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金属厚度对基于裂纹的传感器灵敏度的影响。

Effect of Metal Thickness on the Sensitivity of Crack-Based Sensors.

机构信息

Department of Mechanical Engineering, Ajou University, San 5, Woncheon-dong, Yeongtong-gu, Suwon 443-749, Korea.

Global Frontier Center for Multiscale Energy Systems, Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul 151-742, Korea.

出版信息

Sensors (Basel). 2018 Aug 31;18(9):2872. doi: 10.3390/s18092872.

DOI:10.3390/s18092872
PMID:30200306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6163335/
Abstract

Among many attempts to make a decent human motion detector in various engineering fields, a mechanical crack-based sensor that deliberately generates and uses nano-scale cracks on a metal deposited thin film is gaining attention for its high sensitivity. While the metal layer of the sensor must be responsible for its high performance, its effects have not received much academic interest. In this paper, we studied the relationship between the thickness of the metal layer and the characteristics of the sensor by depositing a few nanometers of chromium (Cr) and gold (Au) on the PET film. We found that the sensitivity of the crack sensor improves/increases under the following conditions: (1) when Au is thin and Cr is thick; and (2) when the ratio of Au is lower than that of Cr, which also increases the transmittance of the sensor, along with its sensitivity. As we only need a small amount of Au to achieve high sensitivity of the sensor, we have suggested more efficient and economical fabrication methods. With this crack-based sensor, we were able to successfully detect finger motions and to distinguish various signs of American Sign Language (ASL).

摘要

在各个工程领域中,人们尝试了许多方法来制造出性能良好的人体运动探测器,一种基于机械裂纹的传感器正逐渐受到关注,它在金属沉积薄膜上故意生成和利用纳米级裂纹,以实现高灵敏度。虽然传感器的金属层必须对其高性能负责,但它的效果并没有受到太多学术关注。在本文中,我们通过在 PET 薄膜上沉积几纳米厚的铬(Cr)和金(Au)来研究金属层厚度与传感器特性之间的关系。我们发现,在以下情况下,裂纹传感器的灵敏度会提高/增加:(1) 当 Au 较薄而 Cr 较厚时;(2) 当 Au 的比例低于 Cr 时,这也会增加传感器的透光率,同时提高其灵敏度。由于我们只需要少量的 Au 就可以实现传感器的高灵敏度,因此我们提出了更高效、更经济的制造方法。我们使用这种基于裂纹的传感器成功地检测到了手指运动,并能够区分美国手语(ASL)的各种手势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/c8e170b33494/sensors-18-02872-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/184e6beb6f27/sensors-18-02872-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/980c31f69c41/sensors-18-02872-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/42d0a1a4b69d/sensors-18-02872-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/c8e170b33494/sensors-18-02872-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/184e6beb6f27/sensors-18-02872-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/980c31f69c41/sensors-18-02872-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/42d0a1a4b69d/sensors-18-02872-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2ff/6163335/c8e170b33494/sensors-18-02872-g004.jpg

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