RESUMO
The influence of the average surface area of different graphene nanoplatelets (GNP) on the thermo-electrical behaviour, associated with Joule heating, and the attenuation of electromagnetic signals of epoxy composites has been studied, analysing the effect of the morphology obtained as a function of the dispersion time by ultrasonication and the GNP content added. Gravity moulding was used as the first stage in the scaling-up, oriented to the industrial manufacture of multilayer coatings, observing a preferential self-orientation of nanoparticles and, in several conditions, a self-stratification too. The increase of sonication time during the GNP dispersion provides a decrease in the electrical conductivity, due to the GNP fragmentation. Instead, the thermal conductivity is enhanced due to the higher homogeneous distribution of GNPs into the epoxy matrix. Finally, the lower surface area of GNPs reduces the thermal and electrical conductivity due to a greater separation between nanosheets. Regarding the study of the attenuation of electromagnetic waves, it has been discovered that in the frequency range from 100 Hz to 20 MHz, this attenuation is independent of the direction of analysis, the type of graphene, the sonication time, and the state of dispersion of the nano-reinforcement in the matrix. Furthermore, it has also been observed that the conservation of the constant shielding values for the three types of GNPs are in a range of average frequencies between 0.3 and 3 MHz.
RESUMO
The influence of manufacturing parameters of filament extrusion and extrusion-based Additive Manufacturing (AM), as well as different post processing techniques, on the electrical conductivity of 3D printed parts of graphene nanoplatelets (GNP)-reinforced acrylonitrile butadiene styrene (ABS) has been analyzed. The key role of the manufacturing parameters to obtain electrically conductive filaments and 3D printed parts has been demonstrated. Results have shown that an increase in extrusion speed, as well as lower land lengths, induces higher extrudate swelling, with the consequent reduction of the electrical conductivity. Additionally, filaments with lower diameter values, which result in a higher surface-to-cross-section ratio, have considerably lower electrical conductivities. These factors tune the values of the volume and surface electrical conductivity between 10-4-100 S/m and 10-8-10-3 S/sq, respectively. The volume and surface electrical conductivity considerably diminished after 3D printing. They increased when using higher printing layer thickness and width and were ranging between 10-7-10-4 S/m and 10-8-10-5 S/sq, respectively. This is attributed to the higher cross section area of the individual printed lines. The effect of different post processing (acetone vapor polishing, plasma and neosanding, which is a novel finishing process) on 3D printed parts in morphology and surface electrical conductivity was also analyzed.
RESUMO
The electrical response of NH2-functionalized graphene nanoplatelets composite materials under strain was studied. Two different manufacturing methods are proposed to create the electrical network in this work: (a) the incorporation of the nanoplatelets into the epoxy matrix and (b) the coating of the glass fabric with a sizing filled with the same nanoplatelets. Both types of multiscale composite materials, with an in-plane electrical conductivity of ~10-3 S/m, showed an exponential growth of the electrical resistance as the strain increases due to distancing between adjacent functionalized graphene nanoplatelets and contact loss between overlying ones. The sensitivity of the materials analyzed during this research, using the described procedures, has been shown to be higher than commercially available strain gauges. The proposed procedures for self-sensing of the structural composite material would facilitate the structural health monitoring of components in difficult to access emplacements such as offshore wind power farms. Although the sensitivity of the multiscale composite materials was considerably higher than the sensitivity of metallic foils used as strain gauges, the value reached with NH2 functionalized graphene nanoplatelets coated fabrics was nearly an order of magnitude superior. This result elucidated their potential to be used as smart fabrics to monitor human movements such as bending of fingers or knees. By using the proposed method, the smart fabric could immediately detect the bending and recover instantly. This fact permits precise monitoring of the time of bending as well as the degree of bending.
