Chemical Engineering Journal Advances (May 2023)

A highly sensitive and wide-range pressure sensor based on orientated and strengthened TPU nanofiber membranes fabricated by a conjugated electrospinning technology

  • Xu Jin,
  • Zhijun Xu,
  • Bin Wang,
  • Shanshan Ding,
  • Jiayu Ma,
  • Meng Cui,
  • Chuanchun Wang,
  • Yuping Jiang,
  • Jiali Liu,
  • Xiuqin Zhang

Journal volume & issue
Vol. 14
p. 100491

Abstract

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Flexible capacitive pressure sensors as one of the crucial sensing components have aroused widespread concern because of their vital role in development of wearable artificial devices, healthcare biomonitoring and human-machine interface. However, there has been a considerable challenge to successfully fabricate them with a tradeoff between high sensitivity and wide sensing range by low-cost and convenient manufacturing methods. Herein, the orientated thermoplastic polyurethane elastomer rubber nanofiber membranes (TPU-O NMs) were prepared via conjugated electrospinning to build a dielectric layer for the flexible capacitive wide-range pressure sensors with high sensitivity. In addition, polyaniline (PANI) was in situ polymerized on the TPU-O NMs as flexible electrodes to maintain the conductive pathway, flexibility, and breathability of the sensors. The TPU@PANI NMs form a bamboo-raft-like microstructure between the aligned fibers under pressure, resulting in a significant increase in sensitivity and working range. Furthermore, the conductive TPU@PANI NMs can be stretched to 1600% without fracture. The assembled sensor has a high sensitivity of 31.73 kPa−1 and a fast response/recovery time of 96 ms. Meantime, it also exhibits a minimum detection limit of 1 Pa, an excellent stability of 10,000 cycles, and a good linearity in a broad working age (1 Pa∼122.5 kPa). Finally, the capacitive pressure sensor was successfully applied for full-range detection of human motions, such as finger bending, joint bending, and even boxing movements. Hence this highly sensitive and wide-range pressure sensor can be a promising candidate for healthcare monitoring, motion recognition, and wearable circuitry in artificial intelligence.

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