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

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 (HT-DFT) calculations, oxygen vacancy formation energy, E_vac, data for a pool of all-inorganic ABO₃ and A^I_0.5A^II_0.5BO₃ 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 in between state-of-the-art SOFC cathode and oxygen permeation components. In addition, an intuitive approach to estimate E_vac and ASR data of complex perovskites solely by using the easy-to-access data of simple perovskites is shown, which is expected to boost future explorations on perovskite material search space for genuinely diverse energy applications.