Strain monitoring is of great interest in order to check components structural life, to prevent catastrophic failures, and, possibly, to predict residual life in case of unexpected events. In this study, strain sensing epoxy-based coatings containing carbon nanotubes (MWCNTs), graphene nanoplatelets (GNPs), and a mix of the two (MWCNT+GNP) have been produced, with the same initial electrical resistivity, and applied on glass fiber reinforced composites. Morphological, mechanical, and electrical tests have been then performed evaluating the resistance variation and the strain sensing performance of the sensors. A theoretical model to relate the resulting gauge factors to the different types of nanofillers has been applied. The results showed that all systems present a strain sensing performance with different gauge factors (and hence sensitivity) at low strain: GNP samples showed the highest gauge factor (10.3), MWCNT samples the lowest (1.5), and the mixed system lies in the middle (4.3). From analytical analysis, the value of initial distance among conductive particles was found to be 0.3 nm in the case of MWCNT and 1.2 nm for GNP, explaining why the gauge factors of the produced sensors are different.

The health monitoring of structures is of great interest in order to check components’ structural life and monitor damages during operation. Self-monitoring materials can provide both the structural and monitoring functionality in one component and exploit their piezoresistive behavior, namely, the variation of electrical resistivity with an applied mechanical strain. In this work, self-monitoring plies were developed to be inserted into glass-fiber reinforced epoxy-based laminates in order to achieve structural monitoring. Nanocomposite epoxy-based resins were developed employing different contents of high surface area carbon black (CB, 6 wt%) and multiwall carbon nanotubes (MWCNT, 0.75 and 1 wt%), and rheologically and thermomechanically characterized. Self-monitoring plies were manufactured by impregnating glass woven fabrics with the resins, and were laminated with non-sensing plies via a vacuum-bag process to produce sensored laminates. The self-monitoring performance of the laminates was assessed during monotonic and cyclic three-point bending tests, as well as ball drop impact tests. A higher sensitivity was found for the CB-based systems (Gauge Factor 6.1), while MWCNTs (0.55 and 1.04) ensure electrical percolation at lower filler contents, as expected. The systems also showed the capability of being used to predict residual life and damage occurred under impact.

In this paper, poly-ether-ether-ketone (PEEK) carbon-nanotube (CNT) self-monitoring composites at different levels of filler loading (i.e., 3, 5 and 10% by weight) have been extruded as 3D-printable filaments, showing gauge factor values of 14.5, 3.36 and 1.99, respectively. CNT composite filaments of 3 and 5 wt% were 3D-printed into tensile samples, while the PEEK 10CNT filament was found to be barely printable. The 3D-printed PEEK 3CNT and PEEK 5CNT composites presented piezo-resistive behavior, with an increase in electrical resistance under mechanical stress, and showed an average gauge factor of 4.46 and 2.03, respectively. Mechanical tests highlighted that 3D-printed samples have a laminate-like behavior, presenting ultimate tensile strength that is always higher than 60 MPa, hence they offer the possibility to detect damages in an orthogonal direction to the applied load wit high sensitivity.