Abstract
Efficient predictive tools for oxygen evolution reaction (OER) activity assessment are vital for rational design of anodes for green hydrogen production. Reaction mechanism prediction represents an important pre-requisite for such catalyst design. Even then, lattice oxygen evolution remains understudied and without reliable prediction methods. We propose a computational screening approach using density functional theory to evaluate the lattice oxygen evolution tendency in candidate surfaces. The method is based on a systematic assessment of the adsorption energies of oxygen evolution intermediates on model active sites with varying local structure. The power of the model is shown on model rutile (110) oriented surfaces of a) RuO2, b) Ru(1−x)Ni(x)O2 and c) Ru(1−x)Ti(x)O2. The model predicts a) no lattice exchange, b) lattice exchange at elevated electrode potentials and c) minor lattice exchange at elevated electrode potentials and high titanium content. While in the case of a) and b) the predictions provide sufficiently accurate agreement with experimental data, c) experimentally deviates from the above prediction by expressing a high tendency to evolve lattice oxygen at high titanium content (x = 0.20). This discrepancy can likely be attributed to the presence of structural defects in the prepared material, which are hard to accurately model with the applied methodology.
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