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基于固液摩擦起电的高灵敏度柔性自供电压力传感器

High-Sensitivity Flexible Self-Powered Pressure Sensor Based on Solid-Liquid Triboelectrification.

作者信息

Wu Yu, Lei Rui, Cao Jie, Chen Si, Zhong Yan, Song Jie, Jin Zhelin, Cheng Guanggui, Ding Jianning

机构信息

Institute of Intelligent Flexible Mechatronics, Jiangsu University, Zhenjiang 212013, P. R. China.

出版信息

ACS Sens. 2025 Mar 28;10(3):2347-2357. doi: 10.1021/acssensors.5c00165. Epub 2025 Mar 18.

DOI:10.1021/acssensors.5c00165
PMID:40101150
Abstract

Self-powered sensors based on triboelectric nanogenerators (TENG) possess advantages such as lightweight, small size, and low cost. However, the trade-off among response time, sensitivity, and wear resistance of the triboelectric layer in such sensors remains unresolved. In this paper, a hydrophobic triboelectric layer was prepared using polydimethylsiloxane (PDMS) doped with polytetrafluoroethylene (PTFE), generating triboelectric signals through the contact and separation of the triboelectric layer with water. Compared to the traditional solid-solid triboelectric charging method in self-powered sensors, this sensor primarily relies on solid-liquid triboelectric charging, effectively avoiding the wear issues caused by traditional solid-solid triboelectric charging. Simultaneously, thanks to the solid-liquid contact mode, the response time of the self-powered sensor is significantly improved, and it maintains high sensitivity under extremely small trigger forces. Finally, this paper demonstrates the application of this self-powered sensor in scenarios such as detecting human joint movements, mechanical finger states, and robotic hand grasping states, showing its promising application prospects in the field of intelligent monitoring.

摘要

基于摩擦纳米发电机(TENG)的自供电传感器具有重量轻、尺寸小和成本低等优点。然而,此类传感器中摩擦电层在响应时间、灵敏度和耐磨性之间的权衡仍未得到解决。本文采用掺杂聚四氟乙烯(PTFE)的聚二甲基硅氧烷(PDMS)制备了一种疏水性摩擦电层,通过摩擦电层与水的接触和分离产生摩擦电信号。与自供电传感器中传统的固-固摩擦起电方法相比,该传感器主要依靠固-液摩擦起电,有效避免了传统固-固摩擦起电引起的磨损问题。同时,由于固-液接触模式,自供电传感器的响应时间显著提高,并且在极小的触发力下仍保持高灵敏度。最后,本文展示了这种自供电传感器在检测人体关节运动、机械手指状态和机器人手抓握状态等场景中的应用,显示出其在智能监测领域广阔的应用前景。

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