New Insights to Effective Carbon Nanofiber Features Due to Defective Interphase for Prediction of Tunneling Conductivity in Composites Publisher Pubmed



Zare Y ; Munir MT ; Rhee KY ; Park SJ
Source: Scientific Reports Published:2025

Abstract

Many nanocomposites include a defective interphase influencing the charge transfer through network. However, the impact of defective interphase on the conductivity of composites including carbon nanofiber (CNF), mentioned as PCNFs, has often been overlooked. In this study, the defective interphase is characterized by the parameter Lc, representing the minimum CNF length necessary for effective conduction transfer from the CNF to the matrix. The effective concentration and length of CNFs in PCNFs, along with the percolation threshold and network concentration, are thus defined by Lc. Furthermore, Weber-Kamal model is refined and extended using effective terms and tunneling properties to estimate PCNF conductivity accurately. The influence of all contributing factors on PCNF conductivity is validated, and the experimental conductivity results support the model predictions. A maximum conductivity of 0.11 S/m is reached at Lc = 10 μm and polymer tunnel resistivity (ρ) of 50 Ω m, while the values of Lc > 16 μm result in an insulating sample. Thus, minimizing Lc and polymer tunnel resistivity maximizes nanocomposite conductivity, whereas higher values of Lc do not enhance conductivity. The lowest Lc and highest interphase conductivity are observed in the sample with the highest conductivity, corroborating the impacts of Lc and interphase conductivity on the measured PCNF conductivity. © 2025 Elsevier B.V., All rights reserved.