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
刚刚
aganer完成签到,获得积分10
1秒前
Ava应助小宝真的嘴硬采纳,获得10
1秒前
1秒前
哒哒发布了新的文献求助10
2秒前
佟鹭其完成签到 ,获得积分10
2秒前
4秒前
aganer发布了新的文献求助10
4秒前
xiaoma完成签到,获得积分10
6秒前
研友_LN3NWn发布了新的文献求助10
6秒前
7秒前
8秒前
ZM发布了新的文献求助10
8秒前
吴学仕发布了新的文献求助10
9秒前
12秒前
科研通AI6.4应助嘻嘻采纳,获得10
12秒前
田様应助nnn采纳,获得10
12秒前
没时间解释了完成签到 ,获得积分10
13秒前
李志刚发布了新的文献求助10
13秒前
香蕉觅云应助lili采纳,获得10
14秒前
cdercder应助Lny采纳,获得10
14秒前
jack完成签到,获得积分10
14秒前
15秒前
Camellia发布了新的文献求助10
15秒前
哒哒完成签到,获得积分10
17秒前
传奇3应助Sunny采纳,获得30
17秒前
失眠的霸完成签到,获得积分10
19秒前
Y_Y应助眼睛大板凳采纳,获得10
20秒前
lmhytr发布了新的文献求助10
20秒前
22秒前
酷波er应助Munchr1采纳,获得10
22秒前
科研通AI6.3应助单薄烤鸡采纳,获得10
23秒前
23秒前
树德完成签到,获得积分10
24秒前
洁净板栗完成签到,获得积分10
24秒前
Marpple完成签到,获得积分10
25秒前
25秒前
李志刚完成签到,获得积分10
26秒前
27秒前
27秒前
高分求助中
Signals, Systems, and Signal Processing 610
Annie Ernaux: De la perte au corps glorieux 600
Petrology and Plate Tectonics,2025 500
Circular Polar Constellations Providing Continuous Single or Multiple Coverage Above a Specified Latitude 400
Burger's Medicinal Chemistry and Drug Discovery 400
Probability and Stochastic Processes 333
New directions for experimental lessons in science teaching: Myth, Mystery, Necessity? by Emily K. da Silva Cunha Souto (Author), Flávia Lins Silva (Author) 333
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 6742762
求助须知:如何正确求助?哪些是违规求助? 8473912
关于积分的说明 18075779
捐赠科研通 6012453
什么是DOI,文献DOI怎么找? 3003900
邀请新用户注册赠送积分活动 1980422
关于科研通互助平台的介绍 1945325