Fully light-modulated memristor based on ZnO/MoOx heterojunction for neuromorphic computing

Author:

Zheng Jiahui1ORCID,Du Yiming1,Dong Yongjun1ORCID,Shan Xuanyu1ORCID,Tao Ye1ORCID,Lin Ya1ORCID,Zhao Xiaoning1ORCID,Wang Zhongqiang1ORCID,Xu Haiyang1,Liu Yichun1ORCID

Affiliation:

1. Key Laboratory for UV Light-Emitting Materials and Technology (Northeast Normal University), Ministry of Education , 5268 Renmin Street, Changchun, China

Abstract

Emerging optoelectronic memristors are promising candidates to develop neuromorphic computing, owing to the combined advantages of photonics and electronics. However, the reversible modulation on device conductance usually requires complicated operations involving hybrid optical/electrical signals. Herein, we design a fully light-modulated memristor based on ZnO/MoOx heterojunction, which exhibits potentiation and depression behaviors under the irradiation of ultraviolet and visible light, respectively. Several basic synaptic functions have been emulated by utilizing optical signals, including short-term/long-term plasticity and spike-number-dependent plasticity. Based on the all-optical modulation characteristics, low-level image pre-processing (including contrast enhancement and noise reduction) is demonstrated. Furthermore, logic operations (“AND,” “NOTq,” and “NIMP”) can be performed by combining various optical signals in the same device. The memristive switching mechanism under optical stimulus can be attributed to barrier change at the heterojunction interface. This work proposes a fully light-modulated memristor based on ZnO/MoOx heterojunction that may promote the development of neuromorphic computing with high efficiency.

Funder

the NSFC Program

the 111 Project

the Foundamental Research Funds for the Central Universitites

the Fund from Jilin Province

the National Key R&D Program of China

the NSFC for Distinguished Young Scholars

Publisher

AIP Publishing

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Emerging Optoelectronic Devices for Brain‐Inspired Computing;Advanced Electronic Materials;2024-09-09

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