Optimal Design of Membraneless Microfluidic Fuel Cell with Double-Bridge Flow-Channel Cross-Section

In this study, design optimization was performed to improve the performance of a membraneless microfluidic fuel cell having a flow-channel with a double-bridge cross-section. By numerically calculating the governing equations, including the Navier-Stokes', mass-transport, and Butler-Volmer equations, electrochemical phenomena in the fuel cell were analyzed, and the performance of the fuel cell was evaluated. Additionally, an optimization was performed to maximize the peak power density (that is, the objective function) using a genetic algorithm combined with a surrogate model based on a radial-based neural network. Bridge height, inner channel width, and outer channel width were selected as design variables for optimization. Resultantly, an increase in the bridge height and the inner channel width, and a decrease in the outer channel width, effectively increased the peak power density. Furthermore, the optimal shape demonstrated peak power density, which was 252% higher than that of the reference shape.

Automated summary

In this study, design optimization was performed to improve the performance of a membraneless microfluidic fuel cell. The optimal shape demonstrated a peak power density that was 252% higher than that of the reference shape.