Unraveling fundamental activity–stability relationships in rutile oxides

The oxygen evolution reaction (OER) is a widely studied anode reaction for several critical electrochemical reduction reactions, particularly because the OER tends to be kinetically sluggish in comparison to its cathodic counterpart. While consistent improvements have been made in rationalizing experimental OER activity and selectivity trends -- even qualitatively predicting OER performance -- the community has been unable to sufficiently describe or predict material aqueous (in)stability and degradation mechanisms, despite their importance to device lifetime and thus economic viability. In this work, we investigate the interplay, or lack thereof, between OER activity and material aqueous stability across rutile oxides, with a particular focus on iridum oxide (IrO2). By developing a Born-Haber thermodynamic cycle analogous to the computational hydrogen electrode (CHE) model, we enable facile prediction of the thermodynamic driving force for metal dissolution as a function of the applied bias and electrolyte conditions. We apply machine learning techniques, including principal component analysis and symbolic regression, to analyze trends across rutile oxides and find that key thermodynamic descriptors for OER activity and material aqueous stability are only very weakly correlated. Instead, the local atomic environment -- especially electronic structure signatures for interactions between the active site and its neighbors -- play a more important role in predicting material aqueous stability. Leveraging these insights, we investigate the impact of doping IrO2 with a range of transition metals and show that the stability of Ir active sites can be tuned largely independently of its predicted OER activity. These insights lay the foundation for material design to improve stability with respect to corrosion, with the ultimate aim to enhance long-term stability without sacrificing catalytic performance in the OER.