(371ad) Multi-Scale Dynamic Techno-Economic Analysis of Pulsed Electrochemical CO2 Reduction Process

In recent years, research on pulsed electrochemical CO₂ reduction (p-eCO₂R) has gained attention, demonstrating merits such as high C₂₊ product selectivity, catalyst lifetime, and simple operation.^1,2 It offers a method to enhance performance by applying voltage in pulse form without modifying the intrinsic characteristics of the electrolyzer. The authors argued that this method could have economic feasibility because the additional electricity energy from the anodic step is minimal.^3,4 However, p-eCO₂R suffers from the issue that product is not produced during the application of anodic potential. This results in an increase in the minimum selling price (MSP) of the product as the duration of the anodic potential increases, thereby undermining its economic feasibility. Furthermore, the injection of CO₂ during the anodic step also contributes to an increase in unreacted CO₂, potentially leading to a decrease in the purity of the products. Hence, there is a cost-trade-off between issues arising from pulse application and performance enhancement. Additionally, a pulse generator is required for applying pulse power supplement system, and discontinuous flow of products should be controlled before they enter the separation process.

Previous research has predominantly focused on improving stability and selectivity at the electrolyzer scale.^5-7 However, optimizing the pulse profile is crucial, considering the cost trade-off associated with pulsed electrolysis and additional expenses incurred by supplementary processes. Therefore, techno-economic analysis (TEA) at the process scale of p-CO₂R is essential. Furthermore, observing the performance of the electrolyzer based on various pulse profiles necessitates a multiphysics model.^6,8

This study proposed a multiscale model that simultaneously considers pulsed CO₂ electrochemical reduction process system and multiphysics within the electrolyzer and implemented optimization of the pulse profile from the perspectives of TEA and life cycle assessment (LCA). To accomplish this, a COMSOL-based multiphysics model and process simulations using Aspen Plus were created, and TEA/LCA was conducted by integrating these two distinct scale models using Matlab. The electrolyzer was configured using an anion exchange membrane (AEM)-based exchange membrane-electrode-assembly. To improve alignment with experimental data, the kinetics parameters of the electrolyzer were fitted using derivative-free optimization (DFO) methods. TEA indicator includes the MSP of products, incorporating additional costs for achieving high purity through separation processes and for the p-CO₂R process. The system boundary of LCA is gate-to-gate, with global warming impact (GWI) set as the primary indicator. We integrated the completed multi-scale model with the DFO algorithm to find the optimal pulse profile. Finally, we connected this model with the real-time optimization (RTO) algorithm to implement real-time optimal operation based on a digital twin.

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