Multiphysics modeling of metal surface cleaning using atmospheric pressure plasma

Abstract

An atmospheric pressure plasma (APP) system offers advanced, cost-effective processing routes for surface cleaning without a vacuum chamber. The appeal of APP systems in surface cleaning, however, is reduced by lack of a predictive link among the processing parameters, surface-plasma reactions, and plasma chemistry responsible for efficient removal. Here, we present a comprehensive multiphysics model of surface cleaning using a microwave assisted atmospheric plasma system as an alternative to chemical cleaning of surfaces. This model can quantitatively predict the processing time for the removal of the contaminant species from the surface. The presented model investigates the dependencies of removal rates and the nature of the contaminant species on the processing parameters. We demonstrate these dependencies by using polypropylene as a model hydrocarbon impurity. The complex and cooperative effects of microwave power, gas flow rate, torch-substrate distance, and tilt angle have been explored for understanding factors behind efficient cleaning. Our results show that the rate of hydrocarbon degradation is highly dependent on gas temperatures over the surface, flow pattern, and torch-substrate distance and depends less on the angle of attack. This study helps to optimize the values for operational parameters of atmospheric plasma processing that speeds up the experiments toward achieving a higher surface cleaning rate.