Coalescing drops in microfluidic parking networks: A multifunctional platform for drop-based microfluidics

Multiwell plate and pipette systems have revolutionized modern biological analysis; however, they have disadvantages because testing in the submicroliter range is challenging, and increasing the number of samples is expensive. We propose a new microfluidic methodology that delivers the functionality of multiwell plates and pipettes at the nanoliter scale by utilizing drop coalescence and confinement-guided breakup in microfluidic parking networks (MPNs). Highly monodisperse arrays of drops obtained using a hydrodynamic self-rectification process are parked at prescribed locations in the device, and our method allows subsequent drop manipulations such as fine-gradation dilutions, reactant addition, and fluid replacement while retaining microparticles contained in the sample. Our devices operate in a quasistatic regime where drop shapes are determined primarily by the channel geometry. Thus, the behavior of parked drops is insensitive to flow conditions. This insensitivity enables highly parallelized manipulation of drop arrays of different composition, without a need for fine-tuning the flow conditions and other system parameters. We also find that drop coalescence can be switched off above a critical capillary number, enabling individual addressability of drops in complex MPNs. The platform demonstrated here is a promising candidate for conducting multistep biological assays in a highly multiplexed manner, using thousands of submicroliter samples.     

Behavior of a train of droplets in a fluidic network with hydrodynamic traps

The behavior of a droplet train in a microfluidic network with hydrodynamic traps in which the hydrodynamic resistive properties of the network are varied is investigated. The flow resistance of the network and the individual droplets guide the movement of droplets in the network. In general, the flow behavior transitions from the droplets being immobilized in the hydrodynamic traps at low flow rates to breaking up and squeezing of the droplets at higher flow rates. A state diagram characterizing these dynamics is presented. A simple hydrodynamic circuit model that treats droplets as fluidic resistors is discussed, which predicts the experimentally observed flow rates for droplet trapping in the network. This study should enable the rational design of microfuidic devices for passive storage of nanoliter-scale drops.