Concepedia

Publication | Closed Access

Stretchable Triboelectric Self‐Powered Sweat Sensor Fabricated from Self‐Healing Nanocellulose Hydrogels

347

Citations

51

References

2022

Year

TLDR

Visualizing sweat constituents is vital for physiological assessment, yet limited material healing and unreliable power supply hinder practical sensor deployment. The study aims to fabricate a fully flexible, self‑powered sweat sensor from a cellulose‑based conductive hydrogel to overcome these limitations. The sensor employs a cellulose nanocomposite hydrogel electrode—polymerized with polyaniline and cross‑linked by polyvinyl alcohol/borax—using triboelectric effect to quantify Na⁺, K⁺, and Ca²⁺ in real time and wirelessly transmit the data. The device achieves >95 % self‑healing within 10 s, 1530 % stretchability, 0.6 S m⁻¹ conductivity, and sensitivities of 0.039, 0.082, and 0.069 mmol L⁻¹ for Na⁺, K⁺, and Ca²⁺, demonstrating high flexibility, stability, and analytical performance for self‑powered health monitoring.

Abstract

Abstract Though visualizing perspiration constituents is crucial for physiological evaluation, inadequate material healing and unreliable power supply methods restrict its applications. Herein, a fully flexible self‐powered sweat sensor is fabricated from a cellulose‐based conductive hydrogel to address these issues. The hydrogel electrode is composed of a cellulose nanocomposite polymerized in situ with polyaniline and cross‐linked with polyvinyl alcohol/borax. The cellulose nanocomposites furnish the sweat sensor with tensile and electrical self‐healing efficiencies exceeding 95% within 10 s, a stretchability of 1530%, and conductivity of 0.6 S m −1 . The sweat sensor quantitatively analyzes Na + , K + , and Ca 2+ contents in perspiration, to sensitivities of 0.039, 0.082, and 0.069 mmol –1 , respectively, in real time via triboelectric effect and wirelessly transmits the results to a user interface. This fabricated sweat sensor with high flexibility, stability, and analytical sensitivity and selectivity provides new opportunities for self‐powered health monitoring.

References

YearCitations

Page 1