Excellent reversibility of resistive nanocomposite strain sensor composed of silver nanoflowers, polyurethane, and polyester rubber band

Composites Science and Technology(2022)

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摘要
Wearable conductive nanocomposite strain sensors have received considerable attention for rehabilitation and human motion detection. However, their practical application has been hindered by the irreversible resistance change upon stretching cycles. Here we report a resistive-type conductive nanocomposite strain sensor with a nearly perfect reversibility (maximum strain = 30%). Flower shaped silver nanoparticles (AgNFs) with enhanced surface area construct a conductive network as a key sensing element in stretchable polyurethane (PU) matrix. Furthermore, polyester elastic rubber band (PB) is chosen as a backbone to ensure perfect mechanical elasticity and durability. A fiber-type strain sensor (PB/AgNF-PU sensor) is synthesized by coating the elastic PB with the AgNF-PU sensing element. The PB/AgNF-PU sensor shows nearly perfect mechanical and electrical reversibility up to 30% strain. It also shows a high initial conductivity (6328 S/cm) and a gauge factor (32.08). As for application demonstrations, the PB/AgNF-PU sensor successfully carries out human motion detection, such as sitting, walking, and running, using a compact microcontroller equipped with wireless communication. The softness and flexibility of the PB/AgNF-PU sensor ensure conformal attachment on human skin, enabling the detection of subtle strain and angular change of knee. Furthermore, it does not restrict joint motion, unlike a conventional rigid brace equipped with an encoder, providing a breakthrough in free motion analysis. The accurate, comfort, and reversible PB/AgNF-PU sensor is synthesized by a facile and scalable process, assembling the high conductivity of AgNFs, stretchability of PU, and elasticity of PB. The PB/AgNF-PU sensor may find immediate applications in rehabilitation and human motion analysis.
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关键词
Nanocomposites,Nano particles,Sensing,Electro-mechanical behavior,Human motion detection
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