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Updated: Aug 1, 2025

High Throughput Analysis of Liquid Droplet Impacts
Published on: March 6, 2020
Understanding hydrodynamic wear in self-similar superhydrophobic coatings subjected to rapid droplet impacts
Daniel J Braconnier1, Terence Davidovits2, Randall M Erb1
1Department of Mechanical and Industrial Engineering, Northeastern University 360 Huntington Avenue Boston MA 02115 USA r.erb@northeastern.edu.
Abstract:
Superhydrophobic materials rely on both chemical apolarity and surface roughness to achieve the high contact angles and the low roll-off angles that lead to self-cleaning and antibacterial properties. Current superhydrophobic coatings tend to be delicate and lose their properties easily when subjected to droplet impact. Such impact deteriorates these coatings through hydrodynamic wear; changing structure, eroding hydrophobic chemistry, and quickly leading to full wet out of the substrate. In fact, hydrodynamic wear is more detrimental to coatings than seemingly more aggressive mechanical wear including scratching with sandpaper - a common approach used to claim both self-similarity of a material and extreme robustness against wear. What makes certain coatings more robust against hydrodynamic wear? To understand this answer, we systematically study ten disparate self-similar superhydrophobic coating approaches from academia to industry by subjecting them to hydrodynamic wear with rapid droplet impacts. We offer an iteration of a spinning disk methodology that enables parallel testing of multiple coatings simultaneously. We have developed an analytical model that accurately estimates the average size and velocity of droplets created from the spinning disk. We find rapid droplet impacts that simulate a medium rain can deteriorate most coatings within seconds or minutes, with certain exceptions lasting up to 22 days. The more resilient coatings share common attributes including robust apolar chemistry, hierarchal topography, and a slow loss of sacrificial material. The best performing coatings can be characterized using power-law relationships that parallel mechanical fatigue functions and provide a predictive quantitative metric for the performance of hydrophobic coatings. Overall, this paper offers a quantitative approach to hydrodynamic wear of self-similar superhydrophobic coatings.
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