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Ultra‐Stretchable and Fast Self‐Healing Ionic Hydrogel in Cryogenic Environments for Artificial Nerve Fiber

Chan Wang, Ying Liu, Xuecheng Qu, Bojing Shi, Qiang Zheng, Xubo Lin, Shengyu Chao, Changyong Wang, Jinchuan Zhou, Sun Yu, Gengsheng Mao, Zhou Li

Year
2022
Citations
270

Abstract

Abstract Self‐healing materials behave with irreplaceable advantages in biomimetic intelligent robots (BIR) for avoiding or reducing safety hazards and economic losses from accidental damage during service. However, the self‐healing ability is unreservedly lost and even becomes rigid and fragile in the cryogenic environment where BIR are precisely needed. Here, the authors report a versatile ionic hydrogel with fast self‐healing ability, ultra‐stretchability, and stable conductivity, even at −80 °C. The hydrogel is systematically optimized to improve a hydrogen‐bonded network nanostructure, coordinated achieving a quick self‐healing ability within 10 min, large deformation tolerance of over 7000%, superior conductivity of 11.76 S cm −1 and anti‐freezing ability, which is difficult to obtain simultaneously. Such a hydrogel provides new opportunities for artificial electronic devices in harsh environments. As a prospective application, they fabricate an artificial nerve fiber by mimicking the structure and functions of the myelinated axon, exhibiting the property of fast and potential‐gated signal transmission. This artificial nerve fiber is integrated into a robot for demonstrating a real‐time high fidelity and high throughput information interaction under big deformation and cryogenic temperature. The hydrogel and bionic device will bring pioneering functions for robots and open a broad application scenario in extreme conditions.

Keywords

Materials scienceSelf-healingNanotechnologyRobotFiberComputer scienceComposite materialArtificial intelligence

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