High-performance ionic conductive poly(vinyl alcohol) hydrogels for flexible strain sensors based on a universal soaking strategy
Di, X (Di, Xiang)[ 1 ] ; Ma, QY (Ma, Qiyue)[ 1 ] ; Xu, Y (Xu, Yue)[ 1 ] ; Yang, MM (Yang, Mingming)[ 1 ] ; Wu, GL (Wu, Guolin)[ 1 ] ; Sun, PC (Sun, Pingchuan)[ 1 ]
MATERIALS CHEMISTRY FRONTIERS, 2021, 5(1): 315-323
DOI: 10.1039/d0qm00625d
摘要
Conductive materials with predominant mechanical properties and high sensitivity have promising applications in various fields such as fabrication of electric skins, wearable sensors, and soft robotics. High-performance and flexible strain sensors based on conductive hydrogels have attracted significant attention because of their potential applications in voice recognition and human-machine interfaces. Inspired by the mechanism of neural tissue signal transmission, herein, a high-strength and relatively high-sensitivity ionic conductive hydrogel was developed by utilizing the completely physically crosslinked polyvinyl alcohol (PVA) and a simple inorganic salt solution soaking strategy. The ionic conductive hydrogels exhibited intriguing remoldability and excellent mechanical properties such as superb tensile strength (8.03 MPa), high toughness (28.7 MJ m(-3)), and high elastic modulus (1 MPa) because of their high-density hydrogen bonding and chain entanglement networks. By integrating the PVA-NaCl gel into a flexible strain sensor, the sensor displayed high conductivity (7.14 S m(-1)) at room temperature and subzero temperature, high accuracy (GF = 0.989), and sensitive strain responsiveness in a wide strain detection window of 0.2-400%. These results imply good performance for monitoring and distinguishing various human daily activities and slight physiological signals. Furthermore, the as-made PVA sol could convert to gel state just by being injected on a flexible substrate under an ice-bath and the conductive hydrogels displayed excellent biocompatibility and improved cell proliferation. Therefore, the as-formulated hydrogel sensor can have promising applications in wearable devices, such as sports monitoring, healthcare monitoring or voice recognition.