All-Optically Controlled Memristive Device Based on Cu <sub>2</sub> O/TiO <sub>2</sub> Heterostructure Toward Neuromorphic Visual System
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, Cu<sub>2</sub>O exhibits outstanding theoretical photoelectric conversion efficiency and broadband photoresponse. In this work, an all-optically controlled memristor based on the Cu<sub>2</sub>O/TiO<sub>2</sub>/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.
Authors
- Xiaoning Zhao (ORCID: https://orcid.org/0000-0002-0082-2288)
- Ya Lin (ORCID: https://orcid.org/0000-0003-1421-8126)
- Xuanyu Shan (ORCID: https://orcid.org/0000-0002-6161-7835)
- Jun Xie (ORCID: https://orcid.org/0000-0001-6657-0880)
- Nanzhi Zou
- Yichun Liu (ORCID: https://orcid.org/0000-0002-8628-6112)
- Zhongqiang Wang (ORCID: https://orcid.org/0000-0002-1133-6058)
- Ye Tao (ORCID: https://orcid.org/0000-0002-3760-7637)
- Haiyang Xu
Institutions
- Northeast Normal University (CN)
Publication Details
- Journal
- Research
- Published
- 2024-12-27
- DOI
- https://doi.org/10.34133/research.0580
- Citations
- 16
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.34
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- People's Government of Jilin Province