材料科学
色散(光学)
分散性
复合材料
像素
聚合物
粒子(生态学)
环氧树脂
纳米复合材料
基质(化学分析)
光学显微镜
粒径
扫描电子显微镜
光学
人工智能
高分子化学
计算机科学
化学工程
工程类
地质学
物理
海洋学
作者
Mostafa Yourdkhani,Pascal Hubert
摘要
The state of dispersion plays an important role on the performance of polymer nanocomposites. Dispersion is usually assessed based on the qualitative evaluation of microscopy micrographs. In this paper, a quantitative algorithm is introduced for analyzing the dispersion of inclusions in polymer composites using image analysis. In a binary image, on-pixels are considered as particle elements while off-pixels stand for matrix elements. To quantify the dispersion, the mean distance value between any matrix elements to their corresponding nearest neighboring particle element is measured. A dispersion index, DI, is then defined by comparing the image of interest with the associated uniformly dispersed case. Synthetic models were utilized to examine the sensitivity of the algorithm to various dispersity scenarios such as the effect of particle size, clustering, and cluster distribution. Optical micrographs of carbon nanotube modified epoxy with different states of dispersion were also employed to assess the applicability and functionality of the algorithm to real micrographs.
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