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Numerical investigation on percolation threshold of CNT-reinforced conductive composites based on three-dimensional Monte Carlo method

机译:基于三维蒙特卡罗法的​​CNT增强导电复合材料渗流阈值的数值研究

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It is reported that carbon nanotube (CNT)-based conductive polymer composites have potential application prospect in structural health monitoring and flexible sensors. However, the current price of CNTs is relatively high compared with other fillers. To reduce the materials cost and ensure the sensing characteristics of this type of materials, the most economic and least amount of CNTs needed should be found, this balance value is called as electrical percolation threshold (EPT) in this study. First, a large number of numerical models containing CNTs with three-dimensional random distribution and epoxy resin matrix are established by Monte Carlo method. Then, the construct of conductive network is observed using these models, and the influence of electron tunneling between two adjacent CNTs on the EPT is investigated. Furthermore, the influence of length-diameter ratio (L/D) of CNTs, length variation and angle distribution of CNTs on EPT is investigated. This research provides useful information on how to produce conductive composites more economically.
机译:据报道,基于碳纳米管(CNT)的导电聚合物复合材料具有结构健康监测和柔性传感器的潜在应用前景。然而,与其他填料相比,CNT的当前价格相对较高。为了减少材料成本并确保这种类型的材料的感测特性,应发现最经济和最少的CNT,这种平衡值称为本研究中的电渗透阈值(EPT)。首先,通过Monte Carlo方法建立含有具有三维随机分布和环氧树脂基质的CNT的大量数值模型。然后,使用这些模型观察导电网络的构造,并研究了EPT上的两个相邻CNT之间的电子隧穿的影响。此外,研究了CNT的长度直径比(L / D),CNT的长度变化和角度分布对EPT的影响。本研究提供了有关如何更经济地生产导电复合材料的有用信息。

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