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Unraveling the roles of network and tunnels in the conductivity of carbon nanofiber composites

Yasser Zare, Muhammad Naqvi, Kyong Yop Rhee, Soo‐Jin Park

2025Scientific Reports10 citationsDOIOpen Access PDF

Abstract

Herein, an advanced conductivity model for polymer-carbon nanofiber (CNF) samples is introduced, stated as PCNFs. This model considers the length (l), radius (R) and amount of CNFs, interphase depth, percolation onset (PT), waviness, network portion, and tunneling length (d), by reasonable and meaningful equations. The proposed model is verified through the measured conductivity of samples and by studying the features' influences on the PCNF conductivity. The model calculations display respectable fitting with the experimented facts from numerous CNF samples. Additionally, all factors sensibly affect the conductivity of PCNFs. Longer and thinner CNFs, higher CNF amount, thicker interphase, shorter tunnels, and lower percolation onset lead to higher conductivity in PCNF. R > 50 nm and l < 15 μm produce an insulative composite, but the top conductivity of 0.21 S/m is displayed at R = 10 nm and l = 25 μm. Accordingly, narrower and bigger nanofibers can improve the conductivity. Furthermore, an insulative material is produced by PT = 0.04 nm and d > 5 nm, nevertheless the conductivity maximizes to 0.25 S/m at the least values of PT = 0.01 nm and d = 2 nm. These results disclose that the lowest percolation onset and narrowest tunnels yield the highest conductivity in the composite.

Topics & Concepts

ConductivityMaterials sciencePercolation (cognitive psychology)Percolation thresholdComposite materialRADIUSCarbon nanofiberQuantum tunnellingInterphaseNanofiberYield (engineering)Electrical resistivity and conductivityThermal conductionCarbon fibersPercolation theoryCarbon Nanotubes in CompositesConducting polymers and applicationsGraphene research and applications
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