Optimization strategy for the velocity distribution based on tool influence function non-linearity in atmospheric pressure plasma processing

Abstract

Atmospheric pressure plasma processing (APPP) is proved to be potential in the fabrication of optical elements with high efficiency and near-zero damage. However, high convergence rate in the figuring process is hard to achieve because of the tool influence function (TIF) non-linearity. Directly solved dwell time map by conventional deconvolution methods does not consider the non-linear thermal effect, which leads to significant figuring error. In this paper, the optimization strategy for TIF non-linearity based on the velocity distribution in APPP is presented. The exponential model of TIF with non-linearity is established by trench experiments. A series of simulations are also conducted to analyze the thermal effect of non-linearity on the figuring process, indicating the TIF constantly changes with velocity distribution. Two evaluation parameters, relative balance factor and velocity concentration factor, are proposed to investigate the figuring capacity of calculated velocity distribution. With two evaluation parameters, the optimization strategy of velocity distribution based on TIF selection is proposed to suppress the non-linearity. Verification experiments are carried out to validate the two optimized TIFs. The results show that high convergence is achieved to be 72.41% and 82.81% for root-mean-square value respectively, which proves the feasibility of the proposed optimization strategy.