Decrypting of effective resistance for composites of polymer-carbon nanofiber: An applicable approach to regulate the electrical conductivity

It is postulated that the effective resistance ( R _eff ) causes a critical impact on the nanocomposite electrical conductivity, and an increase in R _eff inversely affects the composite conductivity. Nevertheless, R _eff remains an elusive parameter, and its dependence on the characteristics of the filler, tunneling district and interphase were inadequately defined. In this work, we advance the Jang-Yin and Weber-Kamal models to accurately assess the conductivity for polymer/carbon nanofiber (CNF) system (PCNF), incorporating key factors as tunneling properties and interphase size. The precision of these models is rigorously evaluated against a broad spectrum of experimental data. By joining the models, we derive an explicit expression for R _eff in PCNFs, elucidating its correlation with percolation onset, CNF concentration, CNF dimensions, interphase depth, CNF waviness, tunneling diameter ( d ), tunneling size, contact number ( m ), and polymer tunneling resistivity. A comprehensive analysis of these factors on the R _eff validates the proposed theoretical framework. Our findings reveal that R _eff reaches a peak value of 2.2 × 10⁶ Ω at m = 50 and d = 10 nm, whereas it significantly decreases to approximately 0.04 × 10⁶ Ω when d exceeds 34 nm. The results indicate that the minimal number and size of contacts maximize R _eff , while increasing both contact number and diameter markedly reduces it. Furthermore, conditions such as reduced CNF waviness, thinner CNFs, a more substantial interphase, weak polymer tunneling resistivity, shorter tunneling distance, larger CNFs, and a lower percolation onset collectively act to minimize R _eff , thereby optimizing the composite electrical conductivity.