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Multiple Stimuli Responsive and Identifiable Zwitterionic Ionic Conductive Hydrogel for Bionic Electronic Skin
Author(s) -
Huang Hailong,
Han Lu,
Fu Xiaobin,
Wang Yanling,
Yang Zhongli,
Pan Likun,
Xu Min
Publication year - 2020
Publication title -
advanced electronic materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.25
H-Index - 56
ISSN - 2199-160X
DOI - 10.1002/aelm.202000239
Subject(s) - materials science , wearable computer , soft robotics , self healing hydrogels , biomedical engineering , nanotechnology , wearable technology , electrical conductor , signal (programming language) , capacitive sensing , electronic skin , computer science , robot , artificial intelligence , embedded system , composite material , medicine , programming language , polymer chemistry , operating system
Bionic electronic skin (E‐skin) is considered to be the best candidate for health monitoring sensor, soft robots, biomedical prostheses, artificial intelligence, and wearable electronics devices. However, most existing studies on bionic E‐skin mainly focus on their strain–stress response. Although some works involved specific response to physiological signals such as temperature, sweat, wet, and so on, most reported E‐skins lack special ability to identify multiple stimuli, which limits their applications in real working environment. In this work, an intelligent zwitterionic ionic conductive hydrogel with double network structure (SAA: NaCl/sodium alginate/poly acrylic‐acrylamide) for bionic E‐skin is developed. The SAA hydrogel as E‐skin not only exhibits high sensitivity to strain–stress, but also demonstrates superior sensing performance in human body motion and physiological signal response. More importantly, the SAA hydrogel possesses excellent identification ability to the superposed signals of multiple stimuli. The type of stimulus can be readily distinguished via electrical signal waveform. The SAA hydrogel should be promisingly applied as multiple stimuli responsive and identifiable bionic E‐skin for sports monitoring, human/machine interfaces, and soft robotics.