Droplet microfluidics: A study of traffic and mass transfer in two-phase microfluidic networks
Wang, William S.
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The field of droplet microfluidics makes it possible to generate lab-on-chip technologies that could significantly improve the way chemical, biological, and pharmaceutical analysis and screening are performed. We investigate two major droplet microfluidic unit operations: 1) the traffic of droplets through branching networks, and 2) the creation of gradients in concentration across static droplet arrays (SDAs). As an example of how modular millifluidic networks can be used as reliable tools for studying droplet traffic, we studied droplet traffic through a modular millifluidic bifurcated loop. We observed the same types of periodic and aperiodic behaviors previously reported with respect to microfluidic bifurcated loops. In addition, our own numerical simulations based on a simple network model for microfluidic droplet traffic were able to predict many of the experimentally observed periodic behaviors and behavioral transitions. We also identified three possible causes for intermittency between different periodic and/or aperiodic behaviors: 1) simultaneous entering and exiting events, 2) channel defects, and 3) equal or nearly equal hydrodynamic resistances in both branches. Concentration gradients across an SDA can be easily generated using a moving aqueous plug to dilute an array of initially equal-concentration trapped aqueous droplets. However, a deeper understanding of the phenomena affecting mass transfer in these networks is needed in order to better design SDA networks and control the dilution behaviors. We therefore developed a phenomenological model and performed numerical, particle-based simulations to evaluate the relative importance of each model element, including: 1) advection within the moving plug; 2) diffusion throughout all aqueous phases; 3) coalescence-induced advection (CIA); and 4) gutter-flow-induced advection (GFIA). GFIA significantly affects dilution rate and final concentration in certain conditions. Our simulations predicted—and we later confirmed with particle image velocimetry experiments—that the relative strength of GFIA varies nonlinearly with plug velocity, decreasing as plug velocity increases. Our analysis could help people predict the range of velocities in which GFIA increases dilution rate.