The EUV mask is protected from particle contamination during exposure by the EUV pellicle, which is constructed from a membrane that is not attached to anything. The pellicle, which is made up of carbon nanotube (CNT) films, has excellent EUV transmission, low reflectivity, and mechanical durability. To evaluate the quality and dependability of the CNT pellicle for the purpose of optimizing the manufacturing process, porosity, bundle size, and particle size distribution are measured utilizing TEM or SEM images and specialized image processing techniques. This article presents a methodology that is specifically designed for processing TEM or SEM images of CNT membranes. Our methodology employs an auto-binarized technique to accurately determine the edge contour from images, and subsequently extract the distribution of each indicator through length or area calculations along the edge. The accuracy of our methodology has been verified through testing using a set of binarized standard reference images. Additionally, we evaluated the practical application of our methodology by comparing CNT membranes with different treatments to determine its sensitivity. We further demonstrated the feasibility of our method by comparing CNT membranes that have undergone varying degrees of hydrogen plasma treatment to the existing Raman D-band to G-band intensity ratio (D/G ratio).
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