Abstract
Porous electrodes are ubiquitous to electrochemical technologies for energy conversion and storage, where they play a set of critical roles in the performance and cost of the systems. While progress on electrode design has been mostly driven by experimentation which is time- and resource-intensive, predictive design algorithms such as topology optimization have the potential to accelerate and guide the design of porous electrodes. By setting a performance target (e.g. maximizing electrochemical power output, reducing pumping power), the computational framework iterates mathematically over multiple electrode structures to satisfy the target, finding the optimal structure in a predictive manner. Here, we present a high-performance topology optimization framework, integrated with multi-physics computational models of transport processes, to design optimal porous electrodes in two- or three-dimensional space for use in electrochemical flow cells. We find that the algorithms computes electrode geometries that enhance the electrochemical and hydraulic performance by up to 29% and 98%, respectively. The resulting optimized designs were translated into cellular architectures using triply periodic minimal surface (TPMS) structures and fabricated using stereolithography 3D printing to demonstrate the manufacturability of the generated structures. We hope that such framework can inspire manufacturing of porous electrodes and the method can be extended to other electrochemical systems.
Supplementary materials
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Supporting information
Description
Additional results of mesh sensitivity analysis, pressure drop profiles, and more flow regimes.
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