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Journal of Materials Science

, Volume 51, Issue 6, pp 2980–2990 | Cite as

Effect of compounding method and processing conditions on the electrical response of exfoliated graphite nanoplatelet/polylactic acid nanocomposite films

  • Erin M. Sullivan
  • Rosario A. Gerhardt
  • Ben Wang
  • Kyriaki Kalaitzidou
Original Paper

Abstract

The focus of this study is to understand the effect of compounding method and polymer physical properties on the electrical response of exfoliated graphite nanoplatelet (GNP)/polylactic acid (PLA) nanocomposite films. Two compounding methods were employed: (i) melt mixing, followed by compression molding, and (ii) solution mixing once the polymer was dissolved in chloroform, followed by solution casting. The physical properties of the polymer, namely the crystallization characteristics were altered using two different cooling rates during compression molding: (i) slow cooling and (ii) fast cooling. The microstructure of the films was examined using scanning electron microscopy. Thermal properties, crystallization behavior, and electrical behavior were determined as a function of the GNP content, compounding method, and cooling rate using differential scanning calorimetry, X-ray diffraction, and impedance spectroscopy, respectively. It was concluded that the SC films had the lowest percolation threshold between 1 and 5 wt% of GNP, followed by the solution-cast films with percolation threshold between 5 and 8 wt% of GNP. The FC films did not percolate until a GNP content of 15 wt% was used. The vast differences in percolation thresholds are attributed to the differences in polymer matrix crystallinity and composite microstructure both in terms of microporosity and GNP dispersion/distribution within the polymer due to the different cooling rates and different compounding methods employed.

Keywords

Polylactic Acid Slow Cool Percolation Threshold Crystallization Behavior Nanocomposite Film 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors would like to thank and acknowledge the financial support provided by Cytec Engineered Materials, the Georgia Tech Manufacturing Institute, and the Jewell Family Fellowship. The authors would also like to thank the undergraduate research assistants Richard Flowers and Yun Ju Oh from the School of Materials Science & Engineering and G.W. Woodruff School of Mechanical Engineering, respectively, at Georgia Institute of Technology, for helping with the fabrication of the films.

Funding

This study was funded through research fellowships received by Erin M. Sullivan from Cytec Engineered Materials, the Georgia Tech Manufacturing Institute, and the Jewell Family Fellowship.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Erin M. Sullivan
    • 1
  • Rosario A. Gerhardt
    • 1
  • Ben Wang
    • 1
    • 2
  • Kyriaki Kalaitzidou
    • 1
    • 3
  1. 1.School of Materials Science and EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Georgia Tech Manufacturing InstituteGeorgia Institute of TechnologyAtlantaUSA
  3. 3.George W. Woodruff School of Mechanical EngineeringGeorgia Institute of TechnologyAtlantaUSA

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