Journal
JOURNAL OF MICROMECHANICS AND MICROENGINEERING
Volume 24, Issue 7, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0960-1317/24/7/075004
Keywords
anisotropic wetting; droplet self-movement; micro-V-grooved surface; micro-characterized variable; micro-grinding
Categories
Funding
- National Natural Science Foundation of China [51075156]
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Micro-characterized variables are proposed to precisely characterize a micro-V-grooved Si surface through the 3D measured topography rather than the designed one. In this study, level and gradient micro-grooved surfaces with depth of 25-80 mu m were precisely and smoothly fabricated using a new micro-grinding process rather than laser machining and chemical etching. The objective is to investigate how these accurate micro-characterized variables systematically influence anisotropic wetting and droplet self-movement on such regular micro-structured surfaces without surface chemical modification. First, the anisotropic wetting, droplet sliding, pinning effect and droplet impact were experimentally investigated; then, theoretical anisotropic wetting models were constructed to predict and design the anisotropic wetting. The experiments show that the level micro-V-grooved surface produces the anisotropic wetting and pinning effects. It not only approximates superhydrophobicity but also produces high surface free energy. Moreover, the gradient micro-V-grooved surface with large pitch may lead to much easier droplet sliding than the level one along the micro-groove. The droplet self-movement trend increases with increasing the micro-groove gradient and micro-V-groove ratio. The micro-groove pitch and depth also influence the droplet impact. Theoretical analyses show that the wetting anisotropy and the droplet anisotropy both reach their largest value and disappear for a sharp micro-groove top when the micro-V-groove ratio is equal to 0.70 and 2.58, respectively, which may change the wetting between the composite state and the non-composite state. It is confirmed that the wetting behavior may be designed and predicted by the accurate micro-characterized variables of a regular micro-structured surface.
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