Chu Fuqiang, Yan Xiao, Miljkovic Nenad
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, People's Republic of China.
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.
Langmuir. 2022 Apr 12;38(14):4452-4460. doi: 10.1021/acs.langmuir.2c00373. Epub 2022 Mar 29.
Rapid shedding of microdroplets enhances the performance of self-cleaning, anti-icing, water-harvesting, and condensation heat-transfer surfaces. Coalescence-induced droplet jumping represents one of the most efficient microdroplet shedding approaches and is fundamentally limited by weak fluid-substrate dynamics, resulting in a departure velocity smaller than 0.3, where is the capillary-inertia-scaled droplet velocity. Laplace pressure-driven single-droplet jumping from rationally designed superhydrophobic grooves has been shown to break conventional capillary-inertia energy transfer paradigms by squeezing and launching single droplets independent of coalescence. However, this interesting droplet shedding mechanism remains poorly understood. Here, we investigate single-droplet jumping from superhydrophobic grooves by examining its dependence upon surface and droplet configurations. Using a volume of fluid (VOF) simulation framework benchmarked with optical visualizations, we verify the Laplace pressure contrast established within the groove-confined droplet that governs single-droplet jumping. An optimal departure velocity of 1.13 is achieved, well beyond what is currently available using condensation on homogeneous or hierarchical superhydrophobic structures. We further develop a jumping/non-jumping regime map in terms of surface wettability and initial droplet volume and demonstrate directional jumping under asymmetric confinement. Our work reveals key fluid-structure interactions required for the tuning of droplet jumping dynamics and guides the design of interfaces and materials for enhanced microdroplet shedding for a plethora of applications.
微滴的快速脱落提高了自清洁、防冰、集水和冷凝传热表面的性能。聚结诱导的液滴跳跃是最有效的微滴脱落方法之一，从根本上受到流体与基底间微弱动力学的限制，导致其脱离速度小于0.3，其中 是毛细管惯性尺度下的液滴速度。从合理设计的超疏水凹槽中由拉普拉斯压力驱动的单液滴跳跃已被证明能够打破传统的毛细管惯性能量传递模式，通过挤压和发射独立于聚结的单液滴来实现。然而，这种有趣的液滴脱落机制仍未得到很好的理解。在此，我们通过研究单液滴跳跃对表面和液滴构型的依赖性，来探究超疏水凹槽中的单液滴跳跃。使用基于光学可视化的流体体积（VOF）模拟框架，我们验证了在凹槽限制的液滴内建立的控制单液滴跳跃的拉普拉斯压力对比。实现了1.13的最佳脱离速度，远远超过目前在均匀或分级超疏水结构上利用冷凝所能达到的速度。我们进一步根据表面润湿性和初始液滴体积绘制了跳跃/非跳跃状态图，并展示了在非对称限制下的定向跳跃。我们的工作揭示了调节液滴跳跃动力学所需的关键流体-结构相互作用，并为众多应用中增强微滴脱落的界面和材料设计提供了指导。
