(670c) A Systematic Analysis of the Electrochemical Reduction of CO2 Using Uncertainty Quantification

Electrochemical reduction of CO₂ has emerged as a promising technology to combat climate change. Despite significant advancements in catalyst materials and electrolyzer optimization, translating this progress into practical applications is challenging due to the system's complex multiphase and multiscale nature, particularly under industrially relevant conditions. Accounting for uncertainties in the physical system is crucial to develop more accurate models, ranging from estimating kinetic parameters to biases in transport parameters. In this study, we perform uncertainty quantification of an electrochemical cell model validated against experimental data. We explore the uncertainties associated with the input model parameters and compare them with the experimental measurements, assessing the reliability of the model predictions. Our analysis also sheds light on the contribution of different parameters to the variation in current density predictions, which can help build confidence in the model. By quantifying the biases and uncertainties in model parameters, we can develop more accurate models, which could accelerate the translation of the electrochemical reduction of CO₂ into practical applications.