A recyclable, mechanically robust, and anti-freezing chitosan/polyvinyl alcohol/polyaniline conductive hydrogel for multifunctional sensing application.
Journal:
International journal of biological macromolecules
Published Date:
Jun 18, 2026
Abstract
Conductive hydrogels have demonstrated fascinating application potential in flexible electronics. However, conductive hydrogels often exhibit poor mechanical properties, low electrical conductivity and limited recyclability, which hinders the electrochemical performance and green sustainable usability of hydrogel sensors. Therefore, it is crucial to develop hydrogel sensors with satisfactory mechanical strength, excellent electrical conductivity and recyclability. Herein, aniline (ANI) monomer was in-situ polymerized within a chitosan/poly (vinyl alcohol) (CS/PVA) network to generate interpenetrating polyaniline (PANI) chains. After undergoing three freeze-thaw cycles, the PVA chain generates microcrystalline regions, which promotes its gelation. Conjugated PANI backbones providing continuous conductive pathways for delocalized π-electrons and forming multiple hydrogen bondings among PANI, CS, and PVA networks synergistically endow the electronic conductive hydrogel with high conductivity and robust mechanical properties. The thermal solubility of hydrogels facilitates multiple recycling and remolding without significant performance degradation. As a strain sensor, the hydrogel displays high electrical conductivity (3.58 S/m), outstanding sensing sensitivity (GF = 3.46, ∼450%), fast response time, and reliable stability, making it suitable for various human motion monitoring. Moreover, incorporation of the glycerol/water binary solvent confers the hydrogel with anti-freezing and moisture-retention capabilities, enabling it as an epidermal electrode for high-fidelity acquisition of weak electrophysiological signals (EMG, ECG, and EEG) toward early-stage disease screening and diagnosis. In addition, coupling multi-channel sign language signal acquisition with machine learning algorithms could achieve precise assessment of gesture recognition accuracy. This work has broadened new horizons for the development of intelligent PANI-based hydrogel electronic devices.
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