"Characterisation of the strain-sensing capability of carbon-nanotube embedded polymeric thin films manufactured with an industrial ink-jet printer"
Characterisation of the strain-sensing capability of carbon-nanotube embedded polymeric thin films manufactured with an industrial ink-jet printer
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The design and construction of aerospace structures is governed by the concept of lightweight design to maximize sustainable loads while increase fuel-efficiency. Despite the use of materials with outstanding mechanical properties, such as aluminium alloys or fibre-reinforced polymers, the monitoring of these structures is of grave importance to ensure the integrity and furthermore the safety of the structure during its service life. Next-generation Structural Health Monitoring systems themselves need to be lightweight and integrated into the structure to accomplish this task. The development of nanomaterial-based thin films with their unique properties made the design of inkjet-printed spatial strain sensors possible. However, the capabilities and qualities of such sensors is dependent on many factors including materials used and the ratio of components, utilised process for deposition of the material on the surface and post-processing procedure. The objective of this study was to develop and characterise a carbon nanotube based thin film strain sensor and to optimise its electrical properties by customising its conductivity. To accomplish this task, the composition of the ink in which the carbon nanotubes are dispersed as well as the printing process were modified in comparison to a previous study where the thin film was sprayed onto the surface . The effects of these modifications were studied by determination of the conductivity and piezoresistive behaviour of a sensor. To acomplish this, uniform strain was applied to the sensor and the resulting change in conductivity was measured by the method of Montgomery. Subsequently, strain was induced locally in the sensor. The MATLAB-based open-source software EIDORS was used to reconstruct the conductivity distribution during loading and visualise the results.