Abstract Atmospheric pressure plasma (APP) is an emerging technology for surface modification and depositing plasma coating without a vacuum chamber in ambient air to improve corrosion protection and paint adhesion for aerospace and energy applications. Current atmospheric plasma-based platforms lack the ability to control the surface chemistry of the coating for diverse operating environments. Here, we develop a predictive multiphysics model of protective layer deposition using microwave-assisted atmospheric plasma system. We connect this model to the detailed gas-phase and surface-plasma chemistry to predict and optimize the effective operational parameters to link the nature of growth of the oxide film on the substrate. The proposed modeling approach systematically identifies, couples, and characterizes multiple chemical and physical phenomena under a modular framework. This multiphysics model quantitatively correlates the growth of oxide film to the surface chemistry during the deposition process, which is very challenging to determine from experiments. The modeling approach also includes a modified organosilicon evaporation model to calculate evaporation rates of a precursor, tetraethyl orthosilicate (TEOS). We have assessed the presented model based on the results obtained from experiments. The dependencies of the growth rate of the film on the processing parameters were investigated to understand factors behind the efficient APP deposition. The results show that growth rates strongly depend on gas temperatures over the surface, flow patterns, and torch-substrate distance, and depend less on the angle of attack. Finally, for large area applications, the movement of the torch and impact on coating uniformity have been modeled using the detailed multiphysics simulation.

中文翻译：

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使用多物理场建模方法了解大气压等离子体中二氧化硅的动力学生长环境

摘要 大气压等离子体 (APP) 是一种新兴技术，用于表面改性和在环境空气中无需真空室即可沉积等离子体涂层，以提高航空航天和能源应用的防腐蚀和油漆附着力。当前基于大气等离子体的平台缺乏针对不同操作环境控制涂层表面化学的能力。在这里，我们使用微波辅助大气等离子体系统开发了保护层沉积的预测多物理场模型。我们将此模型与详细的气相和表面等离子体化学联系起来，以预测和优化有效的操作参数，从而将衬底上氧化膜的生长性质联系起来。提议的建模方法系统地识别、耦合、并在模块化框架下表征多种化学和物理现象。这种多物理场模型定量地将沉积过程中氧化膜的生长与表面化学相关联，这对于从实验中确定是非常具有挑战性的。建模方法还包括改进的有机硅蒸发模型，用于计算前体原硅酸四乙酯 (TEOS) 的蒸发速率。我们已经根据实验获得的结果评估了所提出的模型。研究了薄膜生长速率对加工参数的依赖性，以了解有效 APP 沉积背后的因素。结果表明，生长速率很大程度上取决于表面上的气体温度、流动模式和焊炬与基板的距离，而对攻角的依赖性较小。最后，