Kirigami-Inspired 3D-Printable MXene Organohydrogels for Soft Electronics

被引:44
|
作者
Zhuo, Fengling [1 ]
Zhou, Jian [1 ,2 ]
Liu, Ying [1 ]
Xie, Jianfei [3 ]
Chen, Hui [1 ]
Wang, Xiaozhi [4 ]
Luo, Jikui [4 ]
Fu, Yongqing [5 ]
Elmarakbi, Ahmed [5 ]
Duan, Huigao [1 ,2 ]
机构
[1] Hunan Univ, Coll Mech & Vehicle Engn, Changsha 410082, Peoples R China
[2] Hunan Univ, Greater Bay Area Inst Innovat, Guangzhou 511300, Peoples R China
[3] Cent South Univ, Xiangya Hosp 3, Nursing Dept, Changsha 410013, Peoples R China
[4] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou 310027, Peoples R China
[5] Northumbria Univ, Fac Engn & Environm, Newcastle Upon Tyne NE1 8ST, England
关键词
Kirigami-inspired; organohydrogels; wearable sensor; human-machine interfaces; Morse code; HYDROGELS; DESIGN; STRAIN; SENSORS;
D O I
10.1002/adfm.202308487
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Conductive hydrogels are compelling materials for the development of soft electronics; however, their essential attributes such as high sensitivity, excellent stretchability, and environmental stability have rarely been achieved simultaneously in one hydrogel. Herein, a Kirigami-inspired strategy is proposed to improve organohydrogel sensitivity without sacrificing their mechanical stretchability and environmental stability. The organohydrogels with multiple interpenetrating networks are synthesized by introducing sodium alginate nanofibrils and conductive MXene nanoflakes into polymer double networks infiltrated with glycerol-water mixtures, featuring remarkable stretchability (>5000%), good sensitivity, and water retention (>30 days). The Kirigami structures are further applied to enhance strain sensitivity, achieving a gauge factor of 29.1, which is approximate to 5.5 times that of an unstructured organohydrogel. Using the Kirigami-inspired sensors, a durable glove is developed for grabbing underwater objects through operating a robotic arm, demonstrating a subaqueous interactive human-machine interfacing.Meanwhile, by integrating the wearable sensor with a machine learning algorithm, a wearable Morse code intelligent recognition system is demonstrated, enabling real-time conversion of Morse code signs into speech with superior recognition accuracy (>99%) and fast response time (approximate to 17 ms). This work offers a new route to synthesize highly sensitive, stretchable, and extremely tolerant organohydrogels, providing a promising platform for next-generation soft electronics.
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页数:13
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