Transistor‐Based Bio‐Hybrid Artificial Afferent Nerves for a Mainly Bio‐Composite Reflex Arc System

The development of sustainable high‐performance bio‐hybrid neuromorphic electronics is essential for the next generation of intelligent human–machine interfaces. However, achieving systemic biocompatibility while maintaining low power consumption and long‐term stability remains a formidable challenge. Here, we report a high‐performance artificial transmission nerve based on a gelatin–starch (GS) nanoparticle ion–gel dielectric, optimized through a synergistic dual‐annealing protocol. The starch incorporation strengthens the intermolecular hydrogen‐bonding network, whereas the tailored annealing optimizes the electric double‐layer interface, yielding a benchmark energy consumption of 2.00 fJ per synaptic event and exceptional cycling stability (> 10 4 cycles). Leveraging these characteristics, we demonstrated a low‐power Morse‐code‐based reservoir computing (RC) system capable of 98.25% recognition accuracy for the full A−Z alphabet. Furthermore, by integrating these transistors with bio‐composite sensors and actuators, we constructed a self‐contained artificial reflex arc. This mainly bio‐composite system faithfully emulates the hierarchical perception and spatiotemporal response dynamics of human skin, where electrode‐length‐modulated sensitivity gradients trigger distinct motor behaviors. This work provides a robust framework for eco‐friendly neuromorphic hardware and paves the way for advanced soft robotics and intelligent prosthetics with bio‐realistic environmental interaction capabilities.