 150 mV. The apparent double layer capacitance is about one order of magnitude larger than the intrinsic double layer capacitance. This discrepancy roots in the inconsistent surface areas that are involved. This analysis of capacitance would provide a more realistic TPB estimate of a working solid-state electrochemical device.
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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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