Facilely prepared layer-by-layer graphene membrane-based pressure sensor with high sensitivity and stability for smart wearable devices

Tao Liu, Caizhen Zhu, Wei Wu, Kai-Ning Liao, Xianjing Gong, Qijun Sun, Robert K.Y. Li*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

50 Citations (Scopus)

Abstract

With the prosperous development of artificial intelligence, medical diagnosis and electronic skins, wearable electronic devices have drawn much attention in our daily life. Flexible pressure sensors based on carbon materials with ultrahigh sensitivity, especially in a large pressure range regime are highly required in wearable applications. In this work, graphene membrane with a layer-by-layer structure has been successfully fabricated via a facile self-assembly and air-drying (SAAD) method. In the SAAD process, air-drying the self-assembled graphene hydrogels contributes to the uniform and compact layer structure in the obtained membranes. Owing to the excellent mechanical and electrical properties of graphene, the pressure sensor constructed by several layers of membranes exhibits high sensitivity (52.36 kPa−1) and repeatability (short response and recovery time) in the loading pressure range of 0–50 kPa. Compared with most reported graphene-related pressure sensors, our device shows better sensitivity and wider applied pressure range. What's more, we demonstrate it shows desired results in wearable applications for pulse monitoring, breathing detection as well as different intense motion recording such as walk, run and squat. It's hoped that the facilely prepared layer-by-layer graphene membrane-based pressure sensors will have more potential to be used for smart wearable devices in the future.
Original languageEnglish
Pages (from-to)241-247
JournalJournal of Materials Science and Technology
Volume45
Online published8 Jan 2020
DOIs
Publication statusPublished - 15 May 2020

Research Keywords

  • Graphene membrane
  • High sensitivity
  • Human motions
  • Self-assembly
  • Wearable devices

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