Exploiting the self-sensing capabilities of buckypapers for in-situ monitoring of impacts and compression after impact on GFRP panels

This paper delves into the application of buckypaper (BP) in enhancing the development of multifunctional Glass-Fibre Reinforced Polymers (GFRPs) integrated with carbon nanotubes (CNTs) for use in Structural Health Monitoring (SHM) applications. The growing demand for composite materials, driven by their outstanding mechanical properties and cost-effectiveness, has spurred the search for innovative damage-sensing techniques. In this context, CNT-based nanocomposites have emerged as a promising alternative due to their piezoresistive properties, providing real-time deformation and damage monitoring capabilities. This study investigates the fabrication and performance of CNT-doped GFRP materials featuring varying CNT concentrations. Tensile tests confirm that BP integration does not compromise mechanical strength, with the resultant sensing network demonstrating heightened sensitivity to strain and early damage detection capabilities. Low-Velocity Impact (LVI) tests show CNTs’ ability to detect dynamic events, characterised by distinct resistance variations linked to impact-induced damage. Compression After Impact (CAI) tests provide additional evidence of BP’s potential for damage detection, highlighting resistance variations associated with compression, buckling and complete specimen failure. These findings highlight the potential of buckypaper-based CNT composites for in-situ SHM applications. The ease of application, absence of CNT agglomeration and minimal impact on host material properties make BP an appealing choice for various industrial applications. • Buckypapers can sense microdamage formation around 50 MPa. • Impact monitoring capabilities are not influenced by buckypaper’s location. • Buckling onset is detected by buckypapers placed far from the damage site. • Only 60 gsm buckypapers could detect buckling, even if placed close to the damage. • 60 gsm buckypapers guarantee the best monitoring performance.