Highly Sensitive and Flexible Capacitive Pressure Sensors Based on Vertical Graphene and Micro-Pyramidal Dielectric Layer

Author:

Zhao Ke1,Han Jiemin1ORCID,Ma Yifei1ORCID,Tong Zhaomin1,Suhr Jonghwan2,Wang Mei1ORCID,Xiao Liantuan1,Jia Suotang1,Chen Xuyuan13ORCID

Affiliation:

1. State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China

2. Department of Polymer Science and Engineering, School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea

3. Faculty of Technology, Natural Sciences and Maritime Sciences, Department of Microsystems, University of Southeast Norway, 3184 Borre, Norway

Abstract

Many practical applications require flexible high-sensitivity pressure sensors. However, such sensors are difficult to achieve using conventional materials. Engineering the morphology of the electrodes and the topography of the dielectrics has been demonstrated to be effective in boosting the sensing performance of capacitive pressure sensors. In this study, a flexible capacitive pressure sensor with high sensitivity was fabricated by using three-dimensional vertical graphene (VG) as the electrode and micro-pyramidal polydimethylsiloxane (PDMS) as the dielectric layer. The engineering of the VG morphology, size, and interval of the micro-pyramids in the PDMS dielectric layer significantly boosted the sensor sensitivity. As a result, the sensors demonstrated an exceptional sensitivity of up to 6.04 kPa−1 in the pressure range of 0–1 kPa, and 0.69 kPa−1 under 1–10 kPa. Finite element analysis revealed that the micro-pyramid structure in the dielectric layer generated a significant deformation effect under pressure, thereby ameliorating the sensing properties. Finally, the sensor was used to monitor finger joint movement, knee motion, facial expression, and pressure distribution. The results indicate that the sensor exhibits great potential in various applications, including human motion detection and human-machine interaction.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Key Research and Development Program of Shanxi Province for International Cooperation

Shanxi Scholarship Council of China

111 Project

Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China

Fund for Shanxi “1331 Project”

Publisher

MDPI AG

Subject

General Materials Science,General Chemical Engineering

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