Nanoscale Memristor Device as Synapse in Neuromorphic Systems

被引:3339
|
作者
Jo, Sung Hyun [1 ]
Chang, Ting [1 ]
Ebong, Idongesit [1 ]
Bhadviya, Bhavitavya B. [1 ]
Mazumder, Pinaki [1 ]
Lu, Wei [1 ]
机构
[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
Nanoelectronics; neuromorphic system; memristor; synaptic adaptation; spike-timing dependent plasticity; RESISTANCE; MODEL;
D O I
10.1021/nl904092h
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A memristor is a two-terminal electronic device whose conductance can be precisely modulated by charge or flux through it. Here we experimentally demonstrate a nanoscale silicon-based memristor device and show that a hybrid system composed of complementary metal oxide semiconductor neurons and memristor synapses can support important synaptic functions such as spike timing dependent plasticity. Using memristors as synapses in neuromorphic circuits can potentially offer both high connectivity and high density required for efficient computing.
引用
收藏
页码:1297 / 1301
页数:5
相关论文
共 50 条
  • [41] Review of memristor devices in neuromorphic computing: materials sciences and device challenges
    Li, Yibo
    Wang, Zhongrui
    Midya, Rivu
    Xia, Qiangfei
    Yang, J. Joshua
    JOURNAL OF PHYSICS D-APPLIED PHYSICS, 2018, 51 (50)
  • [42] Overview of amorphous carbon memristor device, modeling, and applications for neuromorphic computing
    Wu, Jie
    Yang, Xuqi
    Chen, Jing
    Li, Shiyu
    Zhou, Tianchen
    Cai, Zhikuang
    Lian, Xiaojuan
    Wang, Lei
    NANOTECHNOLOGY REVIEWS, 2024, 13 (01)
  • [43] Novel ferroelectric FET based synapse for neuromorphic systems
    Mulaosmanovic, H.
    Ocker, J.
    Mueller, S.
    Noack, M.
    Mueller, J.
    Polakowski, P.
    Mikolajick, T.
    Slesazeck, S.
    2017 SYMPOSIUM ON VLSI TECHNOLOGY, 2017, : T176 - T177
  • [44] RRAM-based synapse devices for neuromorphic systems
    Moon, K.
    Lim, S.
    Park, J.
    Sung, C.
    Oh, S.
    Woo, J.
    Lee, J.
    Hwang, H.
    FARADAY DISCUSSIONS, 2019, 213 : 421 - 451
  • [45] Modulating 3D memristor synapse by analog spiking pulses for bioinspired neuromorphic computing
    Liu, Qi
    Zhang, XuMeng
    Luo, Qing
    Zhao, XiaoLong
    Lv, HangBing
    Long, ShiBing
    Liu, Ming
    SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY, 2018, 61 (08)
  • [46] Modulating 3D memristor synapse by analog spiking pulses for bioinspired neuromorphic computing
    Qi Liu
    XuMeng Zhang
    Qing Luo
    XiaoLong Zhao
    HangBing Lv
    ShiBing Long
    Ming Liu
    Science China(Physics,Mechanics & Astronomy), 2018, (08) : 79 - 85
  • [47] Dual-terminal artificial synapse in two-dimensional CrSBr memristor for neuromorphic computing
    Li, Zhi
    Liu, Ruiqi
    Chu, Yafei
    Feng, Sihua
    Lan, Weican
    Duan, Hengli
    Liu, Chaocheng
    Yan, Wensheng
    JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS, 2024, 35 (16)
  • [48] Multifunctional Artificial Electric Synapse of MoSe2-Based Memristor toward Neuromorphic Application
    Li, Yumo
    Sun, Hao
    Yue, Langchun
    Yang, Fengxia
    Dong, Xiaofei
    Chen, Jianbiao
    Chen, Jiangtao
    Zhang, Xuqiang
    Zhao, Yun
    Chen, Kai
    Li, Yan
    JOURNAL OF PHYSICAL CHEMISTRY LETTERS, 2025, 16 (05): : 1175 - 1183
  • [49] SPICE Study of STDP Characteristics in a Drift and Diffusive Memristor-Based Synapse for Neuromorphic Computing
    Hu, Suman
    Kang, Jaehyun
    Kim, Taeyoon
    Lee, Suyoun
    Park, Jong Keuk
    Kim, Inho
    Kim, Jaewook
    Kwak, Joon Young
    Park, Jongkil
    Kim, Gyu-Tae
    Choi, Shinhyun
    Jeong, Yeonjoo
    IEEE ACCESS, 2022, 10 : 6381 - 6392
  • [50] Modulating 3D memristor synapse by analog spiking pulses for bioinspired neuromorphic computing
    Qi Liu
    XuMeng Zhang
    Qing Luo
    XiaoLong Zhao
    HangBing Lv
    ShiBing Long
    Ming Liu
    Science China Physics, Mechanics & Astronomy, 2018, 61