A definitive screening design framework systematically resolves coupled component effects in Cu gas diffusion electrodes for CO2 reduction. By integrating statistical modeling, validation experiments, and structural analysis, this study identifies dominant and conditional electrode component effects, enabling predictive formulation selection and guiding rational fabrication of multi-component gas diffusion electrodes for enhanced multi-carbon selectivity.
ABSTRACT
A Design of Experiments (DoE) approach is used in the design and development of gas diffusion electrodes (GDEs) for electrochemical CO2 reduction (CO2R). Rational GDE design remains challenging due to the presence of multiple components and their complex effects on performance. Here, five electrode components, Cu, carbon, polytetrafluoroethylene, Nafion, and Sustainion, are evaluated for electrochemical CO2R using the DoE approach by evaluating 17 distinct single-active-layer (SAL)-GDEs. Experimental results are analyzed using a definitive screen design (DSD) framework to identify component-performance relationships, including first- and second-order effects. Nafion is found to strongly affect overall product distribution, while carbon is most influential for improving C2H4 selectivity. The DSD models are validated with experiments, enabling formulation predictions beyond the original design space. Following model predictions, increasing carbon loading was experimentally shown to improve C2H4 selectivity, achieving a peak faradaic efficiency of 36.1%. The improvement is rationalized by structural characterization, which reveals that increased carbon loading leads to electrode porosity and Cu dispersion favorable for CO2 transport and interfacial surface area. This work demonstrates the strength of statistical methods for rationally designing complex, multi-component GDE architectures and understanding interacting component effects, highlighting potential impact across a wide range of electrochemical conversion systems.