ABSTRACT
This study develops a model for electrical conductivity of polymer carbon nanofiber (CNF) nanocomposites (PCNFs), which includes two steps. In the first step, Kovacs model is developed to consider the CNF, interphase and tunneling regions as dissimilar zones in the system. In the second step, simple equations are expressed to estimate the resistances of interphase and tunnels, the volume fraction of CNF and percolation onset. Although some earlier models were proposed to predict the electrical conductivity of PCNFs, developing of Kovacs model causes a better understanding of the effects of main factors on the nanocomposite conductivity. The developed model is supported by logical influences of all factors on the conductivity and by experimented conductivity of several samples. The calculations show good accordance to the experimented data and all factors rationally manage the conductivity of PCNFs. The highest conductivity of PCNF is gained as 0.019 S/m at the lowest ranges of polymer tunnel resistivity (ρ = 500 Ω m) and tunneling distance (d = 2 nm), whereas the highest levels of these factors (ρ > 3000 Ω m and d > 6 nm) cannot cause a conductive sample. Also, high CNF volume fraction, poor waviness, long and thin CNF, low "k", thick interphase, high CNF conduction, high percentage of percolated CNFs, low percolation onset and high interphase conductivity cause an outstanding conductivity in PCNF.
ABSTRACT
There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)-polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation onset, interphase thickness, CNF waviness, tunneling length among nanoparticles, and the fraction of the networked CNF. The outputs of the developed model correctly agree with the experimentally measured conductivity of several samples. Additionally, parametric analyses confirm the acceptable impacts of main factors on the conductivity of composites. A higher conductivity is achieved by smaller waviness and lower radius of CNFs, lower percolation onset, less tunnel distance, and higher levels of interphase depth and fraction of percolated CNFs in the nanocomposite. The maximum conductivity is obtained at 2.37 S/m by the highest volume fraction and length of CNFs.
ABSTRACT
We studied the effects of temperature on the interplay between dewetting and phase separation at shallow and deep depths at two-phase temperatures in PS/PVME polymer blend thin films. Optical microscopy, AFM measurements, and ellipsometry analysis were performed to investigate the dewetting behavior of the films. At the deep quench depth (phase separation temperature of 115 °C), a two-layer film formed, consisting of a thin PVME layer directly on the surface of a silicon wafer (as the wetting layer) and a bulk layer which was the upper layer. In the bulk layer, the phase separation mechanism was controlled by an apparent nucleation and growth mechanism, which was driven by entropic and anisotropic limitations rather than thermodynamic preferences. After about 106 min of annealing, liquid-liquid dewetting occurred in the interface of the formed layers, triggered by Laplace pressure differences. However, at the shallow quench depth (phase separation temperature of 95 °C), a tri-layered structure formed in the thin films and concentration fluctuations at the interfaces of the formed layers triggered surface fluctuations and instabilities (dewetting phenomenon).
