A Prediction Method of the Removal Function for Inductively Coupled Atmospheric Pressure Plasma Processing Based on Jet Morphology Monitoring and Diagnosis

Inductively coupled atmospheric pressure plasma processing (IC-APPP) is a promising technique of generating freeform surfaces of silicon-based optics. A constant removal function related to the plasma jet morphology is important for ensuring fabrication efficiency and accuracy. However, the removal function of IC-APPP is variable due to the instability of the plasma jet morphology, thereby the need for real-time re-acquisition through multiple pre-experiments. In this study, a prediction method for the removal function of IC-APPP based on jet morphology monitoring and diagnosis is proposed to simplify the acquisition process of the removal function. According to the basic model of the Gaussian-shaped removal function, the peak removal rate (A) and the full-width at half-maximum (FWHM) are fitted as the function of the scanning velocity and jet diagnosis indexes based on the set of experimental data. A specific calculation equation can be used to rapidly predict the removal function of the current plasma jet. The revised prediction model can address dynamic changes in the plasma jet morphology by correcting the removal functions in real time. The set of processing experiments with a variable jet morphology confirms that the predicted peak removal rate (A) and FWHM are always off by less than 10% and 6% from the actual results, respectively. We believe that this prediction method is suitable for any IC-APPP process requiring a quantification of the plasma jet morphology.