Pressure Sensors With Ultrahigh Sensitivity Inspired by Spider Slit Sensilla

灵敏度(控制系统) 材料科学 算法 航程(航空) 符号 量子隧道 计算机科学 光电子学 复合材料 数学 电子工程 工程类 算术
作者
Yan Li,Qien Xue,Zongzheng Zhang,Yufu Bian,Biaobing Jin,Fuling Yang
出处
期刊:IEEE Sensors Journal [IEEE Sensors Council]
卷期号:23 (11): 11729-11737 被引量:2
标识
DOI:10.1109/jsen.2023.3266753
摘要

The crack-based ultrasensitive sensor inspired by the spider has an efficient electro-mechanical conversion mechanism and shows superiority in extremely small movement monitoring. However, a complete explanation of the sensing mechanism and the theoretical study of the optimization of the crack structure is still a challenge. Here, we simplify the bionic sensing layer into a parallel equal-length crack structure and implement the mechanical analysis using the method of complex variable function, from which, three typical stages of the crack structure under different force levels are summarized, which are overlap, transition, and tunneling, respectively. The sensing characteristics at each stage are studied, a pressure-resistance model is established, and also the influence law of the crack parameters on the sensitivity and measuring range is investigated, all to support the design of a bionic crack pressure sensor aiming for ultrahigh sensitivity. To fabricate the pressure sensor, the elastic substrate for the cracks is successfully prepared by gold ion sputtering, and the morphology of the metal cracks is precisely controlled using a photolithography-assisted method. According to experiments, the fabricated pressure sensor shows an ultrahigh sensitivity of $2.39\times107$ kPa $^{{-{1}}}$ in the range of 0.28–0.35 kPa, as well as pleasing repeatability within at least 1000 testing cycles. The sensitivity of the bionic crack pressure sensor is desirable compared with a group of recently reported pressure sensors. Combining with other benefits of stability and reliable fabrication, our bionic crack pressure sensor is attractive for ultraprecision applications, such as human–machine interfaces and biological health monitoring.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
yemu3zhi应助张张采纳,获得10
刚刚
群青完成签到 ,获得积分10
刚刚
颖宝老公完成签到,获得积分0
刚刚
彭语诺发布了新的文献求助10
1秒前
ding应助aiya采纳,获得10
1秒前
草草发布了新的文献求助10
2秒前
Calvin发布了新的文献求助10
2秒前
和谐的小小完成签到,获得积分10
3秒前
pxl99567完成签到,获得积分10
3秒前
m78完成签到 ,获得积分10
3秒前
忧郁的涛完成签到,获得积分10
3秒前
浮游应助时荒采纳,获得10
4秒前
4秒前
思源应助JOE采纳,获得10
4秒前
无情的谷兰完成签到,获得积分10
5秒前
开朗书本完成签到 ,获得积分20
5秒前
yurenxiaojie完成签到,获得积分20
5秒前
粒子完成签到,获得积分10
6秒前
慕青应助伶俐惜灵采纳,获得10
6秒前
英姑应助唐磊采纳,获得10
8秒前
8秒前
科目三应助wangxuezhibuct采纳,获得10
8秒前
霸气千易发布了新的文献求助30
8秒前
9秒前
小魏完成签到,获得积分10
10秒前
11秒前
无情寻芹完成签到,获得积分20
11秒前
11秒前
雨雨子完成签到,获得积分10
13秒前
13秒前
无物发布了新的文献求助50
13秒前
asdf完成签到,获得积分10
14秒前
JKL完成签到,获得积分10
15秒前
15秒前
谢大喵应助Leo采纳,获得10
15秒前
xinzhao完成签到,获得积分10
16秒前
姽婳wy发布了新的文献求助10
18秒前
斗罗大陆完成签到,获得积分10
18秒前
这小猪真帅完成签到,获得积分10
18秒前
谢大喵应助高兴的雅山采纳,获得10
18秒前
高分求助中
Adhesion Science: Principles & Practice 1234
Signals, Systems, and Signal Processing 610
Petrology and Plate Tectonics,2025 400
Burger's Medicinal Chemistry and Drug Discovery 400
New directions for experimental lessons in science teaching: Myth, Mystery, Necessity? by Emily K. da Silva Cunha Souto (Author), Flávia Lins Silva (Author) 333
Scientific experimentation in the classroom: Comparison between genetic-Socratic-exemplary teaching and workshop teaching by Ingrid Hofer (Author) 333
Programming for Chemical Engineers Using C, C++, and MATLAB 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6718898
求助须知:如何正确求助?哪些是违规求助? 8456049
关于积分的说明 18052913
捐赠科研通 5969715
什么是DOI,文献DOI怎么找? 2995456
邀请新用户注册赠送积分活动 1971526
关于科研通互助平台的介绍 1924450