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Estimating electrical conductivity of multi-scale composites with conductive nanoparticles using bidirectional time marching percolation network mapping

机译:使用双向时间行进渗滤网络映射法估计具有导电纳米粒子的多尺度复合材料的电导率

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摘要

A computationally efficient approach is developed to determine electrical conductivity of large specimens of multi-scale composites composed of electrically conductive nanoparticles and nonconductive matrix and micro-scale reinforcements. As a test case, the paper studies nanocomposites and multi-scale fiber/polymer composites of carbon nanotubes. Fraction of percolating carbon nanotubes is defined as a metric for estimating electrical conductivity of composites with intermediate volume fraction of carbon nanotubes. The results indicate that for multi-scale composites with high fiber/reinforcement volume fraction, the simulation size needs to be in millimeters whereas for multi-scale composites with low fiber/reinforcement volume fraction, smaller simulation sizes (in 100s of microns) are sufficient. The present research is a first step towards efficient design of fiber composites for electromagnetic applications such as lightening protection and electromagnetic shielding.
机译:开发了一种计算有效的方法来确定由导电纳米颗粒和非导电基体以及微尺度增强物组成的多尺度复合材料的大型试样的电导率。作为测试案例,本文研究了碳纳米管的纳米复合材料和多尺度纤维/聚合物复合材料。渗滤碳纳米管的分数被定义为用于估计具有碳纳米管的中等体积分数的复合材料的电导率的度量。结果表明,对于具有高纤维/增强体积分数的多尺度复合材料,模拟尺寸需要以毫米为单位,而对于具有低纤维/增强体积分数的多尺度复合材料,较小的模拟尺寸(100微米)就足够了。本研究是高效设计用于电磁应用(例如防雷和电磁屏蔽)的纤维复合材料的第一步。

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