Visualization of evaporation-driven flow inside an evaporating sessile droplet by means of Micro-PIV

Abstract The present study aims to characterize the flow field during droplet evaporation. Evaporation-driven flow in a sessile droplet is experimentally visualized and analyzed using micro-particle image velocimetry (Micro-PIV). In the experiments, tracer-seeded sessile mixture droplets were allowed to evaporate on a substrate, while Micro-PIV captured the time-resolved internal velocity fields. To accelerate data processing for tracking droplet shape evolution, a deep-learning-assisted image analysis method was employed. The principles of hyperparameter optimization for applying Micro-PIV to sub-micron droplets are discussed to improve the accuracy of quantitative measurements. Visualization results for glycerol-water mixture droplets are presented and analyzed. The findings reveal the fundamental flow regimes: a recirculating bulk flow was observed throughout most of the evaporation period. In terms of quantitative measurements, the internal flow velocity initially increased, peaked at approximately mid-evaporation, and subsequently decreased as drying progressed. The combined Micro-PIV and deep learning approach provides a powerful methodology for efficiently acquiring experimental data and elucidating the dynamics of droplet evaporation.