Skip to main navigation Skip to search Skip to main content

Molecular dynamics simulations of thermodynamics and shape memory effect in CNT-epoxy nanocomposites

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Epoxy based shape memory polymers have attracted considerable attention in engineering applications. To achieve excellent thermo-mechanical performance, carbon nanotube (CNT) is used as reinforcement for epoxy matrix. The improvement of mechanical properties and shape memory effect in CNT-epoxy nanocomposites are investigated using molecular dynamics simulations in this study. The two representative systems, neat epoxy and CNT-reinforced epoxy nanocomposite are constructed, and the corresponding physical properties, such as the density and the glass transition temperature are obatained. The mechanical properties and shape memory behaviors within the selected temperature range are characterized by applying tensile loading. The segmental dynamics are also captured during deformation process to investigate how epoxy chains are activated and changed that leads to final conformations. In addition, the free volume during recovery process is tracked to study shape recovery properties. The results can provide better understanding of the reinforcing mechanism of CNT on mechanical properties and shape memory effect of epoxy nanocomposites, which help to enrich the fundamental knowledge of shape memory epoxy nanocomposites and enlightens the design of shape memory materials.
Original languageEnglish
Article number108849
JournalComposites Science and Technology
Volume211
Online published7 May 2021
DOIs
Publication statusPublished - 28 Jul 2021

Research Keywords

  • Carbon nanotubes
  • Molecular dynamics
  • Nano composites
  • Shape memory behaviour

RGC Funding Information

  • RGC-funded

Fingerprint

Dive into the research topics of 'Molecular dynamics simulations of thermodynamics and shape memory effect in CNT-epoxy nanocomposites'. Together they form a unique fingerprint.

Cite this