Ultrahigh sensitive carbon-based conducting rubbers for flexible and wearable human-machine intelligence sensing

TitleUltrahigh sensitive carbon-based conducting rubbers for flexible and wearable human-machine intelligence sensing
Publication TypeJournal Article
Year of Publication2020
AuthorsAjeev, A, Javaregowda, BH, Ali, A, Modak, M, Patil, S, Khatua, S, Ramadoss, M, Kothavade, PAnil, Arulraj, AKashmir
JournalAdvanced Materials Technologies
Volume5
Issue12
Pagination2000690
Date PublishedDEC
Type of ArticleArticle
ISSN2365-709X
Keywordsconducting rubbers, gauge factor, human&\#8211, machine interfacing, voice recognition, wearable strain sensors
Abstract

The wearable strain sensors with multifunctional applications can fuel the rapid development of human-machine intelligence for various sectors like healthcare, soft robotics, and Internet of Things applications. However, achieving the low-cost and mass production of wearable sensors with ultra-high performance remains challenging. Herein, a simple, cost-effective, and scalable methodology to fabricate the flexible and highly sensitive strain sensors using carbon black and latex rubbers (LR) is presented. The LR-based strain sensor demonstrates excellent flexibility, fast response (approximate to 600 ms), ultra-high sensitivity (maximum gauge factor of 1.2 x 10(4) at 250% strain), and long-term stability over 1000 cycles. The LR-based strain sensors are sensitive to monitor subtle human motions such as heart pulse rate and voice recognition along with high-strain human joint operations. Additionally, the sensing mechanism of LR bands is investigated by surface topographies and electromechanical response under various strained/unstrained conditions. Further, a smart glove-based sensor module made of LR strain bands with an Arduino reader for the human-machine intelligence device for non-verbal communication in military applications is demonstrated.

DOI10.1002/admt.202000690, Early Access Date = NOV 2020
Type of Journal (Indian or Foreign)

Foreign

Impact Factor (IF)

5.969

Divison category: 
Polymer Science & Engineering

Add new comment