Image-based closed-loop feedback for highly mono-dispersed microdroplet production

Abstract Micron-scale droplets isolated by an immiscible liquid can provide miniaturised reaction vessels which can be manipulated in microfluidic networks, and has seen a rapid growth in development. In many experiments, the precise volume of these microdroplets is a critical parameter which can be influenced by many external factors. In this work, we demonstrate the combination of imaging-based feedback and pressure driven pumping to accurately control the size of microdroplets produced in a microfluidic device. The use of fast-response, pressure-driving pumps allows the microfluidic flow to be quickly and accurately changed, while directly measuring the droplet size allows the user to define the more meaningful parameters of droplet size and generation frequency rather than flow rates or pressures. The feedback loop enables the drift correction of pressure based pumps, and leads to a large increase in the mono-dispersity of the droplets produced over long periods. We also show how this can be extended to control multiple liquid flows, allowing the frequency of droplet formation or the average concentration of living cells per droplet to be controlled and kept constant