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Advanced Science
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High‐Conductivity, Self‐Healing, and Adhesive Ionic Hydrogels for Health Monitoring and Human‐Machine Interactions Under Extreme Cold Conditions

Authors: Fei Han; Shumeng Chen; Fei Wang; Mei Liu; Jiahui Li; Hao Liu; Yanshen Yang; +6 Authors

High‐Conductivity, Self‐Healing, and Adhesive Ionic Hydrogels for Health Monitoring and Human‐Machine Interactions Under Extreme Cold Conditions

Abstract

AbstractIonic conductive hydrogels (ICHs) are emerging as key materials for advanced human‐machine interactions and health monitoring systems due to their unique combination of flexibility, biocompatibility, and electrical conductivity. However, a major challenge remains in developing ICHs that simultaneously exhibit high ionic conductivity, self‐healing, and strong adhesion, particularly under extreme low‐temperature conditions. In this study, a novel ICH composed of sulfobetaine methacrylate, methacrylic acid, TEMPO‐oxidized cellulose nanofibers, sodium alginate, and lithium chloride is presented. The hydrogel is designed with a hydrogen‐bonded and chemically crosslinked network, achieving excellent conductivity (0.49 ± 0.05 S m−1), adhesion (36.73 ± 2.28 kPa), and self‐healing capacity even at −80 °C. Furthermore, the ICHs maintain functionality for over 45 days, showcasing outstanding anti‐freezing properties. This material demonstrates significant potential for non‐invasive, continuous health monitoring, adhering conformally to the skin without signal crosstalk, and enabling real‐time, high‐fidelity signal transmission in human‐machine interactions under cryogenic conditions. These ICHs offer transformative potential for the next generation of multimodal sensors, broadening application possibilities in harsh environments, including extreme weather and outer space.

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Keywords

long‐term stability, multifunctional wearable sensors, Science, Q, Electric Conductivity, Nanofibers, Hydrogels, self‐healing, ionic conductive hydrogels, Cold Temperature, Wearable Electronic Devices, health monitoring, Humans, human‐machine interactions, Research Article, Monitoring, Physiologic

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Average
Top 10%
Green
gold