Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62447
Title: Fabrication and characterization of Gecko-inspired dry adhesion, superhydrophobicity and wet self-cleaning surfaces
Authors: Zhang, Y
Qu, S
Cheng, X
Gao, X
Guo, X 
Keywords: Gecko-inspired microfiber polydimethylsiloxane surfaces
Surface properties
Counterface
Superhydrophobicity
Wet self-cleaning
Issue Date: 2016
Publisher: Elsevier
Source: Journal of bionic engineering, 2016, v. 13, no. 1, p. 132-142 How to cite?
Journal: Journal of bionic engineering 
Abstract: In this study, gecko-inspired polydimethylsiloxane (PDMS) microfiber surfaces were fabricated by combining Inductively Coupled Plasma (ICP) and micro-mold casting. The effect of roughness and surface energy of counterface on the adhesion of gecko-inspired microfiber surfaces and its superhydrophobicity and wet self-cleaning were studied. The adhesion of gecko-inspired microfiber surfaces depended on the roughness of the counterfaces due to the influences of contact area and interlocking mechanism. SEM images of interfaces between counterfaces with different roughness and gecko-inspired microfiber surfaces revealed the matched and dis-matched contact directly. The gecko-inspired microfiber surface got the larger adhesive force from the higher surface energy counterface, which is consisted with Johnson-Kendall-Roberts (SKR) theory. The smaller dimension and lower duty ratio of microfibers on PDMS resulted in the increasing of Water Contact Angle (WCA) and the decreasing of Sliding Angle (SA) compared to those of smooth PDMS. Particularly, sample P-8-28-20 had the biggest WCA (155) and SA (7), which displayed the superhydrophobicity and the best wet self-cleaning efficiency in all samples. The present studies showed that the roughness and surface energy of counterface both affected the adhesion of gecko-inspired microfiber surfaces. The smaller dimension and lower duty ratio of microfibers on PDMS endowed it with the superhydrophobicity and the wet self-cleaning abilities.
URI: http://hdl.handle.net/10397/62447
ISSN: 1672-6529
DOI: 10.1016/S1672-6529(14)60167-0
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