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Metal-air batteries are encountered as a promising solution for energy storage due to their high energy density, cost effectiveness, and environmental benefits. Yet, the application of metal-air batteries in practice is still not mature, which is also related to the bifunctional oxygen electrocatalysis at the cathode, comprising the oxygen reduction (ORR) and oxygen evolution (OER) reactions during discharge and charge of the battery, respectively. Experimentally, the performance of electrocatalysts in the OER and ORR is described by bifunctional index (BI), but, so far, there is no direct approach to capture the BI on the atomic scale. Herein, we present a method to ascertain the BI from ab initio theory, thereby combining a data-driven methodology with thermodynamic considerations and microkinetic modeling as a function of the applied overpotential. Our approach allows deriving the BI from simple adsorption free energies, which are easily accessible to electronic structure theory in the density functional theory (DFT) approximation. We outline how our methodology may steer the design of efficient bifunctional catalysts on the atomic scale.

The application of proton exchange membrane electrolyzers in practice to produce gaseous hydrogen as energy vector is majorly hampered by the sluggish oxygen evolution reaction (OER) at the anode. On the atomic scale, a scaling relation between the OH and OOH intermediates has been recognized as main limitation for the development of highly active OER catalysts. Breaking scaling relation is considered as a universal remedy to obtain OER materials with enhanced electrocatalytic activity. While it is a well-accepted paradigm that the optimum OER catalyst reveals a symmetric thermodynamic free-energy landscape, recently, it was suggested that the thermodynamic ideal may correspond to a free-energy landscape with asymmetric shape, allowing thermoneutral stabilization of the key intermediate at the target overpotential. In the present manuscript, we analyze breaking scaling relation in the OER to the symmetric and asymmetric thermodynamic free-energy landscapes by statistical methods at different applied overpotentials. Our analysis reveals that breaking scaling relation to the asymmetric rather than to the symmetric picture is statistically more significant as soon as an overpotential is applied, calling for a change in mindset when thermodynamic considerations are used for catalyst optimization.