Printed and Flexible Capacitive Pressure Sensor with Carbon Nanotubes based Composite Dielectric Layer.
Zhenxin GuoLixin MoYu DingQingqing ZhangXiangyou MengZhengtan WuYinjie ChenMeijuan CaoWei WangLuhai LiPublished in: Micromachines (2019)
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.