3D Monte Carlo simulation modeling for the electrical conductivity of carbon nanotube-incorporated polymer nanocomposite using resistance network formation

Journal Title: Materials Science: Advanced Composite Materials - Year 2018, Vol 2, Issue 2

Abstract

High electrical and thermal conductivity associated with high stiffness and strength offer tremendous opportunities to the development of a series of carbon nanotube incorporated composite materials for a variety of applications. In particular, a small amount of carbon fibers or carbon nanotubes in a non-conductive polymer will transform a composite into a conductive material, which reveals superb potential of their future application in electronic devices. The relation between the amount of carbon nanotubes in a polymer and the electrical conductivity of it can be studied experimentally as well as theoretically with various simulation models. A three-dimensional (3D) Monte Carlo simulation model using resistance network formation was developed to study the relation between the electrical conductivity of the polymer nanocomposite and the amount of carbon nanotubes dispersed in it. In this model, carbon nanotubes were modeled as curvy cylindrical nanotubes with various lengths and fixed tube diameter, all of which were randomly distributed in a non-conductive constrained volume, which represents polymer. The model can be used to find the volumetric electrical resistance of a constrained cubic structure by forming a comprehensive resistance network among all of the nanotubes in contact. As more and more nanotubes were added into the volume, the electrical conductivity of the volume increases exponentially. However, once the amount of carbon nanotubes reached about 0.1 % vt (volume percentage), electrical percolation was detected, which was consistent with the experimental results. This model can be used to estimate the electrical conductivity of the composite matrix as well as to acquire the electrical percolation threshold.

Authors and Affiliations

Nanzhu Zhao, Yongha Kim, Joseph H. Koo

Keywords

Related Articles

Metallic nanoformulations: Green synthetic approach for advanced drug delivery

An important reason for investigation using plants for nanotechnological research is due to their easy availability as well as applications in various ailments. Silver nanoformulation can be synthesized using whole plant...

Short beam strength and flexural behavior of GFRP laminates embedded with short carbon fibers having notch

This paper examines the mechanical performance of eight-layered GFRP laminate embedded with short carbon fibers (SCF). Eight layered GFRP samples are prepared using press molding machine at 40 KN pressure. Notched sample...

Mechanical and structural properties of termite soil as a partial replacement to cement for different applications

This paper presents the results of the experimental and theoretical study of the mechanical and structural properties of termite soil as a partial replacement to cement for different applications, especially in the build...

Investigation of the mechanical and physical properties of PLA produced by injection molding for matrix material of polymer composites

Polymer materials are increasingly being used due to their superior properties such as light weight, low cost and corrosion resistance. The difficult destruction of highly advantageous polymers in the environment leads t...

Correlations between dynamic fragility, activation energy and glass transition temperature in polymeric composite materials: An overview from literature

Here, it is compiled data from literature for glass transition temperature (Tg) and activation energy (Ea) for different types of polymeric composite materials. A correlation among both parameters and dynamic mechanical...

Download PDF file
  • EP ID EP679021
  • DOI -
  • Views 174
  • Downloads 0

How To Cite

Nanzhu Zhao, Yongha Kim, Joseph H. Koo (2018). 3D Monte Carlo simulation modeling for the electrical conductivity of carbon nanotube-incorporated polymer nanocomposite using resistance network formation. Materials Science: Advanced Composite Materials, 2(2), -. https://europub.co.uk./articles/-A-679021