Mechanical properties of carbon nanotube‐filled polyethylene composites: A molecular dynamics simulation study

POLYMER COMPOSITES(2019)

引用 32|浏览3
暂无评分
摘要
Molecular dynamics (MDs) simulations are carried out to study the mechanical properties of low- and high-density polyethylene (LDPE and HDPE) and their composites filled with carbon nanotubes (CNTs). The influences of the number of polymer chains, CNT type and concentration, and strain rate on the predicted mechanical properties are studied. Two different temperatures of 100 and 300 K are used to represent the glassy and rubbery states of the polymers, respectively. Results indicate that the models typically show four stages of deformation before failure: linear elastic and yield followed by strain softening and strain hardening. Thepristine models simulated at a given temperature exhibit a similar behavior regardless of their density, especially during the linear elastic stage. The HDPE models exhibit fairly similar behaviors in their strain-hardening response regardless of the number of chains, while this factor considerably influences the strain-hardening response of the LDPE models. Strain rate is shown to have a strong influence on different mechanical characteristics of all of polymer models examined (i.e., elastic modulus, yield stress, post-yield strain softening, and strain hardening behavior). In contrast, LDPE and HDPE composites exhibit essentially the same behavior and similar failure characteristics under a given temperature regardless of the strain rate applied. The tensile strength of CNT-filled LDPE and HDPE increases linearly with CNT concentration within the range of concentrations studied (0.79-2.63 wt%) and is inversely proportional to the CNT chirality. The results are thoroughly discussed and the factors contributing to their departure from reference laboratory data are outlined. (C) 2018 Society of Plastics Engineers
更多
查看译文
关键词
polyethylene composites,molecular dynamics simulation,molecular dynamics,mechanical properties
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要