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A Selective-Response Bioinspired Strain Sensor Using Viscoelastic Material as Middle Layer

Authors :
Wang Kejun
Shichao Niu
Meng Xiancun
Zhiwu Han
Dakai Wang
Yuqiang Fang
Guoliang Ma
Liu Linpeng
Jingxiang Wang
Tao Sun
Junqiu Zhang
Zhang Changchao
Luquan Ren
Source :
ACS Nano. 15:19629-19639
Publication Year :
2021
Publisher :
American Chemical Society (ACS), 2021.

Abstract

Flexible strain sensors have an irreplaceable role in critical and emerging fields, such as electronic skins, flexible robots, and prosthetics. Although numerous efforts have been made to improve sensor sensitivity to meet specific application scenarios, the signal-to-noise ratio (SNR) is an extremely critical and non-negligible indicator, which takes into account higher sensitivity, meaning that they can also detect the noise signals with high sensitivity. Coincidentally, scorpions with ultrasensitive vibration sensilla also face such a dilemma. Here, it is found that the scorpion ingeniously uses the viscoelastic material in front of its slit sensilla to realize efficient preprocessing of the signal. Its mechanism is that the loss factor of materials changes with frequency, affecting energy storage and transmission. Inspired by this ingenious strategy, a bioinspired strain sensor insensitive to a low strain rate was designed using a two-step template transfer method. As a result, its relative change in resistance reached 110% under the same strain (0.3197%) but with different strain rates (0.1 Hz and ∼20 Hz). The noncontact vibration experiments also show different responses to low-frequency vibration and high-frequency impact. Moreover, it can also be used as a typical flexible strain sensor. Under the tensile state, it has a gauge factor (GF) as high as 4596 upon 0.6% strain, and the response time is 140 ms. Therefore, it is expected that this strain sensor will be used in many important ultraprecision measurement fields, especially when the measured signal is small.

Details

ISSN :
1936086X and 19360851
Volume :
15
Database :
OpenAIRE
Journal :
ACS Nano
Accession number :
edsair.doi.dedup.....d61268aaeca9b07122e34310247964d9
Full Text :
https://doi.org/10.1021/acsnano.1c06843