journal article·2026-03-16Open access

Self-revival iontronic neuromorphic devices for robust human-machine interaction

Yanfei Li, Jiayi Chen, Shilin Tang, Chenxi Zhu, Zhanpeng Hong, Xuefeng Lin, Xiang He, Jianyu Ming, Ning Liu, Linghai Xie, Haifeng Ling

npj Flexible Electronics· Volume 10· Issue 1

Abstract

Flexible neuromorphic devices exhibit substantial promise for applications in next-generation intelligent human-machine interaction systems. While, the primary hurdle for flexible neuromorphic devices lies in functional impairment arising from mechanical damage. Here, earthworm-inspired self-revival iontronic neuromorphic devices are fabricated with a decentralized architecture by polymer ion gel as an ion transport network. In the integrated device, a discrete hemispheric array structure is engineered to arrest crack propagation by physical isolation. Furthermore, the devices exhibit self-revival capacity after damage due to the rapidly-formed dynamic chemical bonds and transferable properties of independent hemispheric units. Notably, the iontronic neuromorphic devices are applied for the motion-cognition nerve system, achieving a human body movement tracking accuracy rate of 98%. Even when damaged, the system maintains a 96% tracking accuracy rate after self-revival. This work contributes to the design of novel neuromorphic devices and demonstrates significant potential for revolutionizing fields such as prosthetics, rehabilitation, and interactive robotics.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Materials and Mechanics · Advanced Memory and Neural Computing

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