神经形态工程学
异质结
材料科学
光电子学
计算机科学
物联网
纳米技术
人工智能
嵌入式系统
人工神经网络
作者
Jun Xie,Xuanyu Shan,Nanzhi Zou,Ya Lin,Zhongqiang Wang,Ye Tao,Xiaoning Zhao,Haiyang Xu,Yichun Liu
出处
期刊:Research
[American Association for the Advancement of Science]
日期:2024-12-27
卷期号:8: 0580-0580
被引量:16
标识
DOI:10.34133/research.0580
摘要
The optoelectronic memristor integrates the multifunctionalities of image sensing, storage, and processing, which has been considered as the leading candidate to construct novel neuromorphic visual system. In particular, memristive materials with all-optical modulation and complementary metal oxide semiconductor (CMOS) compatibility are highly desired for energy-efficient image perception. As a p-type oxide material, Cu2O exhibits outstanding theoretical photoelectric conversion efficiency and broadband photoresponse. In this work, an all-optically controlled memristor based on the Cu2O/TiO2/sodium alginate nanocomposite film is developed. Optical potentiation and depression behaviors have been implemented by utilizing visible (680 nm) and ultraviolet (350 nm) light. Furthermore, a 7 × 9 optoelectronic memristive array with satisfactory device variation and environment stability is constructed to emulate the image preprocessing function in biological retina. The random noise can be reduced effectively by utilizing bidirectional optical input. Beneficial from the image preprocessing function, the accuracy of handwritten digit classification increases more than 60%. Our work presents a pathway toward high-efficient neuromorphic visual system and promotes the development of artificial intelligence technology.
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