Bottom-up design of porous electrode by combining a genetic algorithm and a pore network model

28 September 2022, Version 2
This content is a preprint and has not undergone peer review at the time of posting.


The microstructure of porous electrodes determines multiple performance-defining properties, such as the available reactive surface area, mass transfer rates, and hydraulic resistance. Thus, optimizing the electrode architecture is a powerful approach to enhance the performance and cost-competitiveness of electrochemical technologies. To expand our current arsenal of electrode materials, we need to build predictive frameworks that can screen a large geometrical design space while being physically representative. Here, we present a novel approach for the optimization of porous electrode microstructures from the bottom-up that couples a genetic algorithm with a previously validated electrochemical pore network model. In this first demonstration, we focus on optimizing redox flow battery electrodes. The genetic algorithm manipulates the pore and throat size distributions of an artificially generated microstructure with fixed pore positions by selecting the best-performing networks, based on the hydraulic and electrochemical performance computed by the model. For the studied VO2+/VO2+ electrolyte, we find an increase in the fitness of 75% compared to the initial configuration by minimizing the pumping power and maximizing the electrochemical power of the system. The algorithm generates structures with improved fluid distribution through the formation of a bimodal pore size distribution containing preferential longitudinal flow pathways, resulting in a decrease of 73% for the required pumping power. Furthermore, the optimization yielded an 47% increase in surface area resulting in an electrochemical performance improvement of 42%. Our results show the potential of using genetic algorithms combined with pore network models to optimize porous electrode microstructures for a wide range of electrolyte composition and operation conditions.


genetic algorithm
pore network model
redox flow batteries
porous electrode microstructure
pore-scale modeling
electrochemical storage

Supplementary materials

Appendix - Bottom-up design of porous electrode by combining a genetic algorithm and a pore network model
In this document the appendix can be found which includes: the pore network model equations and boundary conditions, a network comparison with a commercial electrode, a pore sensitivity study, the experimental procedures to obtain the operating parameters, the pore surface area values for the reference network, a manufacturability section, the parametric evaluation plots including the fitness, electrical power, pumping power, pore size distribution, polarization curves, pore and throat diameters, and pore surface area values for all systems tested, parameter evolution tables with the absolute and relative improvements of the systems, and the equation for the relative increase of the surface area at the electrode-membrane interface.


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