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• W2955475635 abstract "A nanocomposite-based sensor ink made from carbon black and polyvinyl pyrrolidone was developed for fabricating a new breed of sensor by an inkjet printing approach, to accommodate the general purposes of structural health monitoring. This ink can be directly deposited onto the surface of various substrates or engineering structures such as polyimide film via computer-aided design to configure nanocomposite sensor arrays or dense sensor networks. Strong structure adaptability and high flexibility make this sensor a promising candidate to alternate traditional piezoresistive and piezoelectric sensors, in signal acquisition of dynamic disturbance on complex engineering structures. Lightweight and without the need to use wires or cables, the printed sensor network significantly reduces the weight and volume penalty imposed on the host structures, even when the network is deployed at a large scale. It also minimizes the possibility of exfoliation of the sensors from the host structure under cyclic load. The printed pattern distinguishes superior performance in the perception of acousto-ultrasonic signals from static up to 500 kHz, with high signal-to-noise ratio, sensitivity, and fidelity. By virtue of the tunneling current between two adjacent nanoparticles that are in close proximity (within several nanometers), the printed sensor network is capable of perceiving ultrasonic waves. The fabrication process of the sensor network does not entail any specially made printing facilities, and the carbon black/polyvinyl pyrrolidone hybrid can easily be injected into an inkjet cartridge for printing. Several confirmatory experiments and a proof-of-concept test were carried out based on the printed sensor network to validate the capability of the printed sensor for structural health monitoring." @default.
• W2955475635 created "2019-07-12" @default.
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• W2955475635 date "2019-07-01" @default.
• W2955475635 modified "2023-10-17" @default.
• W2955475635 title "An ultra-thin printable nanocomposite sensor network for structural health monitoring" @default.
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• W2955475635 doi "https://doi.org/10.1177/1475921719859338" @default.
• W2955475635 hasPublicationYear "2019" @default.
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