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基于梯度皱纹结构和涂覆银纳米线的聚二甲基硅氧烷的高灵敏度和宽量程柔性压力传感器。

High-Sensitivity and Wide-Range Flexible Pressure Sensor Based on Gradient-Wrinkle Structures and AgNW-Coated PDMS.

作者信息

Liu Xiaoran, Wang Xinyi, Xue Tao, Zhao Yingying, Zou Qiang

机构信息

School of Microelectronics, Tianjin University, Tianjin 300072, China.

Tianjin Flying Pigeon Group Co., Ltd., Tianjin 301600, China.

出版信息

Micromachines (Basel). 2025 Apr 15;16(4):468. doi: 10.3390/mi16040468.

Abstract

Flexible pressure sensors have garnered significant attention due to their wide range of applications in human motion monitoring and smart wearable devices. However, the fabrication of pressure sensors that offer both high sensitivity and a wide detection range remains a challenging task. In this paper, we propose an AgNW-coated PDMS flexible piezoresistive sensor based on a gradient-wrinkle structure. By modifying the microstructure of PDMS, the sensor demonstrates varying sensitivities and pressure responses across different pressure ranges. The wrinkle microstructure contributes to high sensitivity (0.947 kPa) at low pressures, while the PDMS film with a gradient contact height ensures a continuous change in the contact area through the gradual activation of the contact wrinkles, resulting in a wide detection range (10-50 kPa). This paper also investigates the contact state of gradient-wrinkle films under different pressures to further elaborate on the sensor's sensing mechanism. The sensor's excellent performance in real-time response to touch behavior, joint motion, swallowing behavior recognition, and grasping behavior detection highlights its broad application prospects in human-computer interaction, human motion monitoring, and intelligent robotics.

摘要

柔性压力传感器因其在人体运动监测和智能可穿戴设备中的广泛应用而备受关注。然而,制造兼具高灵敏度和宽检测范围的压力传感器仍然是一项具有挑战性的任务。在本文中,我们提出了一种基于梯度皱纹结构的涂覆有银纳米线的聚二甲基硅氧烷(PDMS)柔性压阻式传感器。通过改变PDMS的微观结构,该传感器在不同压力范围内表现出不同的灵敏度和压力响应。皱纹微观结构有助于在低压下实现高灵敏度(0.947 kPa),而具有梯度接触高度的PDMS薄膜通过逐渐激活接触皱纹确保接触面积的连续变化,从而实现宽检测范围(10 - 50 kPa)。本文还研究了梯度皱纹薄膜在不同压力下的接触状态以进一步阐述传感器的传感机制。该传感器在对触摸行为、关节运动、吞咽行为识别和抓握行为检测的实时响应方面的优异性能突出了其在人机交互、人体运动监测和智能机器人领域的广阔应用前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe24/12029205/c7873e06beab/micromachines-16-00468-g001.jpg

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