(124h) Macroscale Modeling of Electrochemical CO2 Reduction on Copper Catalysts

Electrochemical CO₂ reduction (CO₂R) holds immense potential to assist in the decarbonization of chemical industry by using renewably sourced electricity to upconvert CO₂ to more valuable chemical and fuels. Of the catalysts explored for this process, only copper (Cu)-containing materials possess the ability to directly catalyze CO₂R to more valuable C₂₊ products with high selectivity. These findings motivate efforts to enhance selectivity of C₂₊ products and mitigate selectivity to less valuable C₁ products and hydrogen (H_2­), especially with regard to the effect of the local chemical microenvironment on catalytic performance. For instance, enhancements in local pH and CO₂ availability at the cathode surface have been demonstrated to suppress hydrogen (H₂) evolution and improve C₂₊ selectivity.

Macroscale modeling will be critical to understanding the effects of local microenvironment on the product distributions obtained in CO_­2R on Cu catalysts. However, there is a dearth of studies that have attempted to model product distributions on Cu catalysts under conditions relevant to CO₂R in electrochemical energy conversion devices. In this talk, I will discuss best practices in the development of simplified kinetic models capable of describing CO₂R on Cu catalysts, as well as the application of those kinetics within macroscale models simulating electrochemical CO₂R for various device architectures (liquid-fed planar H-cell, vapor-fed membrane electrode assembly, etc.). These macroscale models elucidate how the various chemical microenvironments accessible in these various device architectures lead to different observed product distributions. Using these insights, optimal device configurations are proposed to maximize the rate of C₂₊ formation and minimize the formation of undesired C₁ products and H₂.