导电复合材料渗滤模型和压阻效应研究

发布时间：2018-02-09 05:56

本文关键词： 导电复合材料导电网络各向异性渗滤阈值压阻特性　出处：《中国科学技术大学》2017年博士论文　论文类型：学位论文

【摘要】：随着机器人技术的快速发展,机器人的应用范围越来越广,对机器人的智能化和安全性要求也越来越高。在这样的背景下,可以覆盖机器人关键部位或全身的柔性传感器引起了研究者的广泛关注。作为一种新型的压阻传感材料,导电复合材料是以聚合物材料为基体,通过填充导电填料,将基体的柔性和填料的导电性有机地结合起来。传统的金属或半导体压阻材料硬且脆,与之相比,导电复合材料更加柔韧,更适合应用于柔性传感器的设计。本论文旨在开发具有低填料体积分数和高压阻效应的导电复合材料。重点关注导电复合材料的渗滤阈值和压阻特性,围绕导电网络结构与电阻率之间的关系,展开一系列的理论与实验研究。我们首先研究了球形羰基铁粉颗粒(CIP)填充的导电复合材料的电学特性。CIP沿着磁场方向取向,形成链状结构,从而得到各向异性导电复合材料。通过统计分析,得到磁场强度对CIP链状结构长度的影响。制备了不同CIP体积分数的导电复合材料,并测试了它们的电阻率和电阻随压力的变化,得到渗滤阈值和压阻灵敏度系数。建立了杆状填料的2D导电网络模型,通过Monte Carlo仿真方法分析各向异性情况下CIP链状结构的平均长度、长度分布以及方向等参数对导电网络和渗滤阈值的影响。该模型预测的渗滤阈值与实验结果具有较好的一致性。我们又以杆状多壁碳纳米管(MWCNT)和微量CIP为填料,制备了导电复合材料。在磁场作用下微量CIP沿磁场方向运动,并诱导局部MWCNT产生一定程度的取向,从而得到各向异性导电复合材料。建立了杆状填料的3D导电网络模型,通过Monte Carlo仿真方法分析MWCNT杆状结构的取向程度对导电网络和渗滤阈值的影响。另外,建立了 MWCNT导电网络的8杆结构模型,引入MWCNT的方向角参数,分析导电复合材料的电阻率随取向程度的变化。通过实验测试得到导电复合材料的渗滤阈值和压阻灵敏度系数,并验证了模型预测的结果。另外,我们还研究了片状石墨烯(GNP)填充的各向异性导电复合材料。在导电复合材料的制备过程中,微量CIP沿磁场方向运动并诱导局部GNP产生一定程度的取向。结合晶格模型和排斥体积理论,建立了圆片填料的3D导电网络模型,分析GNP圆片的方向分布对临界接触距离的影响,从而得到GNP取向程度对渗滤阈值的影响。GNP的取向程度越高,临界接触距离就越大,则对应渗滤阈值就越低。通过实验测试得到导电复合材料的渗滤阈值,验证了模型预测结果。并测试不同应力下试样电阻值的变化,计算压阻灵敏度系数。
[Abstract]:With the rapid development of robot technology, the application scope of robot is more and more extensive, and the requirement of intelligence and safety of robot is more and more high. Flexible sensors that can cover key parts of the robot or the whole body have attracted wide attention. As a new type of piezoresistive sensing material, conductive composites are filled with conductive fillers, which are based on polymer materials. The flexibility of the matrix is organically combined with the conductivity of the filler. Traditional metal or semiconductor piezoresistive materials are hard and brittle, and conductive composites are more flexible than those of conventional metal or semiconductor piezoresistive materials. The purpose of this paper is to develop conductive composites with low volume fraction of filler and high pressure resistance effect, focusing on the percolation threshold and piezoresistive characteristics of conductive composites. A series of theoretical and experimental studies have been carried out on the relationship between electrical network structure and resistivity. Firstly, the electrical properties of conductive composites filled with spherical carbonyl iron particles (CIPs) have been investigated. Through statistical analysis, the influence of magnetic field strength on the length of CIP chain structure was obtained. The conductive composites with different CIP volume fraction were prepared. The percolation threshold and piezoresistive sensitivity coefficient were obtained by measuring their resistivity and resistance with pressure. The 2D conductive network model of rod packing was established. The average length of CIP chain structure under anisotropic condition is analyzed by Monte Carlo simulation method. The influence of length distribution and direction on the conductivity network and percolation threshold. The predicted percolation threshold of the model is in good agreement with the experimental results. We also use rod-shaped multi-walled carbon nanotubes (MWCNT) and trace amounts of CIP as fillers. Conductive composites were prepared. Under the action of magnetic field, trace CIP moved along the direction of magnetic field, and local MWCNT was induced to produce a certain degree of orientation, thus anisotropic conductive composites were obtained. A 3D conductive network model of rod fillers was established. The influence of orientation degree of MWCNT rod structure on conductive network and percolation threshold is analyzed by Monte Carlo simulation method. In addition, the 8-bar structure model of MWCNT conductive network is established, and the direction angle parameter of MWCNT is introduced. The change of resistivity with orientation of conductive composites is analyzed. The percolation threshold and piezoresistive sensitivity coefficient of conductive composites are obtained by experimental tests, and the results of model prediction are verified. We also studied the anisotropic conductive composites filled with flake graphene GNPs. Trace CIP moves along the direction of magnetic field and induces a certain degree of orientation of local GNP. Based on lattice model and repellent volume theory, the 3D conductive network model of disk packing is established, and the influence of the direction distribution of GNP wafer on the critical contact distance is analyzed. The higher the orientation degree of GNP is, the greater the critical contact distance is, and the lower the percolation threshold is. The predicted results of the model are verified, and the change of the resistance value of the sample under different stresses is tested to calculate the piezoresistive sensitivity coefficient.
【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：TB33

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