(126f) Effect of Electric Field on Kinetic Modeling of the ORR: Rationalizing pH Behavior of Metal and Oxide ORR Catalysts | AIChE

(126f) Effect of Electric Field on Kinetic Modeling of the ORR: Rationalizing pH Behavior of Metal and Oxide ORR Catalysts

Authors 

Kelly, S. R. - Presenter, Stanford University
Norskov, J. - Presenter, Stanford University
Chan, K., Technical University of Denmark
Kirk, C., Stanford University
Previously developed kinetic models have captured activity trends across oxygen reduction reaction (ORR) catalysts but have failed to explain the effect of pH on ORR activity, or how these pH effects vary across catalysts. Here, we present a newly developed kinetic model which incorporates the effect of electric field on ORR activity, and show that this model predicts experimental results across the entire pH range on several catalysts with remarkable accuracy. Using only the effect of electric field, we are able to qualitatively and somewhat quantitatively predict onset potentials, H2O2 activity, and Tafel slopes for Pt(111), Au(111), and Au(100) catalysts. We then use this model to produce activity volcanoes for both 2e- and 4e-ORR, allowing us to better understand pH trends on various catalysts. We show that electric field has a comparatively large effect on the energetics of the OOH adsorbate, leading to larger pH dependencies on weak binding catalysts, which are limited by protonation of O2 to form OOH. Conversely, strong binding catalysts, which are limited by OH coverage, are much less affected by changes in pH (see attached figure).

Next, we show that this simple kinetic model can also explain experimental trends seen on oxide catalysts used in the ORR. By considering subtle differences in the O vs OH scaling relation as well as the effect of electric field, we are able to explain why researchers have struggled to find oxide catalysts which compete with platinum for 4e-ORR activity in acid, as well as why oxide catalysts tend to be more selective toward the 2e-ORR than similar metal catalysts. Ultimately, we show that that this updated kinetic model can help explain experimentally observed catalytic trends, as well as help predict future oxygen reduction catalysts.

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