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Simulation of Percolation Threshold and Electrical Conductivity in Composites Filled With Conductive Particles: Effect of Polydisperse Particle Size Distribution

机译:填充导电颗粒的复合材料的渗透阈值和电导率模拟:多分散粒径分布的影响

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A Monte Carlo simulation method was developed in the open source programing language Python to predict the conductive filler concentration at the percolation threshold and the electrical conductivity for different filler concentrations in electrically conductive composites (ECCs) with fiber-like conductive fillers. The computer method was programmed to consider the aspect ratio distribution of the fibers or a single average aspect ratio for the determination of the percolation threshold. The results for the two cases were compared to values reported in the literature for liquid crystal polymers (LCP) with synthetic graphite (SG) and to results obtained experimentally for polyvinylidene fluoride (PVDF) with polypyrrole (PPy)-coated amorphous silica fibers (ASF). Additionally, a contact resistance based on the tunneling effects principle was used to predict the electrical conductivity, and the results of the simulations were compared to the experimental data for the same ECCS. It was found that the percolation thresholds predicted through the simulations considering the aspect ratio distribution were within the concentration limits associated with the transition from electrical insulation to conductivity, while the electrical conductivity predictions had similar behavior to the experimental data, although the values were of different magnitudes. (C) 2014 Society of Plastics Engineers
机译:在开源编程语言Python中开发了一种Monte Carlo模拟方法,以预测渗滤阈值下的导电填料浓度以及含纤维状导电填料的导电复合材料(ECC)中不同填料浓度的电导率。对计算机方法进行编程,以考虑纤维的纵横比分布或单个平均纵横比,以确定渗滤阈值。将这两种情况的结果与文献中报道的具有合成石墨(SG)的液晶聚合物(LCP)的值进行比较,并与具有聚吡咯(PPy)涂层的无定形二氧化硅纤维(ASF)的聚偏二氟乙烯(PVDF)的实验结果进行比较)。此外,基于隧穿效应原理的接触电阻用于预测电导率,并将仿真结果与相同ECCS的实验数据进行比较。发现通过考虑长宽比分布的模拟预测的渗透阈值在与从电绝缘到电导率的转变相关的浓度极限内,而电导率的预测与实验数据具有相似的行为,尽管值不同数量级。 (C)2014年塑料工程师学会

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