The Role of Roughness in Random Superhydrophobic Surfaces

Abstract

To investigate the role of roughness in superhydrophobic coatings a variety of superhydrophobic and non-superhydrophobic surfaces were synthesized using various polymer binders, nanosilica particles and fluoro chemistry on both glass and polycarbonate substrates. The roughness of the coatings was measured by profilometry and atomic force microscopy (AFM) and analyzed by a variety of statistical methods. Superhydrophobic surfaces showed a peak to peak distance below 5 microns and a radius of less than 0.5 micron, but this information alone was insufficient to predict superhydrophobicity. The skewness and kurtosis for the surfaces indicated that all coated samples, both superhydrophobic and non-superhydrophobic, had a random Gaussian roughness distribution, but there was no significant difference in the skewness and kurtosis values for either superhydrophobic or non-superhydrophobic surfaces. The power spectral density function (PSDF) was found to be an effective tool to predict the required roughness for superhydrophobicity and provides information over the entire range of length scales. The average peak radius for the micro and nano scales calculated from ACL and RMS values were found to be less than 3 µm and 520 nm, respectively, which supports the accepted theory is that superhydrophobic surfaces require tightly packed asperities and small micron and nano roughness. The characterization of the surfaces allowed experimental verification of theoretical models for the roughness factor and critical roughness parameters. It was found that the RMS/ACL values should be 0.35 or higher for designing surfaces with contact angles above 150°. This work shows a unique method for measuring, quantifying, and understanding the role of roughness, that can be used to design surfaces for superhydrophobicity and future applications such as self-cleaning, icephobicity, anti-biofouling, corrosion resistance, and water repellency.