Novel graphene-based piezoresistive strain gauge rosettes for structural health monitoring

This article presents a novel and cost-effective method for developing graphene-based piezoresistive strain gauge rosettes tailored for structural health monitoring (SHM) applications. The rosettes were produced using a spray-coating technique with a waterborne paint matrix infused with graphene nanoplatelets (GNPs) as conductive fillers. Comprehensive characterization of the sensors was conducted, encompassing morphological, electrical, rheological, electromechanical, and dynamic properties. The rheological behavior of the polymer blend, with varying GNP and water contents, was optimized to achieve a suitable viscosity for uniform spray deposition. The electrical percolation threshold was established by gradually increasing the GNP content up to 4.12 vol.%. An optimal formulation containing 3.18 vol.% GNPs and 37.30 vol.% water with respect to paint was identified, yielding defect-free coatings with an electrical conductivity of approximately 9 S/m. The piezoresistive performance was evaluated through quasi-static three-point bending tests and dc electrical measurements, revealing a maximum gauge factor (GF) of ~27 at 0.9% strain. In addition, rosettes configured parallel and perpendicular to the applied strain direction were analyzed to extract the principal strains and their orientations. The experimental results were further validated via finite element simulations using COMSOL Multiphysics (Registered trademark). Dynamic testing was also performed on the GNP/paint-based rosette affixed to a polycarbonate plate to estimate the modal parameters through operational modal analysis (OMA), with the extracted natural frequencies closely matching those obtained from conventional strain rosettes. These findings demonstrate that the proposed GNP/paint-based strain rosette offers a scalable, reliable, and effective solution for multidirectional strain sensing in emerging SHM systems.