(66c) Influence of pH on Oxygen-Evolution-Reaction Mechanism | AIChE

(66c) Influence of pH on Oxygen-Evolution-Reaction Mechanism


Weng, L. C., Joint Center for Artificial Photosynthesis, LBNL
Pham, T. A., Lawrence Livermore National Laboratory
Alia, S., National Renewable Energy Laboratory
Bell, A., UC Berkeley
Danilovic, N., Lawrence Berkeley National Laboratory
Weber, A., Lawrence Berkeley National Laboratory
Ogitsu, T., Lawrence Livermore National Lab
Zhan, C., Lawrence Livermore National Laboratory
As renewable energy generation grows, it is predicted that there will be an excess of inexpensive electrons. Storing and using this excess electricity in chemical bonds provides a foundation for carbon-free technologies and products. The key, and often limiting, reaction in this process, whether CO2 reduction or water electrolysis, is the oxygen evolution reaction (OER). OER occurs in multiple environments across the pH range depending on the specific cell and products. Of particular interest is the near-neutral range as it avoids corrosive highly acidic or alkaline solutions and is compatible with photoelectrochemical water splitting among other technologies. However, there is little understanding how OER proceeds under these environments.

In this talk, we will explore OER mechanism across length scales by coupling ab-initio energy barrier predictions from DFT with continuum models of ion transport and a microkinetic framework including both alkaline and acidic pathways. Comparison of the simulation to experimental data elucidates the OER mechanism and surface species coverages across a broad pH range (1 to 13). Studying the microkinetics provide details of the rate-determining steps for the reaction as a function of surface pH. Such effects are especially prevalent in near-neutral pHs, where ionic concentration gradients and boundary-layer thickness play a significant role. Additionally, the results demonstrate that the alkaline pathway dominates under most pH conditions and for various steps in the mechanism. Both the model and experimental results highlight that OER rate actually increases at the mid pH range due to the confluence of multiple pathways. Overall, the approach and results provide foundational knowledge for how OER proceeds and ways to analyze the reaction pathway and optimize performance.

J.C.F. would like to acknowledge support from National Science Foundation Graduate Research Fellowship under Grant No. DGE 1106400. This work was partially funded by Department of Energy’s HydroGEN consortium.