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Highly electrically conductive adhesives using silver nanoparticle (Ag NP)-decorated graphene: the effect of NPs sintering on the electrical conductivity improvement

  • Behnam Meschi Amoli
  • Josh Trinidad
  • Anming Hu
  • Y. Norman Zhou
  • Boxin ZhaoEmail author
Article

Abstract

Electrically conductive adhesives (ECAs) filled with silver nanoparticle (Ag NP)-decorated graphene were prepared and the effect of curing temperature on the electrical conductivity of the ECAs was discussed. Mono-dispersed Ag NPs with an average size of 9 nm were successfully deposited and simultaneously functionalized with mercaptopropionic acid (MPA) on graphene surface. The surface functionalization of the NPs with MPA made the decorated graphene dispersible in organic solvents, which facilitated its dispersion inside epoxy. The decorated graphene was added into conventional ECAs (consisting of silver flakes and epoxy) at concentrations close to the percolation threshold and beyond that resulting in a significant electrical conductivity improvement (especially at concentrations close to the percolation threshold). The electrical resistivity of hybrid ECAs with the decorated graphene decreased as the curing temperature increased. Curing the ECA with 1 wt% of the decorated graphene at 220 °C resulted in a highly conductive adhesive with a low electrical resistivity of 4.6 × 10−5 Ω cm (close to that of eutectic lead based solders). The dramatic electrical conductivity improvement of ECAs is due to the sintering between small Ag NPs on the graphene surface and silver flakes. Morphological and thermal studies showed that Ag NPs start to sinter at approximately 150 °C when the MPA layer began to decompose from their surface. The quality of filler–filler interaction was investigated by monitoring the effect of temperature on the electrical resistivity of conductive fillers “thin-film” before their addition to epoxy.

Keywords

Graphene Oxide Graphene Surface Graphene Nanosheets Conductive Filler Conductive Adhesive 
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

Acknowledgments

This work was supported by a Strategic Project Grant from the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Behnam Meschi Amoli
    • 1
    • 2
    • 4
  • Josh Trinidad
    • 1
    • 2
  • Anming Hu
    • 3
    • 4
    • 5
  • Y. Norman Zhou
    • 2
    • 3
    • 4
  • Boxin Zhao
    • 1
    • 2
    • 4
    Email author
  1. 1.Department of Chemical EngineeringUniversity of WaterlooWaterlooCanada
  2. 2.Waterloo Institute for NanotechnologyUniversity of WaterlooWaterlooCanada
  3. 3.Department of Mechanical and Mechatronics EngineeringUniversity of WaterlooWaterlooCanada
  4. 4.Centre for Advanced Materials JoiningUniversity of WaterlooWaterlooCanada
  5. 5.Department of Mechanical, Aerospace and Biomedical EngineeringUniversity of Tennessee KnoxvilleKnoxvilleUSA

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