Energy-Balance modeling of coalescence-induced droplet jumping on flat surfaces and slingshot structures

Abstract

The highly efficient coalescence-induced droplet jumping on surfaces has attracted significant interest due to its potential for heat transfer enhancement, self-cleaning, anti-ice/frosting, and directional liquid collection. However, existing velocity models fail to accurately predict experimental results, primarily due to overestimations of excess surface energy and kinetic energy, or underestimations of viscous dissipation. Moreover, no theoretical model has been developed to address slingshot structures until now. In this study, a universal predictive model with enhanced precision is established. This model not only predicts the jumping velocity for slingshot structures but is also applicable to flat surfaces and even surfaces with particles. Key energy terms have been refined by incorporating the actual droplet shape, calculating viscous dissipation separately for distinct dynamic stages, and introducing a novel approach to kinetic energy utilization. Additionally, it is pointed out that normalized texture height is the dominant geometry parameter for droplet jumping velocity enhancement. By comparing the prediction results with previous experiments, this model agrees well with the vast majority of data on flat and slingshot structures, and the relative errors are ∼ 13 %.