A Photonic Neuromorphic Autonomous Perceptual Decision System Enabled by MOF‐Based Array
Ye Wang, Shangxun Li, Yisen Yao, Yujie Wei, Guijiang Liu, Haolan Wang, Artur Movsesyan, Liang Pan, Zhiming M. Wang · Advanced Functional Materials · 2025
Abstract Emulating human‐like perceptual decisions remains a critical challenge in humanoid intelligent robots, as existing neuromorphic devices lack multi‐signal parallel processing for advanced cognitive functions such as autonomous situation adaptation and dynamic environment interaction. Here, a neuromorphic autonomous perceptual decision system using an optoelectronic synapse array based on a heterostructure of 1D_ZnO nanorod (NR) and 0D_Cu 3 (HHTP) 2 MOFs is reported. A significant improvement in responsivity (≈6.77 mA W −1 ) and detectivity (≈1.08 × 10 10 Jones) over pristine components is achieved in this 1‐0D heterostructure at 405 nm. Benefiting from the synaptic characteristics of the hybrid architecture, the bio‐visual selective memorizing and forgetting behavior are successfully demonstrated in an array. Moreover, a photonic neuromorphic autonomous perceptual decisions system composed of “visual evidence accumulation‐action preparation‐decision‐action” is developed, enabling an autonomous turn of a robotic dog through multi‐signal processing. This work bridges neuromorphic materials with bioinspired cognitive architectures, offering a scalable framework for autonomous systems that replicate higher‐order brain functions.