Residence time distribution analysis of magnetic nanoparticle-enhanced mixing using time-dependent magnetic actuation in microfluidic system

The dynamics of an innovative time-dependent magnetic nanoparticle (MNP)-based mixing strategy is demonstrated in this study using a multiphysics finite element model. Residence time distribution (RTD) analysis, for the first time, is successfully applied to predict the performance as well as investigate and optimize a wide range of design parameters used in the magnetically actuated mixing process. Orientation of electrodes as well as the direction of current to produce desirable magnetic field are found to play a major role on mixing performance. It is also found that a two-electrode system with an optimized current can be as effective as a four-electrode system. For effective mixing, an optimum switching frequency of current supplied to electrodes is predicted. Effect of MNP size, flow condition on mixing performance is also studied using RTD analysis and optimized values are predicted. Overall, the developed “numerical prototype” in conjunction with RTD analysis demonstrates that time-dependent magnetic actuation can be effectively used to mix or tag MNPs with biomolecules in situ for further processing and the numerical model can be used as a predictive tool in the design and optimization of mixing strategy for developing efficient lab-on-a-chip systems.