Computational Materials Science2022，Vol.2029.DOI:10.1016/j.commatsci.2021.110986

Theoretical estimation on electrical conductivity, synergy effect and piezoresistive behavior for nanocomposites with hybrid carbon nanotube/graphene based on modified Bethe lattice method

Liu, Ping Li, Yuwen Wu, Chen Liu, Caixia Ma, Yuanming Zhang, Yugang Xing, Kun Liu, Guangzhu Wang, Junfeng Huang, Ying Li, Man Song, Aiguo Yang, Xiaoming
Computational Materials Science2022，Vol.2029.DOI:10.1016/j.commatsci.2021.110986
✕
  • NSTL
  • Elsevier

Theoretical estimation on electrical conductivity, synergy effect and piezoresistive behavior for nanocomposites with hybrid carbon nanotube/graphene based on modified Bethe lattice method

Liu, Ping 1Li, Yuwen 1Wu, Chen 1Liu, Caixia 1Ma, Yuanming 1Zhang, Yugang 1Xing, Kun 1Liu, Guangzhu 1Wang, Junfeng 1Huang, Ying 1Li, Man 2Song, Aiguo 3Yang, Xiaoming4
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作者信息

  • 1. Hefei Univ Technol
  • 2. SuZhou Chien Shiung Inst Technol
  • 3. Southeast Univ
  • 4. Zhejiang Ouren New Mat Co Ltd
  • 折叠

Abstract

In this work, based on the modified Bethe lattice method and excluded volume theory, a conductivity prediction model was proposed for ternary nanocomposites such as carbon nanotubes, graphene nanoplatelet and epoxy, and the influence trend of filler size change on the overall conductivity was also analyzed. The synergy effect was then analyzed based on the above model, and it can be concluded that the enhanced synergy effect between carbon nanotubes and graphene nanosheets is the result of the competition between the geometric synergy effect (whether enhanced or not) and the electrical conductivity of the filler. Moreover, based on this prediction model, we extended a piezoresistive model under tensile strain and explored the effects of filler dosage, size and work function of polymer matrix on piezoresistive effect. It is found that the ternary conductive polymer with enhanced synergy in conductivity also has the chance to have a higher gauge factor, which is valuable for the application of flexible pressure sensors. Although our discussion focuses on the two fillers of carbon nanotubes and graphene, this heuristic prediction model can also be applied to other ternary nanocomposites.

Key words

Polymer-matrix composites (PMCs)/Electrical properties/Sensing/Probabilistic methods/Shell theory/PERCOLATION-THRESHOLD/NANOTUBES/COMPOSITES/PERFORMANCE/INTERPHASE/PREDICTION

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN：0927-0256
被引量2
参考文献量43
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