Kumaresan, Y. , Mishra, S. , Ozioko, O., Chirila, R. and Dahiya, R. (2022) Ultra-high gauge factor strain sensor with wide range stretchability. Advanced Intelligent Systems, 4(9), 2200043. (doi: 10.1002/aisy.202200043)
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Abstract
Strain sensors with wide range stretchability, good sensitivity, high gauge factor, and reliability are needed for several applications. Herein we present stretchable strain sensors capable of operating over multi-strain range and having excellent gauge factor. The systematic study, carried out with different combinations of elastomer, conductive filler and graphene-carbon paste (GCP), revealed that the sensors exhibit excellent stretchability when only filler particles are present in the elastomer, and they exhibit high sensitivity when filler particles are mixed with GCP. The molecular dynamics simulations show that the addition of GCP to the elastomer- filler composite helps to attain the excellent sensor response with wide range stretchability. Thus, sensors response can be tuned by using selected material composition. Accordingly, the strain sensor with 50 wt.% GCP revealed 500% stretchability and a maximum gauge factor of 504. Likewise, 150 wt.% GCP loading led to sensors with 45% stretchability and an unprecedented gauge factor of 1834140. The capability to detect the small- to large-scale strains make the presented sensors attractive for monitoring the movements by body parts – which range from small movements during facial expression to large movement experienced by the limb joints.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work was supported in part by Engineering and Physical Sciences Research Council (EPSRC) through engineering fellowship for growth (EP/R029644/1) and European Commission through FET-OPEN project Ph-Coding (H2020-FETOPEN-2018- 829186) and Innovative Training Network Project INTUITIVE (H2020-MSCA-ITN-2019-861166). |
| Keywords: | Stretchable electronics, strain sensor, carbon nanotube, elastomer and gauge factor. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Dahiya, Professor Ravinder and Kumaresan, Dr Yogeenth and Chirila, Mr Radu-Razvan and Ozioko, Mr Oliver and Mishra, Mr Shashank |
| Authors: | Kumaresan, Y., Mishra, S., Ozioko, O., Chirila, R., and Dahiya, R. |
| College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
| Journal Name: | Advanced Intelligent Systems |
| Publisher: | Wiley |
| ISSN: | 2640-4567 |
| ISSN (Online): | 2640-4567 |
| Published Online: | 16 June 2022 |
| Copyright Holders: | Copyright © 2022 The Authors |
| First Published: | First published in Advanced Intelligent Systems 4(9): 2200043 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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