Stretchable and High‐Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring

Electronic textiles with remarkable breathability, lightweight, and comfort hold great potential in wearable technologies and smart human-machine interfaces. Ionic capacitive sensors, leveraging the advantages of the electric double layer, offer higher sensitivity compared to traditional capacitive sensors. Current research on wearable ion-capacitive sensors has focused mainly on two-dimensional (2D) or three-dimensional (3D) device architectures, which show substantial challenges for direct integration with textiles and compromise their wearing experience on conformability and permeability. One-dimensional (1D) stretchable fiber materials serve as vital components in constructing electronic textiles, allowing for rich structural design, patterning, and device integration through mature textile techniques. Here, a stretchable functional fiber with robust mechanical and electrical performances is fabricated based on semi-solid metal and ionic polymer, which provided a high stretchability and good electrical conductivity, enabling seamless integration with textiles. Consequently, high-performance stretchable fiber sensors are developed through different device architecture designs, including pressure sensors with high sensitivity (7.21 kPa<sup>-1</sup>), fast response (60 ms/30 ms), and excellent stability, as well as strain sensors with high sensitivity (GF = 1.05), wide detection range (0-300% strain), and excellent sensing stability under dynamic deformations.

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Publication Details

Journal
Advanced Science
Published
2024-11-11
DOI
https://doi.org/10.1002/advs.202412859
Citations
31
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
5.72

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article

Stretchable and High‐Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring

Lishen Zhang, Hongbiao Sun, Jiangxin Wang, Jiawei Liu et al.
31 citations
Advanced Science
Advanced Sensor and Energy Harvesting Materials
5.72
article

Stretchable and High‐Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring

Lishen Zhang, Hongbiao Sun, Jiangxin Wang, Jiawei Liu, Jinhui Wang, Xin Xie, Yan Yang, Yanfeng Hou, Guangchuan Chen
article en
31 citations

Abstract

Electronic textiles with remarkable breathability, lightweight, and comfort hold great potential in wearable technologies and smart human-machine interfaces. Ionic capacitive sensors, leveraging the advantages of the electric double layer, offer higher sensitivity compared to traditional capacitive sensors. Current research on wearable ion-capacitive sensors has focused mainly on two-dimensional (2D) or three-dimensional (3D) device architectures, which show substantial challenges for direct integration with textiles and compromise their wearing experience on conformability and permeability. One-dimensional (1D) stretchable fiber materials serve as vital components in constructing electronic textiles, allowing for rich structural design, patterning, and device integration through mature textile techniques. Here, a stretchable functional fiber with robust mechanical and electrical performances is fabricated based on semi-solid metal and ionic polymer, which provided a high stretchability and good electrical conductivity, enabling seamless integration with textiles. Consequently, high-performance stretchable fiber sensors are developed through different device architecture designs, including pressure sensors with high sensitivity (7.21 kPa<sup>-1</sup>), fast response (60 ms/30 ms), and excellent stability, as well as strain sensors with high sensitivity (GF = 1.05), wide detection range (0-300% strain), and excellent sensing stability under dynamic deformations.

Advanced ScienceVol. 12(1)
Sichuan University (CN)
National Natural Science Foundation of China, Sichuan University, Young Scientists Fund
Openalex Percentile: Top 3%
Advanced Sensor and Energy Harvesting Materials
5.72
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