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This paper reports on an investigation of the critical parameters which determine the electrical and electromechanical properties of carbon nanotube (CNT) nanocomposites. For this purpose, a novel analytical model, based on the tunnelling mechanisms of CNTs, is proposed. Three dispersion parameters are introduced in the model to reflect the CNT aggregation state. Microscopy analysis and electrical and strain monitoring tests were carried out on CNT nanocomposites manufactured by toroidal stirring and three roll milling. It is observed that electrical conductivity is greatly affected by dispersion procedure as well as strain sensitivity, measured by the gauge factor (GF). Generally, well dispersed materials have higher conductivities and GF. In this regard, the aggregate ratio has a prevalent effect. Experimental data and theoretical predictions allow the correlation of dispersion parameters given by manufacturing procedures with electrical properties to develop highly sensitive nanocomposites. This demonstrates the potential and applicability of the proposed model.

The capabilities of Digital Light Processed CNT doped nanocomposites for electrothermally triggered selective shape memory have been explored. Here, selective shape memory enables fixing the temporary shape and recovering the original one of different regions of a specimen individually, without affecting the other regions. In this regard, the shape memory capabilities of different matrices based on mixtures of rigid and elastic resins, consisting in hard segments (HS) and soft segments (SS), respectively, doped with CNTs have been investigated. A decrease in the HS:SS ratio leads to a decrease in the glass transition temperature, which constitutes the transformation temperature needed for fixing the temporary shape and recovering the original one. However, the electrical conductivity experiences a sudden drop, reaching values below the percolation threshold at 0:100 samples. Therefore, only the 100:0 and 80:20 samples were valid for shape memory triggered by Joule's effect. Furthermore, selective shape memory tests were conducted by placing different electrodes throughout the material by dividing the specimen in one, two or three individual regions that could be activated selectively. Here, it has been observed that the shape recovery ratio was above 75% in every case, proving the potential of the proposed materials and technique for selective shape memory activation by Joule's heating.

The addition of functionalized graphene nanoplatelets (f-GNPs) into the epoxy resin of glass fiber multiscale composite materials creates an electrically conductive network. This electrical network is highly sensitive to strain induced in the material. For this reason, it is a competitive material to be used in structural health monitoring (SHM). Sensitivity of multiscale composite materials is ∼50 under tensile loads and the behavior under compression loads differs, making possible the detection of different load conditions. Independency of the strain rate is related to the enhanced interface between f-GNPs and the epoxy matrix due to functionalization. Additionally, the electrical behavior is reversible without the loss of efficiency in sensorial properties.

The incorporation of graphene nanoplatelets (GNPs) as a coating on glass fibre fabrics for strain monitoring applications was analysed. Non-functionalized and functionalized GNPs were used in order to study the effect of the functionalization in the morphology of the coating and the electrical behaviour of the material. In contrast with non-functionalized GNPs, when NH 2 -functionalized GNPs were used, the nanoparticles adapted to the surface of the fibres causing a major effectiveness of the electrical network created along the fibres, achieving an electrical conductivity in the order of 10 −2 S/m. The sensitivity values, obtained under tensile loads, reached values in the order of 840 up to 16400.

The mechanical and crack sensing capabilities of CFRP-metal Mode-II coupons and skin-stringer T-joints under bending conditions with carbon nanotube (CNT) doped adhesive films are explored. Different surface treatments of the aluminium substrate are tested (grit blasting and sandpaper brushing). Mode-II energy fracture slightly increases with CNT addition due to the nanoparticle toughening effect when the surface treatment is adequate. However, in the case of brushed specimens, the enhanced lubricant properties of CNTs leads to the promotion of weak interfaces between adhesive and metal substrate. The electrical resistance increases with the load nose displacement with a good correspondence to the crack length. A crack opening effect is herein noticed in the last stages of the Mode-II tests due to the difference between the stiffness of metal and CFRP adherents, which is reflected in a sudden increase of the electrical resistance. These results have been also validated by theoretical analysis. Electromechanical response of T-joints shows a similar behaviour with an increasing sensitivity when placing a CFRP stringer, due to a more prevalent crack opening observed in this type of specimens. Therefore, crack sensing capabilities are demonstrated at both coupon and sub-element level.

Carbon nanotubes (CNT) were added to epoxy/polycaprolactone (PCL) blends in order to get electrically conductive blends. As it was expected, an increase of CNT content promotes a higher electrical conductivity due to the creation of more electrical pathways. Furthermore, it was observed that the enhancement is also observed with increasing PCL content, reaching values of around 0.2 S/m for 0.2 wt % CNT and 20 wt % PCL samples, due to its effect on rheological properties of the mixture, which affect positively to the CNT dispersion process, thus leading to more homogeneous and well dispersed nanocomposites, as observed by microstructural analysis. Thermal conductivity also increases with CNT content but decreases with PCL addition due to its insulating properties. A study of the voltage required to reach the above-mentioned self-healing temperature for each material has been performed by thermography monitoring. It has been observed that the samples with the highest amount of both CNT and PCL, have the best resistive heating capabilities due to a higher thermoresistive efficiency of the electrical network, reaching temperatures above 100 °C, at voltages below 150 V.

The study carried out analyses the strain sensor capability of nanocomposites reinforced with different graphene nanoplatelets (GNPs) contents. Nanocomposites with GNPs content around the percolation threshold have shown high gauge factor values, around 65 at high strain. The dominant mechanism of the sensors, based on changes induced in the tunnel and contact resistance, was evaluated. Monitored GNP/epoxy based sensors have shown to be capable of discriminating between tensile and flexural strain modes as the configuration of the GNPs during the tests behaves differently. Flexural strains makes possible the creation of new electrically conductive paths meaning an apparent lower sensitivity while strain produced in a tensile test provokes the breakage of the tunnel or contact based conductive paths.

Standard Mode-I and skin-stringer sub-elements were manufactured using novel adhesive films reinforced with carbon nanotubes. Peeling tests were conducted to analyse the different crack propagation mechanisms. In this context, the influence of manufacturing methods and artificial defects is deeply explored. It was observed that the electrical resistance increased with crack length due to a breakage of electrical pathways, depending on manufacturing and induced defects. Co-bonded specimens showed a more stable behaviour due to a better interface between the adhesive and substrate than joints manufactured by secondary bonding. Moreover, by analysing the influence of artificial defects, it was observed that larger discontinuities induced more unstable electromechanical behaviours as there is a more prevalent breakage of electrical pathways. In this regard, samples with Teflon inserts showed sharper increases of electrical resistance than those previously treated with a liquid agent simulating a kissing bond. Therefore, the proposed technique shows a high potential and applicability for Structural Health Monitoring (SHM) of integrated composite structures.

Several conventional techniques for nanofiller dispersion (high shear mixing, calendering, or a combination of the two) based on applying shear mechanical forces were studied in order to analyze their efficiency in manufacturing epoxy resin reinforced with graphene nanoplatelets (GNPs). Both provide composites with uniform GNP distributions although the calendering process also induces partial exfoliation of graphene. High-shear mixing could induce the reduction of flakes’ lateral size due to breakage and the rolling of nanoplatelets. Several physical properties of manufactured composites were measured. The density and glass transition temperature increase for composites manufactured by the calendering method due to the steric hindrance of exfoliated graphene nanosheets. Finally, the thermal stability of resin is increased by the addition of GNPs. The degradation temperature is increased up to 20 °C for composites manufactured by the calendering method.