张学锋

副教授    硕士生导师

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  • 教师拼音名称: zhangxuefeng
  • 所在单位: 机电工程学院
  • 学历: 研究生(博士)毕业
  • 性别: 男
  • 学位: 博士学位
  • 在职信息: 在职

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A highly sensitive flexible capacitive pressure sensor with wide detection range based on bionic gradient microstructures

发布时间:2024-08-09
点击次数:
所属单位:
机电工程学院
发表刊物:
IEEE Sensors Journal
关键字:
Bionic microstructure, capacitive pressure sensor, flexible device, highly sensitive
摘要:
Introducing microstructures into a flexible pressure sensor is an effective way to improve performance of the sensor. However, existing methods for preparing microstructures in sensors, such as the artificial template method, not only are time consuming and costly but also have restrictions on the diversity and complexity of the achieved microstructures. Therefore, leaves of plants that possess abundant microstructures on surfaces can be used as templates to prepare microstructures in pressure sensors. For this reason, we have developed a flexible capacitive pressure sensor with microstructured dielectric layer and electrodes by a simple and convenient way. Specifically, the polydimethylsiloxane (PDMS) electrode was obtained by transforming the microstructures and a nonflaking multi-walled carbon nanotubes (MWCNTs) conductive layer simultaneously from an indocalamus leaf template. The dielectric layer with double-sided microstructures was formed by molding two indocalamus leaves on both sides. All the microstructures of electrodes and dielectric layer are beneficial to increase the degree of deformation thus improves the sensitivity and detection range efficiently. As a result, the obtained flexible pressure sensor exhibits a high sensitivity of 2.012 kPa(-1), a fast response time less than 20 ms, good durability of 1000 cycles, and a wide detection range up to 100 kPa. In addition, we demonstrated the availability of the designed sensor in the monitoring the tactile pressure signals and human movements. The experimental results confirm that the proposed capacitive pressure sensor has a great potential in applications, such as electronic skin, wearable devices, and intelligent robots.
第一作者:
同志学,王争东,张学锋
论文类型:
期刊论文
通讯作者:
党栋睿,苏松麟
卷号:
23/14/15413-15423
ISSN号:
1530-437X
是否译文:
发表时间:
2023-07-15