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.
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