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CNT 包覆三维聚乙烯-聚丙烯 (ES)/PET 非织造基柔性压力传感器的制备及性能  ( EI收录)  

Preparation and performance of CNT impregnating 3D ethylene-propylene side by side (ES)/PET nonwoven-based flexible pressure sensors

文献类型:期刊文献

中文题名:CNT 包覆三维聚乙烯-聚丙烯 (ES)/PET 非织造基柔性压力传感器的制备及性能

英文题名:Preparation and performance of CNT impregnating 3D ethylene-propylene side by side (ES)/PET nonwoven-based flexible pressure sensors

作者:Gao, Xing[1]; Zhang, Rui[1]; Ying, Di[1]; Zheng, Yingying[2]; Wang, Jian[1,2]; Zou, Zhuanyong[1,2]

机构:[1] Key Laboratory of Clean Dyeing and Finishing Technology of Zhejiang Province, Shaoxing University, Shaoxing, 312000, China; [2] Shaoxing Key Laboratory of High Performance Fibers & Products, Shaoxing University, Shaoxing, 312000, China

年份:2025

卷号:42

期号:4

起止页码:1935

外文期刊名:Fuhe Cailiao Xuebao/Acta Materiae Compositae Sinica

收录:EI(收录号:20251418172222)

语种:中文

外文关键词:Gluing - Impregnation - Physiological models - Polyethylenes - Pressure sensors - Reinforced plastics - Sports medicine - Weaving

外文摘要:To address the challenges associated with low sensitivity, complex production processes, and insufficient breathability of flexible sensors, this study developed a three-dimensional nonwoven material made of polyethylene-polypropylene (Ethylene-propylene side by side, ES)/polyester (PET) fibers through needle punching and thermal bonding techniques. The material was then impregnated with carbon nanotubes (CNT), leading to the successful development of a high-performance CNT impregnating three-dimensional thermally bonded nonwoven-based pressure sensor. The impact of different CNT impregnation processes on sensor performance was comparatively analyzed. The findings indicate that the three-dimensional ES/PET nonwoven-based flexible pressure sensor exhibits a high sensitivity of up to 0.375 kPa?1 and a detection range of 0-214.53 kPa. After 2 100 compression cycles, the sensor demonstrate excellent stability and repeatability, with a response time of 48 ms and a recovery time of 122 ms. In practical applications, this sensor can accurately identify subtle physiological activities such as breathing, swallowing, and finger bending, showing potential for widespread use in sports, medical, and virtual reality fields. ? 2025 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

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