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Enhanced performance of 3D printed highly elastic strain sensors of carbon nanotube/thermoplastic polyurethane nanocomposites via non-covalent interactions

机译:通过非共价相互作用增强碳纳米管/热塑性聚氨酯纳米复合材料的3D打印高弹性应变传感器的性能

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摘要

Strain sensors based on conductive polymer composites have been widely investigated due to their excellent elasticity and sensitivity. Such sensors may be manufactured using additive manufacturing techniques but there are some challenges to overcome in terms of performance if this technique is to be used. In this work, a high-performance strain sensor of carbon nanotube/thermoplastic polyurethane (CNT/TPU) nanocomposites was printed by fused deposition modeling (FDM), and 1-pyrenecarboxylic acid (PCA) was introduced to non-covalently modify the CNTs and improve the polymer-nanofiller interactions. It is shown that the tensile and electrical properties of the modified composites are increased as a result of more uniform CNT dispersion. The 3D printed sensors demonstrate excellent properties with high gauge factor (GF = 117213 at a strain of 250%), large detectable strain (0-250%), good stability (up to 1000 loading/unloading cycles) and wide frequency response range of 0.01-1 Hz. Also, the strain sensing ability of the sensor is greatly improved with the introduction of PCA. The working mechanism of strain sensor was further studied based on the Simmons' tunneling theory. In addition, the sensor demonstrates the capability to monitor human body movements and voice, showing its potential for applications in intelligent robots and wearable electronics where customizability is demanded.
机译:基于导电聚合物复合材料的应变传感器因其出色的弹性和灵敏度而受到广泛研究。可以使用增材制造技术来制造这样的传感器,但是如果要使用该技术,则在性能方面要克服一些挑战。在这项工作中,通过融合沉积建模(FDM)印刷了碳纳米管/热塑性聚氨酯(CNT / TPU)纳米复合材料的高性能应变传感器,并引入了1- py羧酸(PCA)来非共价修饰CNT和改善聚合物-纳米填料的相互作用。结果表明,由于更均匀的CNT分散,改性复合材料的拉伸性能和电性能得以提高。 3D打印传感器显示出优异的性能,具有高应变系数(在250%应变下GF = 117213),可检测应变大(0-250%),良好的稳定性(高达1000个加载/卸载循环)和宽的频率响应范围0.01-1 Hz。另外,随着PCA的引入,传感器的应变感测能力大大提高。基于Simmons隧道理论,进一步研究了应变传感器的工作机理。此外,该传感器还具有监测人体运动和声音的能力,显示了其在要求可定制性的智能机器人和可穿戴电子设备中的应用潜力。

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