Abstract. Nanocomposites were fabricated based on diglycidyl ether of bisphenol A (DGEBA), cured with triethylenetetramine (TETA) and filled with: a) high conductivity carbon black (CB) and b) amino-functionalized multiwalled carbon nanotubes (MWCNTs). The full dynamic mechanical analysis (DMA) spectra, obtained for the thermomechanical characterization of the partially cured DGEBA/TETA/CB and water saturated DGEBA/TETA/MWCNT composites, reveal a complex behaviour as the !-relaxation appears to consist of more than one individual peaks. By employing some basic calculations along with an optimization procedure, which utilizes the pseudo-Voigt profile function, the experimental data have been successfully analyzed. In fact, additional values of sub-glass transition temperature (T i ) corresponding to subrelaxation mechanisms were introduced besides the dominant process. Thus, the physical sense of multiple networks in the composites is investigated and the glass transition temperature T g is more precisely determined, as the DMA !-relaxation peaks can be reconstructed by the accumulation of individual peaks. Additionally, a novel term, the index of the network homogeneity (IH), is proposed to effectively characterize the degree of statistical perfection of the network.
In recent years, the production of municipal solid waste has constantly been increasing. Recycling is becoming more and more important, as it is the only way that we can have a clean and sustainable environment. Recycling, however, is a process that is not fully automated; large volumes of waste materials need to be processed manually. New and novel techniques have to be implemented in order to manage the increased volume of waste materials at recycling factories. In this paper, we propose a novel methodology that can identify common waste materials as they are being processed on a moving belt in waste collection facilities. An efficient waste material detection and classification system is proposed, which can be used in real integrated solid waste management systems. This system is based on a convolutional neural network and is trained using a custom dataset of images, taken on site from actual moving belts in waste collection facilities. The experimental results indicate that the proposed system can outperform existing algorithms found in the literature in real-world conditions, with 92.43% accuracy.
In the present work an epoxy/carbon nanotubes composite system is studied with the main focus on the effect of the network architecture on the thermophysical properties of the system. The fillers' modification plays an important role in the formation of a secondary crosslinking network, between the amine groups of the nanotubes and the epoxy rings of the prepolymer. The secondary network seems to affect the final properties of the product. The results indicate the existence of an interfacial layer around the filler particles and the coexistence of two networks. The discussion includes the effect of the filler content, the dispersion conditions and the architectural structure of the secondary network on the α-and β-relaxations corresponding to the associated temperatures Tg and Τβ and the thermodynamic behavior of the produced material.
The reinforcing role of clays in modern nanocomposites raises the question upon potential synergies with other fillers, in terms of their microwave properties and performance. To this effect, hybrid, multiphase composites are fabricated to comprise organomodified nanoclay (NC) and multiwalled carbon nanotubes (MWCNTs) or carbon black nanoparticles (CB) at varying concentrations in epoxy resin matrix (ER). The performed electromagnetic (EM) characterization in the 2-18-GHz band reveals that NC generally degrades the effective permittivity ε * eff of the NC/CB/epoxy composites, whereas for 2wt% NC a local ε * eff maximum is observed in the NC/MWCNT/epoxy system. This divergent impact of NC is attributed to different microstructural features affecting the dipolar dielectric polarization. Finally, the composites with high ε * eff contribute to the miniaturization of reflection reducing and shielding panels, since the respective return and transmission loss are found to be dominated by the destructive interference mechanism. For both topologies, the composite loaded with 2wt% NC and 0.5wt% MWCNT is evaluated as the most effective in attenuating the EM waves. Through the analysis of the microwave dielectric properties and the shielding mechanisms, the material design objectives emerge along with the potential of NC/carbon nanotubes composites for suppression of EM interference.
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