(560gz) Surface Phase Diagrams of Strontium Titanium Oxide Using an Automated Ab-Initio Grand Canonical Monte Carlo Method

Solid state fuel cells are an alternative energy technology with great potential to impact the energy sector but require improvements to their cost and efficiency to achieve real-world viability. Currently, platinum electrodes are used as catalysts for the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) in regenerative fuel cells. However, Pt resources are limited, and the electrodes are limited by chemisorption scaling relations which prevents optimization of OER and ORR simultaneously. Perovskite materials have been studied for a variety of catalytic applications, including the OER and ORR. Transition metal oxide perovskites of the structure ABO₃ are potentially good replacements for the anode and cathode catalysts due to their stability under OER and ORR and their ability to be altered structurally, allowing for a greater optimization of the reaction for a fraction of the cost of noble-metal electrodes. Also, these materials are comprised of earth-abundant elements.

Reconstructions under different chemical environments of the material surfaces influences the surface chemistry and effectiveness of the ability to catalyze the reaction. Surface reconstructions of the perovskite catalysts was explored using an automated ab initio Grand Canonical Monte Carlo (GCMC) method to sample across thermodynamically relevant surface configurations. In this work, this method was utilized for the generation of surface phase diagrams of strontium titanium oxide (ST) which is important in predicting and understanding the surface chemistry behavior of the materials under differing conditions.

Reconstructing the surfaces of perovskite catalysts can circumvent factors that limit the OER. Theoretical and experimental studies on STO3 have shown that a TiO₂ rich surface can reduce the overpotential of the catalyst for this reaction.