Issue 4, 2020, Issue in Progress

Reduced graphene oxide-based highly sensitive pressure sensor for wearable electronics via an ordered structure and enhanced interlayer interaction mechanism

Abstract

Compressible carbon materials have promising applications in various wearable devices. However, it is still difficult to prepare a carbon material with superior mechanical properties, stable strain-electrical signal response, and high linear sensitivity. In this study, a compressible and conductive carbon aerogel with excellent properties is obtained by designing an ordered wavy layered structure with enhanced interactions between carbon layers. Bidirectional freezing is used to produce a wavy layered structure. Cellulose nanocrystals (CNC) and lignin play important roles in enhancing the interactions between reduced graphene oxide (rGO) layers. Due to the design of the carbon aerogel structure and interlayer interactions, the prepared carbon aerogel exhibits supercompressibility (up to 99% ultimate strain), excellent elasticity and fatigue resistance (91.3% height retention after 10 000 cycles at a strain of 30%), and stable strain-current response. Moreover, the carbon aerogel demonstrated an ultrahigh sensitivity of 190.94 kPa−1, a wide linear range (within strain of 0–80%), and a low detection limit for pressure (0.875 Pa). These advantages suggest that this carbon aerogel has great application potential in wearable devices.

Graphical abstract: Reduced graphene oxide-based highly sensitive pressure sensor for wearable electronics via an ordered structure and enhanced interlayer interaction mechanism

Supplementary files

Article information

Article type
Paper
Submitted
22 Oct 2019
Accepted
28 Dec 2019
First published
10 Jan 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 2150-2159

Reduced graphene oxide-based highly sensitive pressure sensor for wearable electronics via an ordered structure and enhanced interlayer interaction mechanism

K. Zhou, C. Chen, M. Lei, Q. Gao, S. Nie, X. Liu and S. Wang, RSC Adv., 2020, 10, 2150 DOI: 10.1039/C9RA08653F

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