A High‐Performance, Sensitive, Wearable Multifunctional Sensor Based on Rubber/CNT for Human Motion and Skin Temperature Detection. Issue 1 (24th October 2021) - Lin, Mengzhuan; Zheng, Zhongjie; Yang, Li; Luo, Mingshan; Fu, Lihua; Lin, Baofeng; Xu, Chuanhui
Abstract: Recently, flexible wearable electronic devices have attracted immense interest as an alternative for conventional rigid metallic conductors in personal healthcare monitoring, human motion detection, and sensory skins, owing to their intrinsic characteristics. However, the practical applications of most wearable sensors are generally limited by their poor stretchability and sensitivity, unsatisfactory strength, lower conductivity, and single sensory function. Here a hydrogen bond cross‐linked network based on carboxylic styrene butadiene rubber (XSBR) and hydrophilic sericin (SS) non‐covalently modified carbon nanotubes (CNTs) is rationally designed and then fabricated into multi‐functional sensors. The resultant versatile sensors are able to detect both weak and large deformations, which owns a low detection limit of 1% strain, high stretchability up to 217%, superior strength of 12.58 MPa, high sensitivity with a gauge factor up to 25.98, high conductivity of 0.071 S m −1, and lower percolation threshold of 0.504 wt%. Moreover, the prepared sensors also possess an impressively thermal response (0.01636 °C −1 ) and realize the application in the measurement of human body temperature. The multifunctional and scalable XSBR/SSCNT sensor with the integrated tracking capabilities of real‐time and in situ physiological signals, providing a promising route to develop wearable artificial intelligence in human health and sporting applications. Abstract : A multifunctional sensor with high performance is fabricated from the hydrogen bond cross‐linked network based on carboxylic styrene butadiene rubber (XSBR) and sericin‐modified carbon nanotubes (CNTs). The sensor is a good fit for the basic requirements of full‐human motion detection and real‐time temperature variation monitoring, providing a promising route to develop wearable artificial intelligence in human activity and health.