Model-based feedback control for on-demand droplet dispensing system with precise real-time phase imaging

Recent years have witnessed the advances of droplet-based microfluidics as a powerful tool for high-throughput assays in biology, chemistry, material and environmental sciences. Precise and effective droplet generation is critical for the practical applications of droplet-based microfluidics. Although many passive and active droplet generation methods have been proposed and demonstrated, there are still challenges towards the implementa-tion of droplet-on-demand in terms of system complexity, precision and robustness. In this work, we propose and demonstrate a dual-pressure-pulse (DPP) driven droplet generation method incorporated with model-based feedback control to achieve on-demand droplet generation. Based on the study of droplet formation dynamics in a flow-focusing configuration using real-time quantitative phase imaging (QPI) technique, we validate the proposed dual-pressure-pulse (DPP) driven droplet generation concept, for which the physical model of droplet formation can be greatly simplified. With this approach, model-based feedback control can be implemented for DPP actuation to achieve on-demand droplet generation with relatively high system response and low steady-state error.