Search

In this paper, the internal structure and dielectric properties of unsaturated polyester resin-based neat and single-walled carbon nanotube reinforced composites were comprehensively evaluated with the fractal analysis using the Fast Fourier Transform (FFT). The greyscale images, bitmap (BMP) images and 3D tomographic images were obtained by converting the scanning electron microscope images of the materials. It was observed that the distributions of components in the resin for both materials are irregular and their surfaces exhibit anisotropic behaviors. The surface coating rate (SCR) and fractal dimensionality (FD) of the materials were also calculated using the power spectrum. It has been observed that the fractal dimensionality of the composites can be changed by the doping process and the fractalization of the nanotube doped sample increases compared to the pure material due to nanotube agglomeration, spatial distribution and the orientation. The increase in fractalization as a result of this agglomeration and orientation in carbon nanotubes explains the high dielectric constant values observed at low frequencies by increasing the number and size of carbon nanotubes clusters that act as micro capacitors in certain regions of the matrix. It has been reported that the calculations for the surface coverage ratios for both samples also support these results. [ABSTRACT FROM AUTHOR]

The electrical properties of composite materials over a wide frequency range are of great interest, not only for experimental applications, but also for theoretical studies such as fractal analysis. This study presents comparative analysis of alternating current (ac) conductivity and fractal structure characteristics in standard and single walled carbon nanotube (SWCNT) reinforced polymer composites based unsaturated polyester resin (UPR). The electrical characteristics of polymer matrices at 320 K have been analyzed as a function of frequency by impedance analysis method. It was found that the conductivity of the nanotube doped material in the dc conductivity region, which is the low frequency region, is independent of the frequency and takes a constant value. It was proved that conductivity obeys Jonscher's power law toward the high frequency region. The standard sample showed an insulating behavior that exhibits continuous increase with increasing frequency. The images of the samples were obtained by scanning electron microscope (SEM) to reveal the relationship between the conductivity of the materials and their fractal properties. All samples were converted to binary format for calculations. Cellular particle density for each sample was determined according to scaling theory. Then, the surface coverage ratio, fractal dimensions, cluster densities, average cluster sizes and critical interface exponent values of the samples were calculated and compared with different samples in the literature. It was determined that the coverage ratio and fractal dimension increased when carbon nanotubes were added. In addition, it was observed that the interface critical exponent decreased when the carbon nanotube was doped. [ABSTRACT FROM AUTHOR]

The present study aims to understand the relation between impedance characteristics and fractal behaviours. The pure and single-walled carbon nanotube (SWCNT) reinforced unsaturated polyester resin (UPR)-based composite specimens were produced by the hot press process with this aim. The Nyquist variation in the neat sample shows a straight line, which can describe the great resistance in the material and its insulating nature, while the Nyquist plots of the carbon nanotube doped sample show an almost semi-circular shape, indicating the presence of electrical conductivity. In addition, fractal analysis with statistical scaling method is used to determine the relationships between the superficial heteromorphology and electrical properties of samples. The surface particle coverage rates, fractal dimensions, cluster pattern structures, Feret diameters and Feret angles were calculated for samples. Feret angle decreases indicating that the distance between clusters is decreasing as coverage ratio, fractal dimension and Feret diameter increases. [ABSTRACT FROM AUTHOR]