Enhancing the Hydrophilicity of Non-Woven Fabric Using Atmospheric Pressure Plasma Treatment Optimized by the Design of Experiments

Abstract

The parameters affecting the hydrophilicity and its aging effect on the polymer surface treated with atmospheric pressure plasma were investigated. A series of experimental procedures were performed according to various parameter combinations using the DoE method. The main factors having the most impact were found by quantifying the effect of each process parameter in plasma treatment. In addition, based on the results, multiple regression analysis was conducted to optimize the parameters of the experiment under conditions that maximize the hydrophilicity of the polymer surface. Finally, process capability analysis showed the superiority of optimized conditions statistically, physically, and chemically. A series of experiments and analytical procedures were characterized with the Minitab 20 program, X-ray photoelectron spectroscopy (XPS), and atomic force microscope (AFM).

Case study in machine learning for predicting moderate pressure plasma behavior

“…The least-square fit method of analyzing DOE data has been used successfully for many years to find the optimal parameter space for material processing. [27][28][29][30] Because ML predictor importance ranking is radically different from DOE p-value (logworth) ranking of the parameters, it seems unlikely that one will be able to use ML parameter relative importance ranking values to optimize processes. However, it is worth pointing out that neither DOE nor ML studies can produce an accurate ranking of the optimal parameter space for processing a wafer as neither is based on a physical model of the discharge.…”

“…For many years, researchers deploying plasma systems in the semiconductor industry made use of design of experiment (DOE) studies to ascertain control parameter regimes that would result in the effective processing of a wafer or other substrates. Specifically, DOE studies have been used to narrow in on the "correct parameters" needed in a large number of processes, including hydrophilicity of fabric, 27 gas utilization in semiconductor manufacturing, 28 wire bonding, 29 and many others. A basic review of DOEs and how they are used is given in the online NIST/SEMATECH handbook.…”