Homogenized Modeling of CO2/CO Reduction Catalyst Microenvironments with Intermixed Hydrophobic and Hydrophilic Regions

Electroreduction of CO and CO 2 offer a pathway toward renewable-powered synthesis of hydrocarbon chemicals and fuels. Both the composition and the structure of cathodic catalyst microenvironments in gas diffusion electrodes play a dominant role in determining the product composition and efficiency metrics. Porous and hydrophilic copper environments are known to produce multi-carbon species and exhibit large active surface areas, but recent investigations have shown that the inclusion of sporadically-distributed porous hydrophobic regions creates additional pathways for the delivery of gaseous reactants, thereby mitigating transport limitations seen in pure Cu catalysts. As the design space for catalysts has grown to include a wide variety of material and geometric parameters, accurate PDE-based modeling and simulation of such systems has become necessary to understand and optimize the coupled reaction and transport processes that determine cell performance. High fidelity models, however, pose immense computational challenges. Physical and chemical processes occur over a wide variety of spatiotemporal scales, ranging from pore-scale reaction and transport to device-scale gradients in species concentrations. Additionally, the spatial orientation of these features necessitates modeling in multiple dimensions, and transport occurs simultaneously through two phases located within randomly-intermixed porous regions. As a result of all these factors, numerical simulation of high fidelity models is prohibitively expensive. In this work, we develop, numerically simulate, and validate a predictive model that efficiently incorporates a wide range of physical and chemical processes occurring in catalyst microenvironments with intermixed hydrophobic and hydrophilic regions. We employ homogenization as a means of model reduction, constructing a medium fidelity model that captures both microenvironment geometric scales and full device scales in 3D. Our model, coupled with the appropriate numerical methods for treatment of stiff and multi-dimensional problems, permits low-cost exploration of the high-dimensional parameter space associated with recently developed catalysts, offering quantitative insight into the optimal design of microenvironments for CO and CO 2 electroreduction. This work is supported by the United States Department of Energy under grant DE-SC0021633.