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

机译:基于三维蒙特卡洛法的碳纳米管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在结构健康监测和柔性传感器中具有潜在的应用前景。但是,与其他填充剂相比,目前的碳纳米管价格相对较高。为了降低材料成本并确保此类材料的传感特性,应找到所需的最经济,数量最少的CNT,该平衡值在本研究中称为电渗透阈值(EPT)。首先,通过蒙特卡罗方法建立了大量包含三维随机分布的碳纳米管和环氧树脂基体的数值模型。然后,使用这些模型观察导电网络的构造,并研究两个相邻CNT之间的电子隧穿对EPT的影响。此外,研究了碳纳米管的长径比(L / D),碳纳米管的长度变化和角度分布对EPT的影响。这项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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