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.

中文翻译：

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使用大气压等离子体清洁金属表面的多物理场建模

常压等离子 (APP) 系统为无需真空室的表面清洁提供先进、经济高效的工艺路线。然而，由于缺乏处理参数、表面等离子体反应和负责有效去除的等离子体化学之间的预测联系，APP 系统在表面清洁中的吸引力降低。在这里，我们展示了使用微波辅助大气等离子体系统作为表面化学清洁的替代方法的表面清洁的综合多物理场模型。该模型可以定量预测从表面去除污染物的处理时间。所提出的模型研究了去除率和污染物种类的性质对处理参数的依赖性。我们通过使用聚丙烯作为模型烃杂质来证明这些依赖性。已经探索了微波功率、气体流速、火炬-基板距离和倾斜角的复杂协同效应，以了解有效清洁背后的因素。我们的结果表明，碳氢化合物的降解速率高度依赖于表面上的气体温度、流动模式和炬管与基材的距离，而对攻角的依赖较小。这项研究有助于优化大气等离子体处理的操作参数值，从而加快实验以实现更高的表面清洁率。我们的结果表明，碳氢化合物的降解速率高度依赖于表面上的气体温度、流动模式和炬管与基材的距离，而对攻角的依赖较小。这项研究有助于优化大气等离子体处理的操作参数值，从而加快实验以实现更高的表面清洁率。我们的结果表明，碳氢化合物的降解速率高度依赖于表面上的气体温度、流动模式和炬管与基材的距离，而对攻角的依赖较小。这项研究有助于优化大气等离子体处理的操作参数值，从而加快实验以实现更高的表面清洁率。