Abstract
•A novel passive microfluidic fuel cell design with optimized electrode, rib, and channel structures is proposed.•Multi-factor structural modifications significantly reduce concentration and ohmic losses.•A 3D numerical model validated against experimental data confirms performance improvements.•Optimal design achieves a 15.56 % increase in current density and a 12.12 % increase in power density.
Passive microfluidic fuel cells, operated with methanol and air, are novel energy conversion devices, with low pollution, high portability, and relatively low cost, to debate the increasing energy demand and environmental concerns. During operation, the cell's structure plays a crucial role in determining the ohmic and concentration losses, which are closely related with the cell performance. In this study, a numerical model was developed to investigate the performance of a passive microfluidic fuel cell, focusing on variations in three structural components: electrodes, ribs, and flow channels. Our findings demonstrated that optimal designs in each category notably enhanced the cell performance. Specifically, compared to the base case without modification, using 6 trapezoidal electrodes increased the current and power densities by 20.62 mA cm−2 and 1.89 mW cm−2, respectively. Additionally, the employment of 3 triangular ribs enhanced the densities by 2.5 mA cm−2 and 0.35 mW cm−2, respectively. Furthermore, optimizing wave-shaped channels, with an amplitude of 0.5, a period of 3, and a phase of 0, resulted in increases of 3.55 mA cm−2 and 0.4 mW cm−2 in current and power densities, respectively. Finally, the optimization of three distinct structural categories was integrated and conducted using response surface methodology (RSM). This comprehensive optimization significantly reduced concentration and ohmic losses by decreasing ion transport resistance, thereby enhancing the overall cell performance. Under the optimal structural parameters, the microfluidic fuel cell achieved current and power densities of 52.44 mA cm−2 and 6.21 mW cm−2, respectively, which represent increases of 15.56 % and 12.12 % over those achieved with single-category optimization.
[Display omitted]