Issue 47, 2023

High strength, self-healing sensitive ionogel sensor based on MXene/ionic liquid synergistic conductive network for human-motion detection

Abstract

Ionogels with both high strength and high conductivity for wearable strain and pressure dual-mode sensors are needed for human motion and health monitoring. Here, multiple hydrogen bonds are introduced through imidazolidinyl urea (IU) as a chain extender to provide high mechanical and self-healing properties for the water–borne polyurethane (WPU). The MXene/ionic liquids synergistic conductive network provides excellent conductivity and also reduces the relative content of ionic liquids to maintain the mechanical properties of the ionogels. The mechanical strength of this ionogel reached 1.81–2.24 MPa and elongation at break reached 570–624%. It also has excellent conductivity (22.7–37.5 mS m−1), gauge factor (GF) (as a strain sensor, GF = 1.8), sensitivity (S) (as a press sensor, S1 = 29.8 kPa−1, S2 = 1.3 kPa−1), and fast response time (as a strain sensor = 185 ms; as a press sensor = 204 ms). The ionogel also exhibits rapid photothermal self-healing capabilities due to the inherent photothermal behavior of MXene. It can maintain good elasticity and conductivity at low temperatures. In addition, this ionogel is able to stretch for 1200 cycles without significant change in the relative change of resistance. The ionogel can be assembled as a strain sensor for monitoring human motion and as a pressure sensor array for obtaining pressure magnitude and position information.

Graphical abstract: High strength, self-healing sensitive ionogel sensor based on MXene/ionic liquid synergistic conductive network for human-motion detection

Supplementary files

Article information

Article type
Paper
Submitted
13 iyl 2023
Accepted
02 okt 2023
First published
12 okt 2023

J. Mater. Chem. B, 2023,11, 11251-11264

High strength, self-healing sensitive ionogel sensor based on MXene/ionic liquid synergistic conductive network for human-motion detection

X. Wen, Z. Deng, H. Wang, J. Shi, S. Wang, H. Wang, Y. Song, Z. Du, J. Qiu and X. Cheng, J. Mater. Chem. B, 2023, 11, 11251 DOI: 10.1039/D3TB01570J

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