Issue 23, 2022

Nanocrack-based ultrasensitive wearable and skin-mountable strain sensors for human motion detection

Abstract

Advanced wearable and stretchable strain sensing devices for human motion detection are garnering tremendous attention and thus demonstrate substantial potential for future wearable sensors. This work presents network crack-assisted wearable strain sensors using graphite nanoflake spray coated onto highly elastic nitrile elastomers. The as-fabricated wearable strain sensors demonstrate numerous captivating benefits, including simplicity in the construction process and ultra-large strain sensitivity far surpassing the state of art stretchable strain sensors. It is worth mentioning that the stretchable strain sensors possess an ultrasensitive gauge factor (GF) of 868.12 ± 56.90 and a wide sensing range of up to 30% strain. The electromechanical performance depends on the electrical resistance variation, which is substantially altered by percolative microstructural network cracks with strain concentration during mechanical deformations. The ultrasensitive strain monitoring performance in conjunction with a wide sensing range, prominent reversibility, ultrafast response and recovery speeds (7.5 ms, and 5 ms, respectively), and excellent durability (more than 2000 stretching–releasing cycles under a large-scale strain of 30%) enables the strain sensors to be used as electronic skins for wearable monitoring applications, including but not limited to the detection of full-range human activity monitoring, as well as healthcare and biomedical-related vital signs, soft robotics, and entertainment technology.

Graphical abstract: Nanocrack-based ultrasensitive wearable and skin-mountable strain sensors for human motion detection

Article information

Article type
Paper
Submitted
11 Sep 2022
Accepted
04 Oct 2022
First published
05 Oct 2022
This article is Open Access
Creative Commons BY-NC license

Mater. Adv., 2022,3, 8665-8676

Nanocrack-based ultrasensitive wearable and skin-mountable strain sensors for human motion detection

R. Madhavan, Mater. Adv., 2022, 3, 8665 DOI: 10.1039/D2MA00897A

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