Strain sensors are one of the most widely used transducers for structural health monitoring, since strain can provide rich information regarding structural integrity. Recently, it has been shown that thin film sensors that incorporate nanomaterials can be engineered to possess unique properties, such as flexibility, high sensitivity, and distributed sensing capabilities, to name a few. To date, a plethora of different nanomaterials have been explored for fabricating strain sensors, such as by using conductive polymers, metal nanowires, and carbon nanotubes, among others. The aim of this work is to leverage the unique properties of graphene to fabricate next-generation thin film strain sensors. While graphene exhibits impressive mechanical and electrical properties, it remains challenging to harness these properties for sensing, primarily because of difficulties associated with high-quality synthesis and to incorporate them in a scalable fashion. In this study, few-layered graphene nano-sheets (GNS) were first synthesized using a low-cost, liquid-phase exfoliation technique. Second, GNS was dispersed in an aqueous solution with a low-concentration polymer acting as the dispersing agent. Third, the dispersion was printed onto flexible polymer substrates to form complex geometrical patterns, such as strain rosettes. Then, the electrical and electromechanical properties of the printed thin film sensors were characterized. It was found that the strain rosettes could resolve multi-axial strains applied during coupon tests. Overall, the GNS-based strain sensors showed excellent signal-to-noise ratio, stable sensing performance, high strain sensitivity, and remarkable reproducibility.
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Printed Graphene-Based Strain Sensors for Structural Health Monitoring
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Wang, L, Loh, KJ, Mousacohen, R, & Chiang, W. "Printed Graphene-Based Strain Sensors for Structural Health Monitoring." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring. Snowbird, Utah, USA. September 18–20, 2017. V002T05A002. ASME. https://doi.org/10.1115/SMASIS2017-3839
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