渗透(认知心理学)
材料科学
蒙特卡罗方法
复合材料
导电体
渗流阈值
聚合物
碳纤维
电阻率和电导率
复合数
工程类
数学
电气工程
统计
神经科学
生物
作者
Zhe Zhang,Liang Hu,Qianqian Wang,Shujie Zhang,Lisong Fu,Mengxuan Li,Qi Xiao
出处
期刊:Polymers
[MDPI AG]
日期:2024-02-18
卷期号:16 (4): 545-545
标识
DOI:10.3390/polym16040545
摘要
Conductive polymer composites (CPCs) filled with carbon-based materials are widely used in the fields of antistatic, electromagnetic interference shielding, and wearable electronic devices. The conductivity of CPCs with a carbon-based filling is reflected by their electrical percolation behavior and is the focus of research in this field. Compared to experimental methods, Monte Carlo simulations can predict the conductivity and analyze the factors affecting the conductivity from a microscopic perspective, which greatly reduces the number of experiments and provides a basis for structural design of conductive polymers. This review focuses on Monte Carlo models of CPCs with a carbon-based filling. First, the theoretical basis of the model’s construction is introduced, and a Monte Carlo simulation of the electrical percolation behaviors of spherical-, rod-, disk-, and hybridfilled polymers and the analysis of the factors influencing the electrical percolation behavior from a microscopic point of view are summarized. In addition, the paper summarizes the progress of polymer piezoresistive models and polymer foaming structure models that are more relevant to practical applications; finally, we discuss the shortcomings and future research trends of existing Monte Carlo models of CPCs with carbon-based fillings.
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