Numerical scaling approaches for the irreversible formation of carbon nanotube reinforced polyester-based nanocomposites

Abstract

The internal structure and characteristic properties of pure and carbon nanotube filled composites are closely dependent on the properties of the substances added for production, their weight% in the material, and the production process. The different properties of the components in the material and the variability of production parameters cause the observable surface structures of the produced samples to exhibit self-similar characteristics. This repetition behavior shapes the permeability properties of materials as well as morphological changes. In order to understand the multiple surface structuring of the materials and the characteristic changes it brings, the surfaces of the samples produced with the sheet molding compound (SMC) technique were examined using a scanning electron microscope (SEM). SEM analysis results revealed that the correlation length of the cluster size within the surface structure showed unique fractal scaling behaviors. Universal critical exponent values and fractal dimensions were calculated using the scaling method and numerical approaches to determine the change of the root mean square roughness (rms), which was used as a statistical measure of the surface change of the samples. It was found that the probability distribution in the model proposed for multicluster formation conforms on an exponential distribution and the structuring process of the samples is determined by the Poisson process. It is predicted that the structuring process involves an irreversible, physical and chemical mechanism.