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用于模拟颗粒改性聚合物复合材料电学性能的随机有限元分析框架

Stochastic Finite Element Analysis Framework for Modelling Electrical Properties of Particle-Modified Polymer Composites.

作者信息

Ahmadi Moghaddam Hamidreza, Mertiny Pierre

机构信息

Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.

出版信息

Nanomaterials (Basel). 2020 Sep 5;10(9):1754. doi: 10.3390/nano10091754.

DOI:10.3390/nano10091754
PMID:32899564
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7559305/
Abstract

Properties such as low specific gravity and cost make polymers attractive for many engineering applications, yet their mechanical, thermal, and electrical properties are typically inferior compared to other engineering materials. Material designers have been seeking to improve polymer properties, which may be achieved by adding suitable particulate fillers. However, the design process is challenging due to countless permutations of available filler materials, different morphologies, filler loadings and fabrication routes. Designing materials solely through experimentation is ineffective given the considerable time and cost associated with such campaigns. Analytical models, on the other hand, typically lack detail, accuracy and versatility. Increasingly powerful numerical techniques are a promising route to alleviate these shortcomings. A stochastic finite element analysis method for predicting the properties of filler-modified polymers is herein presented with a focus on electrical properties, i.e., conductivity, percolation, and piezoresistivity behavior of composites with randomly distributed and dispersed filler particles. The effect of temperature was also explored. While the modeling framework enables prediction of the properties for a variety of filler morphologies, the present study considers spherical particles for the case of nano-silver modified epoxy polymer. Predicted properties were contrasted with data available in the technical literature to demonstrate the viability of the developed modeling approach.

摘要

诸如低比重和低成本等特性使聚合物在许多工程应用中颇具吸引力,然而与其他工程材料相比,它们的机械、热和电性能通常较差。材料设计师一直在寻求改善聚合物性能,这可以通过添加合适的颗粒填料来实现。然而,由于可用填料材料、不同形态、填料含量和制造工艺的排列组合不计其数,设计过程具有挑战性。鉴于此类实验所需的大量时间和成本,仅通过实验来设计材料效率低下。另一方面,分析模型通常缺乏细节、准确性和通用性。日益强大的数值技术是缓解这些缺点的一条有前途的途径。本文提出了一种用于预测填料改性聚合物性能的随机有限元分析方法,重点关注电性能,即具有随机分布和分散填料颗粒的复合材料的电导率、渗流和压阻行为。还探讨了温度的影响。虽然该建模框架能够预测各种填料形态的性能,但本研究针对纳米银改性环氧聚合物的情况考虑了球形颗粒。将预测性能与技术文献中的可用数据进行对比,以证明所开发建模方法的可行性。

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