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The authors would like also to thank to Micronsense-Metrologia Industrial (Leiria, Portugal) for the μCT analysis. The authors would also like to thank Prof. Catarina Santos for granting access to the MicroLab - Electron Microscopy Laboratory (Instituto Superior Técnico) for the SEM analyses. Structural Health Monitoring systems assess the part's current condition. This can be performed with a monitoring system comprising sensors, on the surface or embedded, in the monitored parts. However, surface sensors are subject to damage, and embedding the sensors may result in a weakened part. An innovative Self-Sensing Material and its manufacturing process were developed and are presented herein. As proof of concept, Barium Titanate particles were introduced and dispersed into an AA5083-H111 part by Friction Stir Processing (FSP). The particles’ distribution and concentration was evaluated by a set of characterization techniques, demonstrating that greater concentrations, grant enhanced sensitivity to the material. The use of FSP and the embedded particles improved the part’s mechanical behaviour in the processed zone. The sensorial properties were assessed and the response to a set of dynamic loads was measured, being coherent with the solicitations provided. The developed self-sensing material revealed an electrical sensitivity of 12.0 × 10-4 uV/MPa. publishersversion published

Increasing demand for structural health monitoring in space highlights the need to make the creation of these systems more accessible. This study investigates the potential of additive manufacturing to achieve this goal by characterizing a self-sensing material made of a commercially available 3D-printed continuous carbon fibre filament. The results demonstrate the feasibility of converting the filament into a strain sensor with improved sensitivity compared to conventional foil strain gauges. Mechanical and electromechanical properties of the self-sensing material were characterized, including an ultimate tensile strength of 45.09 ± 3.45 MPa, a failure strain of 38.93 ± 3.41%, and a base resistance of 759.11Ω. The tensile gauge factor was calculated to be 467.06 ± 375.90 within the strain range of 0% to 3.8% with a linearity (R2) of 0.93. For the first time, a systematic literature review compares mechanical and electromechanical properties to enable material selection for mechanical design incorporating self-sensing material. The study highlights that the spread of material properties in a group of materials indicates how well-developed a material is for self-sensing purposes. This study advances our understanding of the feasibility of using additive manufacturing to create self-sensing materials for structural health monitoring systems and opens up new avenues for further research.

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Novel nanocomposite smart multifunctional materials are emerging as promising technological advances in construction industry, where thermal-energy efficiency needs should meet environmental sustainability and mechanical performance requirements. In this view, new cement-based materials showed encouraging results in terms of added functional properties combining all the above mentioned capabilities with electrical conductivity and self-sensing potential for a variety of field scopes, e.g. vibration measurements, damage detection, structural health monitoring, electromagnetic shielding, self-heating pavements for deicing and more. The present paper deals with the development and multipurpose experimental characterization of cement-based materials doped with different carbon nanoinclusions consisting of: multi-walled carbon nanotubes, carbon nanofibers, carbon black, and graphene nanoplatelets. The study investigates morphology, optical features, thermal characteristics, electrical properties and strain-sensing capability of the different composites, through a campaign of in-lab experimental measurements. The results highlight the peculiar behavior of each composite material, which is strictly related to the adopted nanoinclusions, that reveal to be suitable for specific purposes. In particular, all carbon nanoinclusions are seen to reduce solar reflectance capability, while they produce negligible variations in thermal emittance. Graphene nanoplatelets represent the most effective nanoinclusion to increase thermal conductivity and diffusivity, which is related to their structural and geometrical characteristics and better capability to distribute the thermal wave. Consistently, the same graphene samples produce the largest electrical conductivity and capacitance. However, multi-walled carbon nanotubes, even though providing comparatively smaller contributions to electrical conductivity, are seen to be the best nanoinclusions for providing strain-sensing capabilities to the cement-based composites.