Shape parameter of Weibull size statistics is a potential indicator of filler geometry in SiO2 reinforced polymer composites

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2024-11-13 DOI:10.1016/j.physa.2024.130222

Huan Jin , Wenxun Sun , Xianan Qin

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Abstract

In a previous study [Physica A, 625 (2023), 129026], a relationship between the filler size distribution and the filler geometry of SiO₂ particle reinforced polymer composites has been reported. It has been experimentally demonstrated that the size of hollow and solid SiO₂ particles disperse in polymer matrix follows Weibull statistics with shape parameter at 2 and 3, respectively. This mechanism has not yet been verified in the one-dimensional (1D) case. In this paper, we study the length distribution of glass fibers in polymer composites. Our results show that the previous theory still holds for the 1D case. Thus, shape parameter of Weibull size statistics could be a potential indicator of filler geometry in SiO₂ reinforced polymer composites. This interesting mechanism can be explained by the scaling nature behind the Weibull statistics. Our study has thus shed new light on the evolution of filler geometry during the fabrication process of polymer composites, and should be useful for the related fields.

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魏布勒粒度统计的形状参数是衡量二氧化硅增强聚合物复合材料中填料几何形状的潜在指标

之前的一项研究[Physica A, 625 (2023), 129026]报道了二氧化硅颗粒增强聚合物复合材料的填料粒度分布与填料几何形状之间的关系。实验证明，分散在聚合物基体中的空心和实心 SiO2 粒子的尺寸遵循形状参数分别为 2 和 3 的 Weibull 统计。这一机制尚未在一维（1D）情况下得到验证。本文研究了聚合物复合材料中玻璃纤维的长度分布。结果表明，之前的理论在一维情况下仍然成立。因此，Weibull 尺寸统计的形状参数可以作为二氧化硅增强聚合物复合材料中填料几何形状的潜在指标。这一有趣的机制可以用 Weibull 统计背后的缩放性质来解释。因此，我们的研究为聚合物复合材料制造过程中填料几何形状的演变提供了新的启示，对相关领域应该有所帮助。

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来源期刊

Physica A: Statistical Mechanics and its Applications 物理-物理：综合

CiteScore

7.20

自引率

9.10%

发文量

852

审稿时长

6.6 months

期刊介绍： Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.