Printed and Flexible Capacitive Pressure Sensor with Carbon Nanotubes based Composite Dielectric Layer

Author:

Guo Zhenxin,Mo LixinORCID,Ding Yu,Zhang Qingqing,Meng Xiangyou,Wu Zhengtan,Chen Yinjie,Cao Meijuan,Wang Wei,Li Luhai

Abstract

Flexible pressure sensors have attracted tremendous attention from researchers for their widely applications in tactile artificial intelligence, electric skin, disease diagnosis, and healthcare monitoring. Obtaining flexible pressure sensors with high sensitivity in a low cost and convenient way remains a huge challenge. In this paper, the composite dielectric layer based on the mixture of carbon nanotubes (CNTs) with different aspect ratios and polydimethylsiloxane (PDMS) was employed in flexible capacitive pressure sensor to increase its sensitivity. In addition, the screen printing instead of traditional etching based methods was used to prepare the electrodes array of the sensor. The results showed that the aspect ratio and weight fraction of the CNTs play an important role in improving the sensitivity of the printed capacitive pressure sensor. The prepared capacitive sensor with the CNTs/PDMS composite dielectric layer demonstrated a maximum sensitivity of 2.9 kPa−1 in the pressure range of 0–450 Pa, by using the CNTs with an aspect ratio of 1250–3750 and the weight fraction of 3.75%. The mechanism study revealed that the increase of the sensitivity of the pressure sensor should be attributed to the relative permittivity increase of the composite dielectric layer under pressure. Meanwhile, the printed 3 × 3 and 10 × 10 sensor arrays showed excellent spatial resolution and uniformity when they were applied to measure the pressure distribution. For further applications, the flexible pressure sensor was integrated on an adhesive bandage to detect the finger bending, as well as used to create Morse code by knocking the sensor to change their capacitance curves. The printed and flexible pressure sensor in this study might be a good candidate for the development of tactile artificial intelligence, intelligent medical diagnosis systems and wearable electronics.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3