A wearable ionic hydrogel strain sensor with double cross-linked network for human machine interface

Zijian Wu; Liying Zhang; Meng Wang; Defeng  Zang; Haiyong  Long; Ling Weng; Ning Guo; Junguo Gao; Yonghong  Liu; Ben Bin Xu

A wearable ionic hydrogel strain sensor with double cross-linked network for human machine interface

Zijian Wu^*, Liying Zhang, Meng Wang, Defeng Zang, Haiyong Long, Ling Weng^*, Ning Guo, Junguo Gao^*, Yonghong Liu, Ben Bin Xu^*

^*Corresponding author for this work

Mechanical and Construction Engineering Department

Research output: Contribution to journal › Article › peer-review

Abstract

Wearable strain sensor prepared with ionic conductive hydrogel holds great promises in a variety of engineering fields. In this work, we introduce sodium casein (SC) into a dual network hydrogel system made of polyvinyl alcohol (PVA) and polyacrylamide (PAM), to prepare an ionic hydrogel sensor. Compared to the PAM/PVA dual network hydrogel, the introduction of SC plays a significant synergistic role. Such dual network PAM/PVA/SC hydrogels exhibit excellent mechanical properties (a maximum strain of 719%, a maximum stress of 444.3 kPa), low hysteresis and rapid recovery after uni-axial stretching. Since SC drives a large number of free ions, PAM/PVA/SC hydrogels present good conductivity while maintaining high physical stability, to enable an excellent sensitivity in a comparatively large strain range (Gauge factor, GF=2.17 under 400% strain). The unique properties allow the generation of stable and accurate electrical signals transduced from different locations of human body. As such, the PAM/PVA/SC hydrogel has the potential to be used as human machine interface for continuous, real-time physiological monitoring.

Original language	English
Journal	Advanced Composites and Hybrid Materials
Publication status	Accepted/In press - 23 Nov 2024

Embargoed Document

Manuscript - 2024-11-3
Accepted author manuscript, 2.77 MB
Embargo ends: 23/11/25

Cite this

@article{2826e47ad2024be8ab44c3970b82a338,

title = "A wearable ionic hydrogel strain sensor with double cross-linked network for human machine interface",

abstract = "Wearable strain sensor prepared with ionic conductive hydrogel holds great promises in a variety of engineering fields. In this work, we introduce sodium casein (SC) into a dual network hydrogel system made of polyvinyl alcohol (PVA) and polyacrylamide (PAM), to prepare an ionic hydrogel sensor. Compared to the PAM/PVA dual network hydrogel, the introduction of SC plays a significant synergistic role. Such dual network PAM/PVA/SC hydrogels exhibit excellent mechanical properties (a maximum strain of 719%, a maximum stress of 444.3 kPa), low hysteresis and rapid recovery after uni-axial stretching. Since SC drives a large number of free ions, PAM/PVA/SC hydrogels present good conductivity while maintaining high physical stability, to enable an excellent sensitivity in a comparatively large strain range (Gauge factor, GF=2.17 under 400% strain). The unique properties allow the generation of stable and accurate electrical signals transduced from different locations of human body. As such, the PAM/PVA/SC hydrogel has the potential to be used as human machine interface for continuous, real-time physiological monitoring.",

author = "Zijian Wu and Liying Zhang and Meng Wang and Defeng Zang and Haiyong Long and Ling Weng and Ning Guo and Junguo Gao and Yonghong Liu and Xu, {Ben Bin}",

year = "2024",

month = nov,

day = "23",

language = "English",

journal = "Advanced Composites and Hybrid Materials",

issn = "2522-0128",

publisher = "Springer",

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TY - JOUR

T1 - A wearable ionic hydrogel strain sensor with double cross-linked network for human machine interface

AU - Wu, Zijian

AU - Zhang, Liying

AU - Wang, Meng

AU - Zang, Defeng

AU - Long, Haiyong

AU - Weng, Ling

AU - Guo, Ning

AU - Gao, Junguo

AU - Liu, Yonghong

AU - Xu, Ben Bin

PY - 2024/11/23

Y1 - 2024/11/23

N2 - Wearable strain sensor prepared with ionic conductive hydrogel holds great promises in a variety of engineering fields. In this work, we introduce sodium casein (SC) into a dual network hydrogel system made of polyvinyl alcohol (PVA) and polyacrylamide (PAM), to prepare an ionic hydrogel sensor. Compared to the PAM/PVA dual network hydrogel, the introduction of SC plays a significant synergistic role. Such dual network PAM/PVA/SC hydrogels exhibit excellent mechanical properties (a maximum strain of 719%, a maximum stress of 444.3 kPa), low hysteresis and rapid recovery after uni-axial stretching. Since SC drives a large number of free ions, PAM/PVA/SC hydrogels present good conductivity while maintaining high physical stability, to enable an excellent sensitivity in a comparatively large strain range (Gauge factor, GF=2.17 under 400% strain). The unique properties allow the generation of stable and accurate electrical signals transduced from different locations of human body. As such, the PAM/PVA/SC hydrogel has the potential to be used as human machine interface for continuous, real-time physiological monitoring.

AB - Wearable strain sensor prepared with ionic conductive hydrogel holds great promises in a variety of engineering fields. In this work, we introduce sodium casein (SC) into a dual network hydrogel system made of polyvinyl alcohol (PVA) and polyacrylamide (PAM), to prepare an ionic hydrogel sensor. Compared to the PAM/PVA dual network hydrogel, the introduction of SC plays a significant synergistic role. Such dual network PAM/PVA/SC hydrogels exhibit excellent mechanical properties (a maximum strain of 719%, a maximum stress of 444.3 kPa), low hysteresis and rapid recovery after uni-axial stretching. Since SC drives a large number of free ions, PAM/PVA/SC hydrogels present good conductivity while maintaining high physical stability, to enable an excellent sensitivity in a comparatively large strain range (Gauge factor, GF=2.17 under 400% strain). The unique properties allow the generation of stable and accurate electrical signals transduced from different locations of human body. As such, the PAM/PVA/SC hydrogel has the potential to be used as human machine interface for continuous, real-time physiological monitoring.

M3 - Article

SN - 2522-0128

JO - Advanced Composites and Hybrid Materials

JF - Advanced Composites and Hybrid Materials

ER -