Computational modeling of electrically conductive networks formed by graphene nanoplatelet-carbon nanotube hybrid particles

Angel Mora Cordova, Fei Han, Gilles Lubineau

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


One strategy to ensure that nanofiller networks in a polymer composite percolate at low volume fractions is to promote segregation. In a segregated structure, the concentration of nanofillers is kept low in some regions of the sample. In turn, the concentration in the remaining regions is much higher than the average concentration of the sample. This selective placement of the nanofillers ensures percolation at low average concentration. One original strategy to promote segregation is by tuning the shape of the nanofillers. We use a computational approach to study the conductive networks formed by hybrid particles obtained by growing carbon nanotubes (CNTs) on graphene nanoplatelets (GNPs). The objective of this study is (1) to show that the higher electrical conductivity of these composites is due to the hybrid particles forming a segregated structure and (2) to understand which parameters defining the hybrid particles determine the efficiency of the segregation. We construct a microstructure to observe the conducting paths and determine whether a segregated structure has indeed been formed inside the composite. A measure of efficiency is presented based on the fraction of nanofillers that contribute to the conductive network. Then, the efficiency of the hybrid-particle networks is compared to those of three other networks of carbon-based nanofillers in which no hybrid particles are used: only CNTs, only GNPs, and a mix of CNTs and GNPs. Finally, some parameters of the hybrid particle are studied: the CNT density on the GNPs, and the CNT and GNP geometries. We also present recommendations for the further improvement of a composite's conductivity based on these parameters.

Original languageEnglish (US)
Article number035010
JournalModelling and Simulation in Materials Science and Engineering
Issue number3
StatePublished - Feb 23 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST).


  • carbon nanotube
  • electrical properties
  • graphene nanoplatelet
  • hybrid particle
  • polymer composites
  • segregated structure

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • General Materials Science
  • Computer Science Applications
  • Modeling and Simulation


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