Multi‐defect‐engineering in <scp>ZnO</scp> / <scp>GO</scp> heterostructures for optoelectronic synaptic devices with ultra‐high dynamic range and low energy consumption

Abstract In artificial visual systems, optimizing the dynamic range (DR) of optoelectronic synapses is essential for achieving robust and environment‐adaptive perception. However, the inherent trade‐off between photoresponse and dark current noise presents significant challenges in realizing a high DR. This study introduces a flat‐band heterojunction strategy to achieve high DR optoelectronic synapses through a zinc oxide (ZnO) nanowires and graphene oxide (GO) sheets heterostructure, which enables efficient minority carrier trapping under minimal external bias. Through multi‐defect‐engineering in the heterojunction structure, the device demonstrates enhanced persistent photoconductivity (PPC), improved photocurrent gain, and significantly suppressed dark current, achieving an ultra‐high DR of 74.9 dB in two‐terminal optoelectronic synaptic devices while reducing energy consumption to 23 fJ/spike at a bias voltage of 1 mV. Additionally, the devices can emulate typical synaptic functionalities and attain 92.84% pattern recognition accuracy in artificial neural network simulations, offering an energy‐efficient platform for advanced neuromorphic systems. This work offers a generalizable strategy for low‐power, high‐fidelity visual perception systems, advancing intelligent sensing and neuromorphic computing. image