Identifying Stable Electrocatalysts Initialized by Data Mining: Sb 2 WO 6 for Oxygen Reduction.

Data mining from computational materials database has become a popular strategy to identify unexplored catalysts. Herein, the opportunities and challenges of this strategy are analyzed by investigating a discrepancy between data mining and experiments in identifying low-cost metal oxide (MO) electrocatalysts. Based on a search engine capable of identifying stable MOs at the pH and potentials of interest, a series of MO electrocatalysts is identified as potential candidates for various reactions. Sb 2 WO 6 attracted the attention among the identified stable MOs in acid. Based on the aqueous stability diagram, Sb 2 WO 6 is stable under oxygen reduction reaction (ORR) in acidic media but rather unstable under high-pH ORR conditions. However, this contradicts to the subsequent experimental observation in alkaline ORR conditions. Based on the post-catalysis characterizations, surface state analysis, and an advanced pH-field coupled microkinetic modeling, it is found that the Sb 2 WO 6 surface will undergo electrochemical passivation under ORR potentials and form a stable and 4e-ORR active surface. The results presented here suggest that though data mining is promising for exploring electrocatalysts, a refined strategy needs to be further developed by considering the electrochemistry-induced surface stability and activity.