Integrated molecular dynamics and experimental approach to characterize low-free-energy perfluoro-decyl-acrylate (PFDA) coated silicon

Low-free-energy surfaces have attracted an intense academic and industrial interest over the last decade. A reduction of the surface free energy (SFE) has been found to enhance self-cleaning, hydrophobic, and non-fouling properties of surfaces, which are highly desirable in many industrial applications. However, tuning the surface chemistry and topography to achieve tailored low free energy surfaces has been found extremely challenging. In this work, we first show that an accurate refinement of the atmospheric plasma technique guarantees a polymeric coating near to the super-hydrophobic regime. Second, by coupling modelling and experimental measurements we suggest a reliable workflow for the surface characterization and smart design. Specifically, the case study proposed in this contest is capable of quantitatively distinguishing the contribution of a Perfluoro Decyl Acrylate (PFDA) coating, and hence decoupling the role of surface chemistry and roughness, in the reduction of the surface free energy of a bare silicon sample. Beyond the specific case study, our results also emphasize that a synergistic combination of models and experiments can unveil the optimal pathway for designing low-free-energy surfaces.