Partial least squares regression as a tool to predict fluoropolymer surface modification by dielectric barrier discharge in a corona process configuration in a nitrogen-organic gaseous precursor environment

Abstract

A dielectric barrier discharge in a corona process configuration is used to treat the surface of fluoropolymers in a nitrogen−organic precursor environment. The surface chemistry, thickness, and water contact angle of the deposited coatings are measured and used to build up an output matrix to be correlated with an input matrix built using electrical parameters of the discharge, the gas mixture chemical composition, and spectroscopic parameters measured in both the infrared and ultraviolet−visible emission spectral regions. A partial least-squares regression (PLSR) model enables determining the most important plasma parameters to drive the coating physicochemical characteristics. From the PLSR model, it is determined that the plasma electrical parameters drive the surface modification process, at the expense of other plasma characteristics such as gas flow, gaseous precursor concentration, nitrogen vibrational temperature, and the level of gaseous precursor conversion within the plasma