A multi-scale modeling and simulation study to investigate the effect of roughness of a surface on its self-cleaning performance

Abstract

The importance of surface roughness on wettability is vital in developing novel techniques and materials for fabrication of self-cleaning coatings. In this study, the effect of varying roughness of a surface on its wettability was explored through changing the interspacing (a_i) and particle diameter (D) of ZnO agglomerated particles in poly(vinylacetate)-graft-poly(dimethylsiloxane) based coatings by constructing and simulating different atomistic and mesoscopic models. The surface roughness has been characterized in terms of roughness factor (R_q = D/a_i). Compared to the base matrix, a maximum enhancement in fluid phobicity was observed to be 33% and 172% against water and oil for R_q = 0.9. The surface energy increased moderately (∼21%) and interaction energy against an Al substrate significantly (∼1251%) by a 15 wt% filler incorporation. The investigation reveals that both a_i and filler concentration (thereby R_q) control imbibition of water/oil molecules by surface grooves to ensure limited wettability and useful self-cleaning ability. Specifically, optimal surface roughness is achieved at a critical R_q = 0.9 when the ZnO filler interspacing is neither too low for it to act as a continuous surface itself nor too high to allow easy penetration of fluid inside surface grooves.