Numerical modeling and experimental validation of passive microfluidic mixer designs for biological applications

The present work reports numerical simulation and experimental validation of novel designs of microfluidic mixers that can be employed for biological mixing applications. Numerical simulations involving various geometrical models were performed for design optimization. The effect of the presence of embedded obstacles was studied in detail, in order to understand the effect of channel occlusion on micromixing. The mixing performance of various channel designs was compared, and crossover in the mixing performance of the designs was observed in response to a change in the flow Reynolds number (Re). The improvement in micromixing efficiency was discussed in connection with the variations in local values of the Reynolds number and Dean number. It was observed that the presence of obstacles contributes to a significant increase in local Re in the vicinity of sharp-edged obstacles, thereby enhancing the efficiency of mixing. In addition, the local Dean number is observed to increase significantly inside spiral microfluidic designs. We validate the optimized microfluidic mixer designs by performing micromixing experiments and image analysis based on regions of interest along the length of the channels. Numerical predictions were observed to be in reasonable agreement with experimental results. Finally, we demonstrated the biological applicability of an optimized micromixer design for on-chip detection of calcium levels in blood serum. The passive mixing designs presented in this work are useful for chip-scale implementations of cell-drug biology, where some of the key cell signaling processes appear at second time scales.