MOLECULAR DYNAMICS SIMULATION OF ENVIRONMENTAL FRIENDLY EASY-CLEAN COATINGS

Abstract

Easy-clean coating materials constitute a rapidly growing group of smart functional materials. Such coatings play a significant role in protecting solid surfaces from contamination, corrosion and wear, and reduce the usage of energy and water for cleaning, and thereby, minimize the pollution and waste caused by cleaning agents. Owing to such astounding performance, they cover an extensive and potential use in divergent easy-clean applications, including, but not limited to, automobile windshields, textiles, outdoor structural glasses, dust-free and self-clean coatings for solar cells, sensors, anti-biofouling, anti-icing, and in the oil and gas industry. Many surfaces in nature, such as lotus leaves, demonstrate superhydrophobic self-clean performance. Mimicking of its surface texture by scientists led to the development of artificial self-clean coatings. We may herein classify the two significant factors that impact the wettability of a surface: (i) its chemical composition and (ii) surface morphology. Researchers have investigated the phobic nature of different polymeric materials and found varying contact angles (CAs) recommending its dependence on surface texture or, more specifically, the surface roughness. Such surface morphology provides microscopic pockets for air, which are trapped in the surface beneath the water drops. So far, numerous techniques such as chemical vapor deposition and template methods involving the use of health-hazardous materials like poly(vinylidene fluoride) (PVDF), poly(tetrafluoroethylene) (PTFE), carbon nanotubes (CNT), etc., have been developed to achieve excellent self-clean effects. The wetting of smooth and rough surfaces is governed by Young, Wenzel, and Cassie– Baxter equations. In this direction, the role of molecular dynamics (MD) simulations in understanding structure-property relationships of yet un-synthesized polymers and to tailor their design to attain specific performance properties has been well established previously. Such computational tools are an aid to the researchers as they help to minimize the number of experiments and needed chemicals by providing optimized results without conducting exhaustive experiments, and consequently, give proficient utilization of resources as well as time. We employ this capability of MD simulations in this work to com