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Effect of phase transitions on the electrical properties of polymer/carbon nanotube and polymer/graphene nanoplatelet composites with different conductive network structures
Author(s) -
Xiang Dong,
Wang Lei,
Tang Yuhao,
Zhao Chunxia,
HarkinJones Eileen,
Li Yuntao
Publication year - 2018
Publication title -
polymer international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.592
H-Index - 105
eISSN - 1097-0126
pISSN - 0959-8103
DOI - 10.1002/pi.5502
Subject(s) - materials science , composite material , carbon nanotube , high density polyethylene , percolation threshold , electrical resistivity and conductivity , crystallization , differential scanning calorimetry , annealing (glass) , composite number , graphene , polyethylene , chemical engineering , nanotechnology , physics , engineering , electrical engineering , thermodynamics
Multi‐walled carbon nanotube (MWCNT)‐ and graphene nanoplatelet (GNP)‐filled high‐density polyethylene (HDPE) composites with dispersed and segregated network structures were prepared by solution‐assisted mixing. Simultaneous DC conductivity and differential scanning calorimetry were used to measure electrical conductivity during composite thermal phase transitions. It was found that the conductive network is deformed during melting and rebuilt again during annealing due to the re‐agglomeration of nanofillers. The rebuilding of the structure is significantly affected by the original network structure and by the shape and loading of the nanofillers. Both deformation and reorganization of the network lead to drastic changes in the conductivity of the composites. The crystallization process also affects the conductive network to some extent and the subsequent volume shrinkage of the polymeric matrix after crystallization results in a further decrease in the resistivity of HDPE/GNP composites. Classical electrical percolation theory combined with a kinetic equation is used to describe the conductivity recovery of composites during annealing, and the results are found to be in good agreement with experimental data. © 2017 Society of Chemical Industry