Abstract A method to quantify the dispersion level of fillers in a polymer composite using optical microscopy and image processing is demonstrated. Optical microscope images of a graphene suspension were taken throughout an ultrasonication procedure. A mixing index was calculated for each image using a modified Shannon entropy analysis, demonstrating that the index can be used to optimize procedures for dispersing fillers in polymers. The flexibility of the Shannon entropy index is achieved through two user-defined variables based on physically meaningful features, allowing the analysis to be applicable to a wide range of filler size distributions. Calculating a mixing index allows for characterization beyond the typical categories of ‘highly’ and ‘poorly’ dispersed systems. An index can be calculated at various stages of composite processing allowing for robust statistical analysis of the dispersion level, using only a small sample volume. The adoption of this method would lead to quantitative characterization of dispersion level in polymer composites, deepening the understanding of how processing impacts composite properties, and aiding in the design of new composite materials.

中文翻译：

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使用改进的香农熵对混合进行定量评估

摘要 展示了一种使用光学显微镜和图像处理量化聚合物复合材料中填料分散水平的方法。在整个超声处理过程中拍摄石墨烯悬浮液的光学显微镜图像。使用改进的香农熵分析为每个图像计算了混合指数，表明该指数可用于优化将填料分散在聚合物中的程序。香农熵指数的灵活性是通过基于物理意义特征的两个用户定义变量实现的，使分析适用于广泛的填料尺寸分布。计算混合指数允许表征超出“高度”和“差”分散系统的典型类别。可以在复合处理的各个阶段计算指数，从而仅使用小样本量就可以对分散水平进行稳健的统计分析。采用这种方法将导致聚合物复合材料中分散水平的定量表征，加深对加工如何影响复合材料性能的理解，并有助于新复合材料的设计。