Coexistence of unipolar and bipolar resistive switching in optical synaptic memristors and neuromorphic computing

被引:0
|
作者
Cui, Dongsheng [1 ]
Pei, Mengjiao [2 ]
Lin, Zhenhua [1 ,3 ]
Wang, Yifei [1 ]
Zhang, Hong [1 ]
Gao, Xiangxiang [3 ]
Yuan, Haidong [3 ]
Li, Yun [2 ]
Zhang, Jincheng [1 ,3 ]
Hao, Yue [1 ,3 ]
Chang, Jingjing [1 ,3 ]
机构
[1] Xidian Univ, Sch Microelect, State Key Lab Wide Bandgap Semicond Devices & Inte, Xian 710071, Peoples R China
[2] Nanjing Univ, Collaborat Innovat Ctr Adv Microstruct, Sch Elect Sci & Engn, Natl Lab Solid State Microstruct, Nanjing 210093, Peoples R China
[3] Xidian Univ, Acad Adv Interdisciplinary Res, Adv Interdisciplinary Res Ctr Flexible Elect, Xian 710071, Peoples R China
来源
CHIP | 2025年 / 4卷 / 01期
基金
中国国家自然科学基金;
关键词
RRAM; URS; BRS; Optical synapse; Neuro- morphic computing; 2-DIMENSIONAL MATERIALS;
D O I
10.1016/j.chip.2024.100122
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The human brain possesses a highly developed capability for sensing-memory-computing, and the integration of hardware with brain-like functions represents a novel approach to overcoming the von Neumann bottleneck. In this study, Ga2O3 photoelectric memristors were successfully fabricated, enabling efficient visual information processing and complex recognition through the integration of optoelectronic synapses with digital storage. The memristors with a Pt/Ga2O3/Pt sandwich structure exhibit the coexistence of unipolar resistive switching (URS) and bipolar resistive switching (BRS), coupled with an impressive switching ratio and stable retention characteristics. The device demonstrates robust photo-responsive properties to ultraviolet (UV) light, which enables the realization of an array of 16 photoconductor types through the manipulation of four-timeframe pulse sequences. Exposure of the device to UV light elicits stable synaptic behaviors, including paired-pulse facilitation (PPF), short-term memory (STM), long-term memory (LTM), as well as learning-forgetting- relearning behavior. Moreover, the device exhibits outstanding image sensing, image memory, and neuromorphic visual preprocessing capabilities as a neuromorphic vision sensor (NVS). The integration of light pulse potentiation with electrical pulse depression yields a remarkable 100 conductances with superior linearity. This advanced functionality is further validated by the ability of the device to facilitate the recognition of 85.3% of handwritten digits by artificial neural networks (ANNs), which underscores the significant potential of artificial synapses in mimicking biological neural.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Magnesium-doped ZnO thin film memristors for enhanced synaptic plasticity and resistive switching in neuromorphic computing
    Ali, Sarfraz
    Khan, Muhammad Farooq
    Ullah, Muhammad Abaid
    Iqbal, Muhammad Waqas
    JOURNAL OF ALLOYS AND COMPOUNDS, 2025, 1015
  • [2] Resistive switching and synaptic characteristics of Hf-doped ZnO sandwiched between HfO2-based memristors for neuromorphic computing
    Feng, Jianhao
    Liao, Jiajia
    Jiang, Yanping
    Bai, Fenyun
    Zhu, Jianyuan
    Tang, Xingui
    Tang, Zhenhua
    Zhou, Yichun
    MATERIALS TODAY COMMUNICATIONS, 2024, 40
  • [3] Bipolar Analog Memristors as Artificial Synapses for Neuromorphic Computing
    Wang, Rui
    Shi, Tuo
    Zhang, Xumeng
    Wang, Wei
    Wei, Jinsong
    Lu, Jian
    Zhao, Xiaolong
    Wu, Zuheng
    Cao, Rongrong
    Long, Shibing
    Liu, Qi
    Liu, Ming
    MATERIALS, 2018, 11 (11):
  • [4] Dynamic resistive switching devices for neuromorphic computing
    Wu, Yuting
    Wang, Xinxin
    Lu, Wei D.
    SEMICONDUCTOR SCIENCE AND TECHNOLOGY, 2022, 37 (02)
  • [5] Analog-Type Resistive Switching Devices for Neuromorphic Computing
    Zhang, Wenbin
    Gao, Bin
    Tang, Jianshi
    Li, Xinyi
    Wu, Wei
    Qian, He
    Wu, Huaqiang
    PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS, 2019, 13 (10):
  • [6] Scalable nanocomposite parylene-based memristors: Multifilamentary resistive switching and neuromorphic applications
    Matsukatova, Anna N.
    Vdovichenko, Artem Yu.
    Patsaev, Timofey D.
    Forsh, Pavel A.
    Kashkarov, Pavel K.
    Demin, Vyacheslav A.
    Emelyanov, Andrey V.
    NANO RESEARCH, 2023, 16 (02) : 3207 - 3214
  • [7] Strategy for the Integrated Design of Ferroelectric and Resistive Memristors for Neuromorphic Computing Applications
    Lee, Jung-Kyu
    Park, Yongjin
    Seo, Euncho
    Park, Woohyun
    Youn, Chaewon
    Lee, Sejoon
    Kim, Sungjun
    ACS APPLIED ELECTRONIC MATERIALS, 2025, 7 (07) : 3055 - 3066
  • [8] Resistive switching in emerging materials and their characteristics for neuromorphic computing
    Asif, Mohd
    Kumar, Ashok
    MATERIALS TODAY ELECTRONICS, 2022, 1
  • [9] Multistate resistive switching behaviors for neuromorphic computing in memristor
    Sun, B.
    Ranjan, S.
    Zhou, G.
    Guo, T.
    Xia, Y.
    Wei, L.
    Zhou, Y. N.
    Wu, Y. A.
    MATERIALS TODAY ADVANCES, 2021, 9
  • [10] Semiempirical Modeling of Reset Transitions in Unipolar Resistive-Switching Based Memristors
    Picos, Rodrigo
    Roldan, Juan Bautista
    Al Chawa, Mohamed Moner
    Garcia-Fernandez, Pedro
    Jimenez-Molinos, Francisco
    Garcia-Moreno, Eugeni
    RADIOENGINEERING, 2015, 24 (02) : 420 - 424