| Hauptseite > Publikationsdatenbank > Microkinetic Analysis of the Oxygen Evolution Performance at Different Stages of Iridium Oxide Degradation |
| Journal Article | FZJ-2022-05334 |
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2022
American Chemical Society
Washington, DC
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Please use a persistent id in citations: http://hdl.handle.net/2128/33973 doi:10.1021/jacs.2c03561
Abstract: The microkinetics of the electrocatalytic oxygen evolutionreaction substantially determines the performance in proton-exchangemembrane water electrolysis. State-of-the-art nanoparticulated rutile IrO2electrocatalysts present an excellent trade-off between activity and stabilitydue to the efficient formation of intermediate surface species. To reveal andanalyze the interaction of individual surface processes, a detailed dynamicmicrokinetic model approach is established and validated using cyclicvoltammetry. We show that the interaction of three different processes, whichare the adsorption of water, one potential-driven deprotonation step, and thedetachment of oxygen, limits the overall reaction turnover. During the reaction,the active IrO2 surface is covered mainly by *O, *OOH, and *OO adsorbedspecies with a share dependent on the applied potential and of 44, 28, and 20%at an overpotential of 350 mV, respectively. In contrast to state-of-the-artcalculations of ideal catalyst surfaces, this novel model-based methodology allows for experimental identification of the microkineticsas well as thermodynamic energy values of real pristine and degraded nanoparticles. We show that the loss in electrocatalytic activityduring degradation is correlated to an increase in the activation energy of deprotonation processes, whereas reaction energies weremarginally affected. As the effect of electrolyte-related parameters does not cause such a decrease, the model-based analysisdemonstrates that material changes trigger the performance loss. These insights into the degradation of IrO2 and its effect on thesurface processes provide the basis for a deeper understanding of degrading active sites for the optimization of the oxygen evolutionperformance.
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