Loading…

A Multi-model, Large-range Flexible Strain Sensor Based on Carbonized Silk Habotai for Human Health Monitoring

In recent years, flexible strain sensors have received considerable attention owing to their excellent flexibility and multifunctionality. However, it is still a great challenge for them to accurately monitor multi-model deformations with high sensitivity and linearity. In this study, the industrial...

Full description

Saved in:
Bibliographic Details
Published in:Chinese journal of polymer science 2023-08, Vol.41 (8), p.1238-1249
Main Authors: Ma, Shi-Dong, Wu, Yu-Ting, Tang, Jian, Zhang, Yu-Min, Yan, Tao, Pan, Zhi-Juan
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In recent years, flexible strain sensors have received considerable attention owing to their excellent flexibility and multifunctionality. However, it is still a great challenge for them to accurately monitor multi-model deformations with high sensitivity and linearity. In this study, the industrial insulating silk habotai was successfully converted into carbonized silk habotai (CSH) for use in strain sensors. A strain sensor created using CSH exhibited excellent sensing performance under multi-model deformations, including stretching, twist and bending. The maximum tensile strain was 434%. The gauge factors were 14.6 in the wide tensile range of 0%–400% with a high linearity of 0.959. In addition, the CSH strain sensor exhibited an extremely fast response time (110 ms) and could accurately detect bending (0°–180°) and torsional (0°–180°) strains. High durability and repeatability were observed for the multi-model strains. Finally, a new type of smart pillow was developed to accurately record head movement and breathing during sleep. The sensor may also be used for auxiliary training in table tennis. The proposed CSH strain sensor has shown great potential for applications in smart devices and human-machine interactions.
ISSN:0256-7679
1439-6203
DOI:10.1007/s10118-023-2924-4