Analysis of an incomplete interphase in carbon nanofiber polymer composites: A new approach for conductivity improvement

While many nanocomposites have an incomplete interphase, this feature has not been fully explored concerning the conductivity for carbon nanofiber (CNF)/polymer samples (PCNFs). This paper models the incomplete interphase in PCNFs, represented by L_c, as the minimum CNF length necessary to achieve effective conduction transfer to the polymer matrix. The effective inverse aspect ratio and CNF concentration are functions of L_c. Also, percolation inception (ϕ_p) and network concentration in PCNFs are estimated through effective parameters. A simplified model is subsequently refined to predict PCNF conductivity, incorporating both the incomplete interphase and tunneling effect. Extensive experimental data validate the model's predictions. Furthermore, the impact of each parameter on PCNF conductivity is thoroughly analyzed to substantiate the proposed simulation. Insulative behavior is shown in samples with large tunneling distances (λ > 5.5 nm), low interphase conductivity (< 50 S/m), minimal interphase depth (t < 9 nm), L_c > 14 μm, or ϕ_p > 0.015. Hence, attaining better PCNF conductivity necessitates shorter tunneling distance, higher interphase conductivity, greater interphase depth, smaller L_c, and lower percolation inception.