Chen Xuemei, Patel Ravi S, Weibel Justin A, Garimella Suresh V
School of Mechanical Engineering and Birck Nanotechnology Center, Purdue University, West Lafayette, Indiana, 47907-2088, USA.
Sci Rep. 2016 Jan 4;6:18649. doi: 10.1038/srep18649.
Coalescence-induced jumping of condensate droplets from a superhydrophobic surface with hierarchical micro/nanoscale roughness is quantitatively characterized. Experimental observations show that the condensate droplet jumping is induced by coalescence of multiple droplets of different sizes, and that the coalesced droplet trajectories typically deviate from the surface normal. A depth-from-defocus image processing technique is developed to track the out-of-plane displacement of the jumping droplets, so as to accurately measure the droplet size and velocity. The results demonstrate that the highest jumping velocity is achieved when two droplets coalesce. The jumping velocity decreases gradually with an increase in the number of coalescing droplets, despite the greater potential surface energy released upon coalescence. A general theoretical model that accounts for viscous dissipation, surface adhesion, line tension, the initial droplet wetting states, and the number and sizes of the coalescing droplets is developed to explain the trends of droplet jumping velocity observed in the experiments.
对具有分级微/纳米尺度粗糙度的超疏水表面上凝聚液滴因聚并引发的跳跃进行了定量表征。实验观察表明，凝聚液滴的跳跃是由不同尺寸的多个液滴聚并引起的，并且聚并后的液滴轨迹通常偏离表面法线方向。开发了一种离焦深度图像处理技术来跟踪跳跃液滴的面外位移，以便准确测量液滴尺寸和速度。结果表明，当两个液滴聚并时可实现最高跳跃速度。尽管聚并时释放出更大的潜在表面能，但随着聚并液滴数量的增加，跳跃速度逐渐降低。建立了一个综合考虑粘性耗散、表面粘附力、线张力、初始液滴润湿状态以及聚并液滴数量和尺寸的通用理论模型，以解释实验中观察到的液滴跳跃速度趋势。
