基于蒙特卡洛采样的橡胶复合材料内部导电网络建模研究

Research on the Internal Conduction Network Modeling of Rubber Composites Based on Monte Carlo Sampling

新型复合导电材料的制作需要大量的配比实验,构建材料内部导电网络可以拟合网络模型与确定材料的优化配比,而目前国内外研究很少。针对设计和构建有效的橡胶复合材料传感器内部导电网络,提出基于蒙特卡洛采样,产生大量数据模拟导电材料的内部导电网络结构,实现拟合复合材料的导电性能。通过仿真建模讨论以橡胶为基底、碳纳米管(CNTs)为惨杂物的复合材料的逾渗阈值、惨杂物浓度和长径比对材料导电率的影响,从而分析材料的内部网络结构。

The fabrication of new composite conductive materials requires a large number of matching experiments.The internal conductive network of the materials can be used to fit the network model and determine the optimal ratio of materials.At present,there are few related studies at home.Aiming at designing and constructing an effective internal conductive network of rubber composite sensor,proposes a Monte Carlo sampling method.A large number of data are generated to simulate the internal conductive network structure of conductive materials and to fit the conductive properties of composites.Based on the simulation model,discusses the composites with rubber as the base and carbon nanotubes(CNTs)as the tragic impurities.Its percolation threshold,the concentration of the impurity and the aspect ratio have an effect on the conductivity of the material,thereby analyzing the internal network structure of the material.