TY - JOUR
T1 - Interpreting Electrical Conductivity for Carbon Nanofiber-Polymer Systems by a Modeling Approach
AU - Arjmandi, Sajad Khalil
AU - Khademzadeh Yeganeh, Jafar
AU - Naqvi, Muhammad
AU - Zare, Yasser
AU - Rhee, Kyong Yop
AU - Park, Soo Jin
N1 - Publisher Copyright:
© 2025 Society of Plastics Engineers.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - A new methodology is developed to interpret the effective conductivity of the polymeric samples reinforced by carbon nanofibers (CNFs), referred to as PCNFs, taking into account the total resistivity of the system. The proposed method is used to estimate the effective conductivity of some samples. The model's predictions are compared to experimental results. Furthermore, applicable equations are provided for CNF effective volume share, waviness of CNFs, threshold of percolation, and the network percentage. In addition, the advanced method is validated through analysis of all factors affecting effective conductivity. The results reveal that a lower percolation onset ((Formula presented.)), thicker interphase, shorter tunneling distance, lower tunneling resistivity of polymer (ρ), larger tunneling diameter (d), and shorter tunneling size all contribute to higher effective conductivity in PCNFs. The effective conductivity reduces to zero when CNF volume percentage ((Formula presented.)) is less than 0.015, but the utmost conductivity of 0.0044 S/m is achieved at (Formula presented.) = 0.04 and d = 40 nm. Furthermore, no conductivity is noticed at ρ > 6 Ω·m and (Formula presented.) > 0.013, while the greatest effective conductivity of 0.0017 S/m is seen at the lowest values of ρ = 1 Ω·m and (Formula presented.) = 0.002.
AB - A new methodology is developed to interpret the effective conductivity of the polymeric samples reinforced by carbon nanofibers (CNFs), referred to as PCNFs, taking into account the total resistivity of the system. The proposed method is used to estimate the effective conductivity of some samples. The model's predictions are compared to experimental results. Furthermore, applicable equations are provided for CNF effective volume share, waviness of CNFs, threshold of percolation, and the network percentage. In addition, the advanced method is validated through analysis of all factors affecting effective conductivity. The results reveal that a lower percolation onset ((Formula presented.)), thicker interphase, shorter tunneling distance, lower tunneling resistivity of polymer (ρ), larger tunneling diameter (d), and shorter tunneling size all contribute to higher effective conductivity in PCNFs. The effective conductivity reduces to zero when CNF volume percentage ((Formula presented.)) is less than 0.015, but the utmost conductivity of 0.0044 S/m is achieved at (Formula presented.) = 0.04 and d = 40 nm. Furthermore, no conductivity is noticed at ρ > 6 Ω·m and (Formula presented.) > 0.013, while the greatest effective conductivity of 0.0017 S/m is seen at the lowest values of ρ = 1 Ω·m and (Formula presented.) = 0.002.
KW - carbon nanofiber (CNF)
KW - effective conductivity
KW - interphase
KW - nanocomposite
KW - percolation threshold
KW - tunneling resistivity
UR - https://www.scopus.com/pages/publications/105016205232
U2 - 10.1002/pc.70443
DO - 10.1002/pc.70443
M3 - Article
AN - SCOPUS:105016205232
SN - 0272-8397
JO - Polymer Composites
JF - Polymer Composites
ER -