Optimized patterning of tandem catalysts for CO₂ reduction in flow reactors

In the global shift towards a sustainable energy future, electrochemical CO₂ reduction (CO2R) is a promising emerging means to produce fuels and value-added chemicals. The CO₂ feed flow provides an avenue to utilize waste emissions, and using a renewable electricity source yields an overall carbon-neutral process.

Metal catalysts are used to decrease the overpotential and to tune the selectivity towards desired products. To achieve higher selectivity and yield, improved CO2R reactor designs are needed. Mass transport models are useful to study in-reactor processes. In this work, we integrate mass transport simulations with adjoint-based optimization to improve CO2R reactor design. A flow reactor setup with a tandem (or cascade) patterning of silver and copper catalyst sections leverages the distinctive strengths of each catalyst: CO₂ → CO on Ag and CO → C₂₊ products on Cu. The optimization scheme iteratively modifies the Ag/Cu electrode patterning until reaching an optimal design. Noticeable current density improvements are reached by the optimized designs, especially with high frequency patterning (i.e., a large number of Ag/Cu sections).

This simplified flow reactor framework is a stepping stone to use optimization in designing industrially-relevant CO2R geometries such as gas diffusion electrodes.