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 calculations, oxygen vacancy formation energy, E-vac, data for a pool of all-inorganic ABO(3) and A(0.5)(I)A(0.5)(II)BO(3) 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 E-vac 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.

Automated summary

This study performed density functional theory calculations to generate oxygen vacancy formation energy data for a range of cubic perovskite materials, and calculated area-specific resistance data related to oxygen reduction reaction and oxygen ion conductivity. By screening 31 candidate perovskites, the study identified materials with properties between state-of-the-art SOFC cathode and oxygen permeation components. The research also presented an intuitive approach to estimate complex perovskite data by using simple perovskite data, aiming to boost future explorations in diverse energy applications.