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 convective-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 electrode structures and flow field with well-defined geometries. Moreover, we show the need for optimizing electrodes 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 required. The computational tool developed in this work can guide the design of high-performance electrode materials for a broad range of operating conditions, electrolyte chemistries, reactor designs, and electrochemical technologies.
Supplementary materials
Title
Appendix - A versatile optimization framework for porous electrode design
Description
In this appendix, the following topics are discussed in more detail than in the main manuscript: the network generation, the electrochemical algorithm, the results of the reference system and a visualization of the formation of the transport pathways, a sensitivity study on the optimization functions including the surface area definition, throat factor, electrode thickness, and fitness function, the results of the simulations for the merging and splitting study, the results of the network evolution study (including an artificially generated voronoi network), the results of the study on the influence of the flow field design, and the results of the study on the effect of the electrolyte chemistry.
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Supplementary weblinks
Title
GA-RFB-electrode repository
Description
The genetic algorithm developed in this work can be found in this repository.
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