Electrochemical (EC) carbon dioxide (CO₂) reduction, where CO₂ is converted to value-added products such as fuel precursors, plays a key role in helping the world’s energy system reach net-zero carbon emissions. Simulations of EC cells provide valuable insight into their operation since detailed experimental results on short length and time scales are difficult to obtain. In this work, we construct a 1D simulation of a membrane-electrode-assembly EC cell for CO₂ reduction, using a porous silver gas diffusion cathode. We run the simulation under different electrolyte conditions, showing how the cell performance is affected. We then perform a sensitivity analysis of all input parameters to the simulation, which has not been presented before in the literature. We show that the CO partial current density (i_CO) is significantly affected by each input parameter of the simulation. i_CO is most sensitive to EC kinetic parameters (i₀/α) of all EC reactions, with a 1% change in α resulting in up to 6% change in i_CO. Since there is uncertainty associated with the value of each input parameter, this indicates that infidelity between experiment and simulation is likely, and thus, caution should be practiced when comparing experimental results to simulation results. Further, we show that the large range of conditions simulated in literature helps to explain the large variance in reported values of i₀ and α. The results of this paper demonstrate the potential of sensitivity analysis methods to quickly optimize aspects of cell performance (CO₂ utilization, Faradaic efficiency, etc.).

中文翻译：

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CO2电解槽一维多物理场仿真灵敏度分析


电化学 (EC) 二氧化碳 (CO ₂ ) 还原（将 CO ₂ 转化为燃料前体等增值产品）在帮助世界能源系统实现目标方面发挥着关键作用净零碳排放。 EC 细胞的模拟为了解其运行提供了宝贵的见解，因为很难获得短长度和时间尺度的详细实验结果。在这项工作中，我们使用多孔银气体扩散阴极构建了用于 CO ₂ 还原的膜电极组件 EC 电池的一维模拟。我们在不同电解质条件下运行模拟，显示电池性能受到的影响。然后，我们对模拟的所有输入参数进行敏感性分析，这在以前的文献中从未出现过。我们表明 CO 部分电流密度 (i _CO ) 受到模拟的每个输入参数的显着影响。在所有 EC 反应中，i _CO 对 EC 动力学参数 (i ₀ /α) 最敏感，α 变化 1% 会导致 i _CO 。由于每个输入参数的值都存在不确定性，这表明实验和仿真之间可能存在不真实性，因此，在将实验结果与仿真结果进行比较时应小心谨慎。此外，我们表明文献中模拟的大范围条件有助于解释 i ₀ 和 α 报告值的巨大差异。本文的结果证明了灵敏度分析方法在快速优化电池性能方面（CO ₂ 利用率、法拉第效率等）的潜力。