A numerical investigation of droplet bouncing behaviors on the superhydrophobic surfaces with different micro-structures. (March 2023)

• Record Type: Journal Article
• Authors: Lu, Sirui; Lu, Hao; Hu, Lina; Wang, Xiaojian
• Is Part Of: Case studies in thermal engineering. Volume 43(2023)
• Publication Date: 2023-03
• Subjects: Droplet bouncing -- Micro-structures -- Superhydrophobic surface -- Lattice Boltzmann method; Heat engineering -- Case studies -- Periodicals; 621.40205
• DOI: 10.1016/j.csite.2023.102728
• Languages: English
• ISSNs: 2214-157X

Abstract

Abstract: Better understanding of the droplet bouncing behaviors and microscopic mechanisms on superhydrophobic surfaces is of significance for a large number of energy applications. In this study, the bouncing process of droplets on superhydrophobic surfaces was investigated by lattice Boltzmann method (LBM). Four types of micro-structures for superhydrophobic surface were investigated: perfectly smooth surface, perfectly regular surface, randomly regular surface, and randomly rough surface. Random rough surfaces were described by skewness (−0.9 to 0.9), kurtosis (1.0–5.0) and standard deviation (0.3–1.1). The basic morphology and roughness parameters of the randomly rough surfaces were obtained by atomic force microscopy (AFM) and was developed by numerical reconstruction method. After the experimental verification, the droplet bouncing characteristics on the superhydrophobic surface with different micro-structures are compared and summarized. The maximum spreading length, the contact time and post-bounce morphology of droplet bouncing process are analyzed. It was found that the maximum spreading length of the droplet is reduced with the increasing of surface skewness, kurtosis and standard deviation. In the random regular surface, the increase of parameters from minimum to maximum reduced the maximum spreading length by 8.22%. The total contact time increased by 16.61%. When the number of surface sharp edges are smaller or the groove-like structures are wider, the contact time of droplet bouncing process can be obviously reduces. The droplet has the best bouncing performance on superhydrophobic surface that satisfy a skewness of 0.3–0.5, kurtosis of 3.0 and standard deviation of 0.7–0.9. The dynamic processes study of the droplets on surfaces with four gradations of roughness has not been done before. The gradual roughness can reflect the change process from theoretical superhydrophobic surfaces to practically prepared superhydrophobic surfaces with droplet bouncing. We have discovered a new law of droplet bouncing from progressively more complex surface microstructures. The main contribution of this work is to give simulation data of droplet bouncing on four surfaces simultaneously. The most suitable surfaces for bouncing are compared and conclusions are drawn. The influence of different surface micro-structures on the droplet bouncing behaviors obtained in this paper may be useful for the optimal design of superhydrophobic surface.