Ultrahigh sensitive carbon-based conducting rubbers for flexible and wearable human-machine intelligence sensing
| Title | Ultrahigh sensitive carbon-based conducting rubbers for flexible and wearable human-machine intelligence sensing |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Authors | Ajeev, A, Javaregowda, BH, Ali, A, Modak, M, Patil, S, Khatua, S, Ramadoss, M, Kothavade, PAnil, Arulraj, AKashmir |
| Journal | Advanced Materials Technologies |
| Volume | 5 |
| Issue | 12 |
| Pagination | 2000690 |
| Date Published | DEC |
| Type of Article | Article |
| ISSN | 2365-709X |
| Keywords | conducting 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. |
| DOI | 10.1002/admt.202000690, Early Access Date = NOV 2020 |
| Type of Journal (Indian or Foreign) | Foreign |
| Impact Factor (IF) | 5.969 |
