4.7 Article

Self-Restoring Capacitive Pressure Sensor Based on Three-Dimensional Porous Structure and Shape Memory Polymer

Journal

POLYMERS
Volume 13, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/polym13050824

Keywords

pressure sensors; capacitive pressure sensor; shape memory polymer; wide pressure range; porous structure; self-restoring; durability

Funding

  1. National Research Foundation of Korea (NRF) - Korea government (MSIT) [2019R1C1C1010730, 2018R1D1A1B07040446]
  2. National Research Foundation of Korea [2018R1D1A1B07040446, 2019R1C1C1010730] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The study introduces a flexible pressure sensor based on a shape memory polymer with notable durability and high sensitivity, which is used for real-time monitoring of shoe insole pressures.
Highly flexible and compressible porous polyurethane (PU) structures have effectively been applied in capacitive pressure sensors because of the good elastic properties of the PU structures. However, PU porous structure-based pressure sensors have been limited in practical applications owing to their low durability during pressure cycling. Herein, we report a flexible pressure sensor based on a three-dimensional porous structure with notable durability at a compressive pressure of 500 kPa facilitated by the use of a shape memory polymer (SMP). The SMP porous structure was fabricated using a sugar templating process and capillary effect. The use of the SMP resulted in the maintenance of the sensing performance for 100 cycles at 500 kPa; the SMP can restore its original shape within 30 s of heating at 80 degrees C. The pressure sensor based on the SMP exhibited a higher sensitivity of 0.0223 kPa(-1) than a typical PU-based sensor and displayed excellent sensing performance in terms of stability, response time, and hysteresis. Additionally, the proposed sensor was used to detect shoe insole pressures in real time and exhibited remarkable durability and motion differentiation.

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