All-Optically Controlled Memristive Device Based on Cu2O/TiO2 Heterostructure Toward Neuromorphic Visual System
Jun Xie,
Xuanyu Shan,
Ningbo Zou,
Ya Lin,
Zhongqiang Wang,
Ye Tao,
Xiaoning Zhao,
Haiyang Xu,
Yichun Liu
Affiliations
Jun Xie
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Xuanyu Shan
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Ningbo Zou
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Ya Lin
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Zhongqiang Wang
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Ye Tao
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Xiaoning Zhao
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Haiyang Xu
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
Yichun Liu
Key Laboratory for UV Light-Emitting Materials and Technology (Ministry of Education), College of Physics,
Northeast Normal University, Changchun, China.
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.
