A versatile optimization framework for porous electrode design†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY Digital discovery Pub Date : 2024-04-25 DOI:10.1039/D3DD00247K
Maxime van der Heijden, Gabor Szendrei, Victor de Haas and Antoni Forner-Cuenca
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Abstract

Porous electrodes are performance-defining components in electrochemical devices, such as redox flow batteries, as they govern the electrochemical performance and pumping demands of the reactor. Yet, conventional porous electrodes used in redox flow batteries are not tailored to sustain convection-enhanced electrochemical reactions. Thus, there is a need for electrode optimization to enhance the system performance. In this work, we present an optimization framework to carry out the bottom-up design of porous electrodes by coupling a genetic algorithm with a pore network modeling framework. We introduce geometrical versatility by adding a pore merging and splitting function, study the impact of various optimization parameters, geometrical definitions, and objective functions, and incorporate conventional electrode and flow field designs. Moreover, we show the need for optimizing geometries for specific reactor architectures and operating conditions to design next-generation electrodes, by analyzing the genetic algorithm optimization for initial starting geometries with diverse morphologies (cubic and a tomography-extracted commercial electrode), flow field designs (flow-through and interdigitated), and redox chemistries (VO2+/VO2+ and TEMPO/TEMPO+). We found that for kinetically sluggish electrolytes with high ionic conductivity, electrodes with numerous small pores and high internal surface area provide enhanced performance, whereas for kinetically facile electrolytes with low ionic conductivity, low through-plane tortuosity and high hydraulic conductance are desired. The computational tool developed in this work can further expanded to the design of high-performance electrode materials for a broad range of operating conditions, electrolyte chemistries, reactor designs, and electrochemical technologies.

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多孔电极设计的多功能优化框架
多孔电极是氧化还原液流电池等电化学装置中决定性能的部件,因为它们控制着反应器的电化学性能和泵送要求。然而,氧化还原液流电池中使用的传统多孔电极并不适合维持对流增强型电化学反应。因此,有必要对电极进行优化,以提高系统性能。在这项工作中,我们提出了一个优化框架,通过将遗传算法与孔隙网络建模框架相结合,对多孔电极进行自下而上的设计。我们通过添加孔隙合并和分裂功能引入了几何多功能性,研究了各种优化参数、几何定义和目标函数的影响,并结合了具有明确几何定义的电极结构和流场。此外,我们还通过分析具有不同形态(立方体和断层扫描提取的商用电极)、流场设计(流经式和交错式)和氧化还原化学(VO2+/VO2+ 和 TEMPO/TEMPO+)的初始几何形状的遗传算法优化,说明了针对特定反应器结构和操作条件优化电极以设计下一代电极的必要性。我们发现,对于具有高离子电导率的动力迟钝型电解质,具有大量小孔和高内表面积的电极可提高其性能;而对于具有低离子电导率的动力促进型电解质,则需要低通透面曲折度和高水力传导。本研究开发的计算工具可指导高性能电极材料的设计,适用于各种操作条件、电解质化学成分、反应器设计和电化学技术。
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