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- W3136989482 abstract "It is a present-day challenge to design and develop oxygen-permeable solid oxide fuel cell (SOFC) electrode and electrolyte materials that operate at low temperatures. Herein, by performing high-throughput density functional theory calculations, oxygen vacancy formation energy, Evac, data for a pool of all-inorganic ABO3 and AI0.5AII0.5BO3 cubic perovskites is generated. Using Evac data of perovskites, the area-specific resistance (ASR) data, which is related to both oxygen reduction reaction activity and selective oxygen ion conductivity of materials, is calculated. Screening a total of 270 chemical compositions, 31 perovskites are identified as candidates with properties that are between those of state-of-the-art SOFC cathode and oxygen permeation components. In addition, an intuitive approach to estimate Evac and ASR data of complex perovskites by using solely the easy-to-access data of simple perovskites is shown, which is expected to boost future explorations in the perovskite material search space for genuinely diverse energy applications." @default.
- W3136989482 created "2021-03-29" @default.
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- W3136989482 creator A5073500004 @default.
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- W3136989482 date "2021-04-23" @default.
- W3136989482 modified "2023-09-24" @default.
- W3136989482 title "High-Throughput Computational Screening of Cubic Perovskites for Solid Oxide Fuel Cell Cathodes" @default.
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- W3136989482 doi "https://doi.org/10.1021/acs.jpclett.1c00827" @default.
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