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Effects of the filler size on the electrical percolation threshold of carbon black–carbon nanotube–polymer composites
Author(s) -
Huang Ying,
Wang Wendong,
Zeng Xiao,
Guo Xiaohui,
Zhang Yangyang,
Liu Ping,
Ma Yuanming,
Zhang Yugang
Publication year - 2018
Publication title -
journal of applied polymer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.575
H-Index - 166
eISSN - 1097-4628
pISSN - 0021-8995
DOI - 10.1002/app.46517
Subject(s) - carbon nanotube , percolation threshold , materials science , composite material , carbon black , percolation (cognitive psychology) , aspect ratio (aeronautics) , filler (materials) , dispersion (optics) , polymer , monte carlo method , electrical conductor , carbon fibers , composite number , electrical resistivity and conductivity , mathematics , physics , statistics , natural rubber , quantum mechanics , neuroscience , optics , biology
The Monte Carlo simulation of filled conductive polymer materials is a method of continuously generating a random conformation and averaging the interesting results to simulate the random dispersion of fillers in space. In our simulation, the irregular shapes of the filler were abstracted into regular ones. Carbon black (CB) aggregates were modeled as spheres, and carbon nanotubes (CNTs) were modeled as capped cylinders. The connection of the fillers was estimated via the calculation of the shortest distance between them; this determined whether a percolation pathway was formed or not. Numerical results were obtained, and these highlight the effects of the filler size, including the aspect ratio of CNTs and the ratio of the diameter of the CB aggregates to the diameter of the CNTs on the electrical percolation threshold (EPT). We found that the EPT decreased with increasing CNT aspect ratio and decreased the diameter ratio of the CB aggregates to CNTs. The simulation results were obtained by a simple pathway‐finder algorithm, which was proven to be effective compared with existing numerical, theoretical, and experimental simulations. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135 , 46517.