Ultra-hydrophobicity through stochastic surface roughness

The self-cleaning properties of ultra-hydrophobic surfaces are of great interest for technological applications. Specific surface roughness, essential for the dewetting effect, is not necessarily based on deterministic lotus leaf structures. Ultra-hydrophobicity also occurs on a large variety of stochastic, e. g., self-organized, roughness structures, which offers prospects for cost-effective manufacturing techniques (e.g., thin film deposition). This work addresses the development of roughness design algorithms, which deliver application-focused structural parameters, required for efficient and targeted manufacturing processes. Our approach is based on the assessment of wetting-relevant surface structures by a specific roughness analysis using power spectral density functions. The resulting quantitative roughness criterion, a 'wetting parameter', enables the prediction of ultra-hydrophobicity for design purpose as well as for an efficient control and adoption of the manufacturing process. The reliability of this method is demonstrated for a variety of surfaces for engineering and optical applications. For optical applications, the roughness design takes into account both wetting properties and optical quality (light scattering). Optical coatings manufactured according to the design specifications yielded low-scattering, ultra-hydrophobic surfaces.