神经形态工程学
计算机科学
弹道
帧(网络)
材料科学
光电子学
融合
光学
响应度
缩放比例
帧速率
光谱(功能分析)
同种类的
物理
晶体管
人工智能
沉积(地质)
计算机硬件
图像传感器
广谱
计算机视觉
图像融合
多路复用
人工神经网络
图像处理
光谱成像
作者
Guan-Hua Dun,Jia-He Zhang,Xinxing Xie,Ken Qin,Danman Wu,Peng Jia-li,He-Xuan Wang,Zi Wang,Hua-Jing Fang,Danxia Xie,He Tian,Yi Yang,Tian-Ling Ren
标识
DOI:10.1038/s41467-025-66810-9
摘要
Bio-inspired photosynapse hardware with wide spectrum information fusion imaging and neuromorphic processing is promising for complex environments perception. However, integrating ultra-wide spectrum responsivity within a single photosynapse device and scaling to a large array has remained challenging. Here, we demonstrate a 64k-scale (65,536 pixels) ultraviolet-to-mid-infrared photosynapse array based on carbon nanotube/molybdenum oxide heterojunctions. Typical photosynapse behaviors are confirmed in the wide spectrum region of 365 nm (ultraviolet), 532 nm (visible), 1064 nm (near infrared), and 10.6 μm (mid-infrared). A polydopamine-mediated surface treatment enables homogeneous deposition of carbon nanotube/molybdenum oxide films across heterogeneous transistor substrates with 99.96% yield. The photosynapse array enhances image frame similarity from 0.897 to 0.965 in dynamic trajectory prediction. Furthermore, the wide spectrum neuromorphic fusion imaging using photosynapse array achieves 99.58% accuracy in trajectory recognition under challenging conditions, surpassing the 63.93% with visible light alone. This work contributes to paving the way for next-generation autonomous perception. Next-generation autonomous systems call for robust perception capabilities in diverse environments. Dun et al. report an ultraviolet-to-mid-infrared photosynapse array with 65,536 pixels and efficient in situ processing capabilities for dynamic trajectory recognition under challenging conditions.
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