A Self‐Healing Ionic Synaptic Device for Resilient Neuromorphic Motion Control of a Mechanical Arm

Biological neuromuscular systems seamlessly integrate signal sensing, synaptic processing, and motor execution, all while possessing remarkable self‐healing capabilities to maintain functional stability after injury. Mimicking this sophisticated integration of neural signal processing and action with embodied resilience remains a grand challenge for artificial systems. Here, we report a self‐healing ionic synaptic device that leverages ion‐mediated signal transmission and dynamically reversible borate ester bonds within a bilayer hydrogel matrix. The device emulates key synaptic functions, including short‐term plasticity, paired‐pulse facilitation, and experience‐accelerated learning. More importantly, it exhibits bio‐inspired dynamic recovery capabilities, autonomously restoring its synaptic functions after severe mechanical damage (100% recovery in Young's modulus). By integrating this device into a neuromorphic control circuit, we construct an artificial neuromuscular system that successfully translates pulse signals into precise, graded movements of a mechanical arm, mimicking muscle contraction and relaxation. The system maintains robust performance even after device damage and self‐healing, demonstrating features such as Morse code recognition and Pavlovian associative learning. This work provides a paradigm for developing resilient, brain‐inspired intelligent systems with perception‐action capabilities for soft robotics and adaptive human‐machine interfaces.