A Semi‐Interpenetrating Network Hydrogel With Synergistic Ionic‐Electronic Dual‐Conduction for High‐Performance Wearable Sensing

The growing demand for precise human motion monitoring has spurred the development of versatile flexible wearable sensors. However, the uncomplicated and rapid fabrication of such integrated sensors remains a formidable challenge, as achieving high performance is frequently accompanied by tedious manufacturing procedures and the severe trade-off of isolating single properties. Herein, this study presents a well-rounded hydrogel featuring an integrated dual-conduction mechanism, composed of polyacrylamide (PAM), phytic acid (PA), and poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), successfully synthesized via a facile one-pot strategy. The hydrogel exhibits an exceptional comprehensive performance equilibrium, delivering a superior combination of extreme stretchability (∼2134%), stable conductivity (5.3 S/m), rapid-response sensitivity (160 ms, a gauge factor of 12 at > 600% strain), and long-term fatigue durability. Practically, the hydrogel sensor can not only precisely monitor the macroscopic motion amplitudes of various human joints but also reliably capture subtle, continuous biomechanical signals, such as user-specific handwriting patterns, Morse code tapping, and wireless wearable human-machine interface. Consequently, this work establishes a highly competitive material paradigm for versatile wearable electronic skins, demonstrating immense potential in both macroscopic motion tracking and high-fidelity micro-signal recognition.

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Publication Details

Journal
Small
Published
2026-10-04
DOI
https://doi.org/10.1002/smll.76122
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00

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article

A Semi‐Interpenetrating Network Hydrogel With Synergistic Ionic‐Electronic Dual‐Conduction for High‐Performance Wearable Sensing

Lü Li, Junjie Wang, Guilong Li, Ye Kang et al.
Small
Advanced Sensor and Energy Harvesting Materials
article

A Semi‐Interpenetrating Network Hydrogel With Synergistic Ionic‐Electronic Dual‐Conduction for High‐Performance Wearable Sensing

Lü Li, Junjie Wang, Guilong Li, Ye Kang, Guifang Chen, Jian Wang, Jialing Zhou, Chunmei Zhang
article en

Abstract

The growing demand for precise human motion monitoring has spurred the development of versatile flexible wearable sensors. However, the uncomplicated and rapid fabrication of such integrated sensors remains a formidable challenge, as achieving high performance is frequently accompanied by tedious manufacturing procedures and the severe trade-off of isolating single properties. Herein, this study presents a well-rounded hydrogel featuring an integrated dual-conduction mechanism, composed of polyacrylamide (PAM), phytic acid (PA), and poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), successfully synthesized via a facile one-pot strategy. The hydrogel exhibits an exceptional comprehensive performance equilibrium, delivering a superior combination of extreme stretchability (∼2134%), stable conductivity (5.3 S/m), rapid-response sensitivity (160 ms, a gauge factor of 12 at > 600% strain), and long-term fatigue durability. Practically, the hydrogel sensor can not only precisely monitor the macroscopic motion amplitudes of various human joints but also reliably capture subtle, continuous biomechanical signals, such as user-specific handwriting patterns, Morse code tapping, and wireless wearable human-machine interface. Consequently, this work establishes a highly competitive material paradigm for versatile wearable electronic skins, demonstrating immense potential in both macroscopic motion tracking and high-fidelity micro-signal recognition.

Small
Chengdu University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 23%
Advanced Sensor and Energy Harvesting Materials
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A Semi‐Interpenetrating Network Hydrogel With Synergistic Ionic‐Electronic Dual‐Conduction for High‐Performance Wearable Sensing — Lü Li, Junjie Wang, et al. · Small (2026) | TGRS Research Map | TGRS