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Vertical organic synapse expandable to 3D crossbar array

Author

Listed:
  • Yongsuk Choi

    (Yonsei University)

  • Seyong Oh

    (Sungkyunkwan University)

  • Chuan Qian

    (Yonsei University)

  • Jin-Hong Park

    (Sungkyunkwan University
    Sungkyunkwan University)

  • Jeong Ho Cho

    (Yonsei University)

Abstract

Recently, three-terminal synaptic devices have attracted considerable attention owing to their nondestructive weight-update behavior, which is attributed to the completely separated terminals for reading and writing. However, the structural limitations of these devices, such as a low array density and complex line design, are predicted to result in low processing speeds and high energy consumption of the entire system. Here, we propose a vertical three-terminal synapse featuring a remote weight update via ion gel, which is also extendable to a crossbar array structure. This synaptic device exhibits excellent synaptic characteristics, which are achieved via precise control of ion penetration onto the vertical channel through the weight-control terminal. Especially, the applicability of the developed vertical organic synapse array to neuromorphic computing is demonstrated using a simple crossbar synapse array. The proposed synaptic device technology is expected to be an important steppingstone to the development of high-performance and high-density neural networks.

Suggested Citation

  • Yongsuk Choi & Seyong Oh & Chuan Qian & Jin-Hong Park & Jeong Ho Cho, 2020. "Vertical organic synapse expandable to 3D crossbar array," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17850-w
    DOI: 10.1038/s41467-020-17850-w
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    Cited by:

    1. He-Shan Zhang & Xue-Mei Dong & Zi-Cheng Zhang & Ze-Pu Zhang & Chao-Yi Ban & Zhe Zhou & Cheng Song & Shi-Qi Yan & Qian Xin & Ju-Qing Liu & Yin-Xiang Li & Wei Huang, 2022. "Co-assembled perylene/graphene oxide photosensitive heterobilayer for efficient neuromorphics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Yao Ni & Jiaqi Liu & Hong Han & Qianbo Yu & Lu Yang & Zhipeng Xu & Chengpeng Jiang & Lu Liu & Wentao Xu, 2024. "Visualized in-sensor computing," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Seokho Seo & Beomjin Kim & Donghoon Kim & Seungwoo Park & Tae Ryong Kim & Junkyu Park & Hakcheon Jeong & See-On Park & Taehoon Park & Hyeok Shin & Myung-Su Kim & Yang-Kyu Choi & Shinhyun Choi, 2022. "The gate injection-based field-effect synapse transistor with linear conductance update for online training," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    4. Dong Gue Roe & Dong Hae Ho & Yoon Young Choi & Young Jin Choi & Seongchan Kim & Sae Byeok Jo & Moon Sung Kang & Jong-Hyun Ahn & Jeong Ho Cho, 2023. "Humanlike spontaneous motion coordination of robotic fingers through spatial multi-input spike signal multiplexing," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
    5. Han Xu & Dashan Shang & Qing Luo & Junjie An & Yue Li & Shuyu Wu & Zhihong Yao & Woyu Zhang & Xiaoxin Xu & Chunmeng Dou & Hao Jiang & Liyang Pan & Xumeng Zhang & Ming Wang & Zhongrui Wang & Jianshi Ta, 2023. "A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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