Automatic Characterization of Droplet Flow Regimes in Microfluidic T-Junctions Using Capacitive Sensing

Abstract

This letter presents the automatic characterization of droplet flow regimes in a microfluidic T-junction using capacitive sensing. Key properties of the generated droplets, such as velocity and length, are extracted via three embedded electrode pairs and used to classify the prevailing flow regime. The resulting flow type depends on the junction geometry, absolute velocities, and their ratio, and is visualized in a so-called capillary plot that fully describes the junction's operational behavior. Accurate prediction, detection, and classification of flow regimes in a given junction opens new possibilities for precise and flexible droplet generation, particularly in lab-on-a-chip applications.