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Three-dimensional Modeling of Percolation Behavior of Electrical Conductivity in Segregated Network Polymer Nanocomposites Using Monte Carlo Method

Received: 19 May 2016     Published: 19 May 2016
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Abstract

Polymer nanocomposites filled with carbon nanotubes are observed to present an onset of the insulator-to-conductor transition through previous experimental studies. In this work, numerical simulations based on Monte Carlo method are performed to investigate the percolation threshold. The conductive fillers are modeled as a three dimensional (3D) network of identical units dispersed in the polymer matrix. However, the distribution of the fibers is not uniform due to the existence of the emulsion particles. The effects of the aspect ratio and fiber length on the critical volume fraction are studied. Linearization is made to the logarithm of simulation results. The calculated critical volume fraction is used in the power-law function to predict the electrical conductivity of the polymer composites. The results from the homogeneous model (without emulsion particles) and the model containing emulsion particles are compared. The effects of the size and the geometrical variation of the emulsion particles are evaluated.

Published in Advances in Materials (Volume 5, Issue 1)
DOI 10.11648/j.am.20160501.11
Page(s) 1-8
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Monte Carlo Simulation, Electrical Conductivity, Nanotubes, Polymer Nanocomposites

References
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  • APA Style

    Heng Gu, Jiaojiao Wang, Choongho Yu. (2016). Three-dimensional Modeling of Percolation Behavior of Electrical Conductivity in Segregated Network Polymer Nanocomposites Using Monte Carlo Method. Advances in Materials, 5(1), 1-8. https://doi.org/10.11648/j.am.20160501.11

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    ACS Style

    Heng Gu; Jiaojiao Wang; Choongho Yu. Three-dimensional Modeling of Percolation Behavior of Electrical Conductivity in Segregated Network Polymer Nanocomposites Using Monte Carlo Method. Adv. Mater. 2016, 5(1), 1-8. doi: 10.11648/j.am.20160501.11

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    AMA Style

    Heng Gu, Jiaojiao Wang, Choongho Yu. Three-dimensional Modeling of Percolation Behavior of Electrical Conductivity in Segregated Network Polymer Nanocomposites Using Monte Carlo Method. Adv Mater. 2016;5(1):1-8. doi: 10.11648/j.am.20160501.11

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  • @article{10.11648/j.am.20160501.11,
      author = {Heng Gu and Jiaojiao Wang and Choongho Yu},
      title = {Three-dimensional Modeling of Percolation Behavior of Electrical Conductivity in Segregated Network Polymer Nanocomposites Using Monte Carlo Method},
      journal = {Advances in Materials},
      volume = {5},
      number = {1},
      pages = {1-8},
      doi = {10.11648/j.am.20160501.11},
      url = {https://doi.org/10.11648/j.am.20160501.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.am.20160501.11},
      abstract = {Polymer nanocomposites filled with carbon nanotubes are observed to present an onset of the insulator-to-conductor transition through previous experimental studies. In this work, numerical simulations based on Monte Carlo method are performed to investigate the percolation threshold. The conductive fillers are modeled as a three dimensional (3D) network of identical units dispersed in the polymer matrix. However, the distribution of the fibers is not uniform due to the existence of the emulsion particles. The effects of the aspect ratio and fiber length on the critical volume fraction are studied. Linearization is made to the logarithm of simulation results. The calculated critical volume fraction is used in the power-law function to predict the electrical conductivity of the polymer composites. The results from the homogeneous model (without emulsion particles) and the model containing emulsion particles are compared. The effects of the size and the geometrical variation of the emulsion particles are evaluated.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Three-dimensional Modeling of Percolation Behavior of Electrical Conductivity in Segregated Network Polymer Nanocomposites Using Monte Carlo Method
    AU  - Heng Gu
    AU  - Jiaojiao Wang
    AU  - Choongho Yu
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    PY  - 2016
    N1  - https://doi.org/10.11648/j.am.20160501.11
    DO  - 10.11648/j.am.20160501.11
    T2  - Advances in Materials
    JF  - Advances in Materials
    JO  - Advances in Materials
    SP  - 1
    EP  - 8
    PB  - Science Publishing Group
    SN  - 2327-252X
    UR  - https://doi.org/10.11648/j.am.20160501.11
    AB  - Polymer nanocomposites filled with carbon nanotubes are observed to present an onset of the insulator-to-conductor transition through previous experimental studies. In this work, numerical simulations based on Monte Carlo method are performed to investigate the percolation threshold. The conductive fillers are modeled as a three dimensional (3D) network of identical units dispersed in the polymer matrix. However, the distribution of the fibers is not uniform due to the existence of the emulsion particles. The effects of the aspect ratio and fiber length on the critical volume fraction are studied. Linearization is made to the logarithm of simulation results. The calculated critical volume fraction is used in the power-law function to predict the electrical conductivity of the polymer composites. The results from the homogeneous model (without emulsion particles) and the model containing emulsion particles are compared. The effects of the size and the geometrical variation of the emulsion particles are evaluated.
    VL  - 5
    IS  - 1
    ER  - 

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Author Information
  • Rexa Electraulic Actuation, Inc. West Bridgewater, MA, USA

  • School of Materials Science and Engineering, East China University of Science and Technology, Shanghai, China

  • Department of Mechanical Engineering, Texas A&M University, College Station, Texas, USA

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