期刊
OPTICS AND LASER TECHNOLOGY
卷 171, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.optlastec.2023.110318
关键词
Magnesium; Laser patterning; Polypropylene coating; Wetting model; Hierarchical roughness
A superhydrophobic coating was manufactured on laser-patterned magnesium surfaces. The effect of polypropylene concentration, laser power, distance, and angle on the coating's properties were investigated. SEM images confirmed the hierarchical roughness of the samples, which correlated with the measured contact angles. Models considering air trapping and spattered melt as rough surfaces provided the most accurate predictions.
A superhydrophobic coating was manufactured on laser-patterned magnesium surfaces. The surface morphology was studied using scanning electron microscopy (SEM). The effect of polypropylene (PP) concentration in the coating solution on the samples' morphology and contact angles (CA) was also investigated. Coating the samples with 20 g/L PP solution led to the filling of laser patterns by PP and, consequently, lower CA. The average CA for samples patterned with a 50 Watts laser was 146.8 degrees, which is slightly larger than those patterned with a 30 Watts laser, 145.8 degrees. Decreasing the concentration of PP coating solution to 15 g/L increases the average CA of about 5 degrees. The hierarchical roughness of these samples is revealed by SEM images which justified the CA measurement results. The roughness is due to both laser patterns, melt spatters, and the granule structure of PP. The effect of laser power, distance, and angle between laser lines (alpha) on CA was studied. Twelve samples are superhydrophobic in this condition. The largest CA is 156.7 degrees for the sample with a pitch-to-pitch distance of 100 mu m with alpha = 45 degrees and a laser power of 30 W. The critical parameters were further investigated by applying four different models. The models were based on diamond-like elements of laser patterns. Two models assume the air trapping in the grooves and unaffected areas and show the best agreement with the observed values. A more accurate prediction is made when the spattered melt is considered a rough surface.
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