Linearly Sensitive Pressure Sensor Based on a Porous Multistacked Composite Structure with Controlled Mechanical and Electrical Properties

Young Jung, Taehan Lee, Jiyoon Oh, Byung Geon Park, Jong Soo Ko, Hyeok Kim, Jong Pil Yun, Hanchul Cho

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Capacitive pressure sensors based on porous structures have been extensively explored for various applications because their sensing performance is superior to that of conventional polymer sensors. However, it is challenging to develop sufficiently sensitive pressure sensors with linearity over a wide pressure range owing to the trade-off between linearity and sensitivity. This study demonstrates a novel strategy for the fabrication of a pressure sensor consisting of stacked carbon nanotubes (CNTs) and polydimethylsiloxane. With the addition of carbon nanotubes, the structure is linearly compressed due to the reinforced mechanical properties, thereby resulting in high linearity. Additionally, the percolation effect is boosted by the CNTs having a high dielectric constant, thus improving the sensitivity. The pressure sensor exhibits linear sensitivity (R2 = 0.991) in the medium-pressure range (10-100 kPa). Furthermore, it delivers excellent performance with a fast response time (∼60 ms), in conjunction with high repeatability, reproducibility, and reliability (5 and 50 kPa/1000 cycles). The fabricated sensors are applied in wearable devices to monitor finger bending and detect finger motions in real time with high precision. The large-area sensor is integrated with a neural network to accurately recognize the sitting posture on a plane, thereby demonstrating the wide-range detection performance.

Original languageEnglish
Pages (from-to)28975-28984
Number of pages10
JournalACS applied materials & interfaces
Volume13
Issue number24
DOIs
StatePublished - 23 Jun 2021

Keywords

  • linear sensitivity
  • multistacked structures
  • porous structures
  • pressure sensors
  • wide pressure range

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