Tuning and predicting the wetting of nanoengineered material surface

Abstract

The wetting of a material can be tuned by changing the roughness on its surface. Recent advances in the field of nanotechnology open exciting opportunities to control macroscopic wetting behaviour. Yet, the benchmark theories used to describe the wettability of macroscopically rough surfaces fail to fully describe the wetting behaviour of systems with topographical features at the nanoscale. To shed light on the events occurring at the nanoscale we have utilised model gradient substrata where surface nanotopography was tailored in a controlled and robust manner. The intrinsic wettability of the coatings was varied from hydrophilic to hydrophobic. The measured water contact angle could not be described by the classical theories. We developed an empirical model that effectively captures the experimental data, and further enables us to predict the wetting of surfaces with nanoscale roughness by considering the physical and chemical properties of the material. The fundamental insights presented here are important for the rational design of advanced materials having tailored surface nanotopography with predictable wettability.