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Multiscale modeling and numerical analyses of the electric conductivity of CNT /polymer nanocomposites taking into account the tunneling effect
Author(s) -
Lu Xiaoxin,
Pichon Lionel,
Bai Jinbo
Publication year - 2021
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.2955
Subject(s) - percolation threshold , materials science , carbon nanotube , quantum tunnelling , nanocomposite , conductivity , percolation theory , percolation (cognitive psychology) , anisotropy , electrical resistivity and conductivity , homogenization (climate) , composite material , polymer nanocomposite , nonlinear system , finite element method , electric field , condensed matter physics , physics , thermodynamics , optoelectronics , optics , biodiversity , quantum mechanics , ecology , neuroscience , biology
Tunneling effect plays a significant part in the extremely low electric percolation threshold and large conductivity of carbon nanotube (CNT)/polymer nanocomposites, which allows electric conduction between two CNTs separated at nanometric distances. In this work, a numerical model taking into account the nonlinear tunneling effect is proposed to evaluate the effective electric conductivity of CNT nanocomposites. The nonlinear finite element formulation is introduced, as well as the definitions of effective quantities for homogenization. Moreover, the CNTs are modeled by highly conducting line segments in order to avoid meshing the thin cylindrical tubes. With this technique, the percolation behavior of the composites has been simulated, and the effects of barrier height, CNT length distribution, CNT aspect ratio as well as alignment have been estimated. It turns out that the barrier height dominates the maximum electric conductivity, while the CNT aspect ratio determines the percolation threshold value, respectively. In addition, the anisotropic behavior is obtained by aligning the CNTs, which also results in higher percolation threshold compared with randomly distributed CNTs. Finally, the results are validated by available experimental data.