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High-Throughput Computational Screening of Cubic Perovskites for Solid Oxide Fuel Cell Cathodes

Author
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
Journal
Journal of Physical Chemistry Letters
Volume
12
Issue
17
Number of Pages
4160-4165
Date Published
04/2021
DOI
10.1021/acs.jpclett.1c00827
Dataset
10.1021/acs.jpclett.1c00827
PId
36ea5c0a4ea9d4d5b1825c689eec465e
Alternate Journal
J. Phys. Chem. Lett.
Label
OA
Attachment
Journal Article
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