CFD-based optimization of a high-throughput recycle micromixer

The present paper uses computational fluid dynamics (CFD) and the response surface method (RSM) to optimize the performance of a novel high-throughput recycle micromixer. The micromixing of DI water and blood plasma with various thermophysical properties is simulated for a broad range of DI water Reynolds numbers (50 < ReDI DI <400). The impacts of geometrical parameters and ReDI DI are assessed on the mixing index (MI) and pressure drop (zp). z p). It is found that the chaotic advection can be enhanced by changing effective parameters due to the recirculating flow in feedback channels and vortex generation in mixing chambers. Accordingly, the channel depth has a major effect on MI and z p in such a way that when the channel depth changes from 50 to 1000 mu m, MI is augmented from 23 % to 73.25 % and z p is reduced from 75.171 kPa to 12.85 kPa when ReDI DI = 400. It is revealed that MI is an enhancing function of ReDI DI and the number of mixing units. Besides, the figure-of-merit (FoM) analysis shows that the proposed micromixer gives a much greater FoM compared to the micromixers with ordered flow patterns when Re is an order of 50. The RSM provides two mathematical correlations for MI and z p to obtain an optimal recycle micromixer that can be efficiently utilized in biological and clinical applications.