Microfluidic droplet trapping, splitting and merging with feedback controls and state space modelling.

Abstract

We combine image processing and feedback controls to regulate droplet movements. A general modelling approach is provided to describe droplet motion in a pressure-driven microfluidic channel network. A state space model is derived from electric circuit analogy and validated with experimental data. We then design simple decentralized controllers to stabilize droplet movement. The controllers can trap droplets at requested locations by fine tuning inlet pressures constantly. Finally, we demonstrate the ability to split and merge the same droplet repeatedly in a simple T-junction. No embedded electrodes are required, and this technique can be implemented solely with a camera, a personal computer, and commercially available E/P transducers.