LAUSR

This study investigates the stochastic variation in droplet size generated within a microfluidic flow-focusing cross-junction. A commercial micro cross-junction was used to experimentally analyze droplet formation under fixed flow rate conditions. An in-house machine learning-based algorithm was developed to automatically detect and measure droplet dimensions from high-speed video recordings. Despite constant flow rates, the analysis revealed fluctuations in droplet size, attributed to velocity oscillations induced by syringe pumps. To explore this phenomenon, micro-Particle Image Velocimetry (micro-PIV) was employed to capture velocity profiles, which were then used to define time-dependent boundary conditions for numerical simulations. Simulations were conducted using the OpenFOAM solver interFoam and validated against experimental data. The results demonstrate good agreement and confirm that velocity fluctuations significantly influence droplet formation. This combined experimental and numerical approach provides an innovative, robust framework for understanding and predicting droplet behavior in microfluidic systems.