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  5. All-Fabric Ultrathin Capacitive Sensor with High Pressure Sensitivity and Broad Detection Range for Electronic Skin

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Article
en
2021

All-Fabric Ultrathin Capacitive Sensor with High Pressure Sensitivity and Broad Detection Range for Electronic Skin

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0 Files

en
2021
Vol 13 (20)
Vol. 13
DOI: 10.1021/acsami.1c05478

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Pengtao Yu
Xin Li
Huayang Li
+7 more

Abstract

Flexible pressure sensors have emerged as an indispensable part of wearable devices due to their application in physiological activity monitoring. To realize long-term on-body service, they are increasingly required for properties of conformability, air permeability, and durability. However, the enhancement of sensitivity remains a challenge for ultrathin capacitive sensors, particularly in the low-pressure region. Here, we introduced a highly sensitive and ultrathin capacitive pressure sensor based on a breathable all-fabric network with a micropatterned nanofiber dielectric layer, an all-fabric capacitive sensor (AFCS). This all-fabric network endows a series of exceptional performances, such as high sensitivity (8.31 kPa–1 under 1 kPa), ultralow detection limit (0.5 Pa), wide detection range (0.5 Pa to 80 kPa), and excellent robustness (10 000 dynamic cycles). Besides, the all-fabric structure provides other properties for the AFCS, e.g., high skin conformability, super thinness (dozens of micrometers), and exceptional air permeability. Our AFCS shows promising potential in breathing track, muscle activity detection, fingertip pressure monitoring, and spatial pressure distribution, paving way for comfortable skinlike epidermal electronics.

How to cite this publication

Pengtao Yu, Xin Li, Huayang Li, Youjun Fan, Jinwei Cao, Hailu Wang, Zihao Guo, Xuejiao Zhao, Zhong Lin Wang, Guang Zhu (2021). All-Fabric Ultrathin Capacitive Sensor with High Pressure Sensitivity and Broad Detection Range for Electronic Skin. , 13(20), DOI: https://doi.org/10.1021/acsami.1c05478.

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Publication Details

Type

Article

Year

2021

Authors

10

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsami.1c05478

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