High-Throughput Computational Screening of Cubic Perovskites for Solid Oxide Fuel Cell Cathodes
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| 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 A I 0.5 A II 0.5 BO3 cubic perovskites is generated. Using E vac 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. |
| Year of Publication |
2021
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| Journal |
Journal of Physical Chemistry Letters
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| Volume |
12
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| Issue |
17
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| Number of Pages |
4160-4165
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| Date Published |
04/2021
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| DOI | |
| Dataset | |
| PId |
36ea5c0a4ea9d4d5b1825c689eec465e
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| Alternate Journal |
J. Phys. Chem. Lett.
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| Label |
OA
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| Attachment | |
Journal Article
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| Download citation |