New insights to effective carbon nanofiber features due to defective interphase for prediction of tunneling conductivity in composites

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 L_c, 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 L_c. 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 L_c = 10 μm and polymer tunnel resistivity (ρ) of 50 Ω m, while the values of L_c > 16 μm result in an insulating sample. Thus, minimizing L_c and polymer tunnel resistivity maximizes nanocomposite conductivity, whereas higher values of L_c do not enhance conductivity. The lowest L_c and highest interphase conductivity are observed in the sample with the highest conductivity, corroborating the impacts of L_c and interphase conductivity on the measured PCNF conductivity.