Human Skin‐Mimicking Ionogel‐Based Electronic Skin for Intelligent Robotic Sorting

Author:

Xia Xuemeng1,Cao Xinyi2,Zhang Bao3,Zhang Leiqian1,Dong Jiancheng1,Qin Jingjing1,Xuan Pengyang1,Liu Leyao1,Sun Yi2,Fan Wei1,Ling Shengjie2,Hofkens Johan45,Lai Feili46ORCID,Liu Tianxi1

Affiliation:

1. Key Laboratory of Synthetic and Biological Colloids Ministry of Education School of Chemical and Material Engineering International Joint Research Laboratory for Nano Energy Composites Jiangnan University Wuxi 214122 P. R. China

2. School of Physical Science and Technology ShanghaiTech University 393 Middle Huaxia Road Shanghai 201210 P. R. China

3. Institute of Polymer Materials School of Materials Science and Engineering South China University of Technology Guangzhou Guangdong 510641 P. R. China

4. Department of Chemistry KU Leuven Celestijnenlaan 200F Leuven 3001 Belgium

5. Department of Molecular Spectroscopy Max Planck Institute for Polymer Research Ackermannweg 10 55128 Mainz Germany

6. State Key Laboratory of Metal Matrix Composites School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai 200240 P. R. China

Abstract

AbstractCreating bionic intelligent robotic systems that emulate human‐like skin perception presents a considerable scientific challenge. This study introduces a multifunctional bionic electronic skin (e‐skin) made from polyacrylic acid ionogel (PAIG), designed to detect human motion signals and transmit them to robotic systems for recognition and classification. The PAIG is synthesized using a suspension of liquid metal and graphene oxide nanosheets as initiators and cross‐linkers. The resulting PAIGs demonstrate excellent mechanical properties, resistance to freezing and drying, and self‐healing capabilities. Functionally, the PAIG effectively captures human motion signals through electromechanical sensing. Furthermore, a bionic intelligent sorting robot system is developed by integrating the PAIG‐based e‐skin with a robotic manipulator. This system leverages its ability to detect frictional electrical signals, enabling precise identification and sorting of materials. The innovations presented in this study hold significant potential for applications in artificial intelligence, rehabilitation training, and intelligent classification systems.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fonds Wetenschappelijk Onderzoek

Publisher

Wiley

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