4.7 Article

Estimation of average contact number of carbon nanotubes (CNTs) in polymer nanocomposites to optimize the electrical conductivity

期刊

ENGINEERING WITH COMPUTERS
卷 38, 期 SUPPL 1, 页码 243-253

出版社

SPRINGER
DOI: 10.1007/s00366-020-01153-1

关键词

Carbon nanotubes (CNTs); Polymer nanocomposites; Contact number; Tunneling effect

资金

  1. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology [2020R1A2B5B02002203]

向作者/读者索取更多资源

This paper suggests an equation to calculate the average contact number of carbon nanotubes (CNTs) in CNT-reinforced polymer nanocomposites (PCNT) and explores the various parameters that affect the contact number. The results show that a dense interphase, a high fraction of networked CNTs, reedy and short CNTs, low CNT surface energy, high polymer surface energy, low tunneling distance, and small contact diameter increase the contact number and improve the conductivity.
The present paper suggests an equation for the average contact number of carbon nanotubes (CNTs) in CNT-reinforced polymer nanocomposites (PCNT) by two developed equations for electrical conductivity. Several novel parameters in PCNT such as CNT size, CNT concentration, network fraction, interphase depth, tunneling effect, and CNT wettability by the polymer medium are considered to define the average contact number (m). m is calculated for some samples and the variation of m is explored over a range of parameters' values. The results show that dense interphase, high fraction of networked CNTs, reedy and short CNTs, low CNT surface energy, high polymer surface energy, low tunneling distance, and small contact diameter increase the m improving the conductivity. Moreover, tunneling distance and CNT contact diameter have the greatest effects on the m. The optimized level for m is necessary to control the nanocomposite's conductivity.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据