IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v12y2021i1d10.1038_s41467-020-20257-2.html
   My bibliography  Save this article

Two-dimensional ferroelectric channel transistors integrating ultra-fast memory and neural computing

Author

Listed:
  • Shuiyuan Wang

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Lan Liu

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Lurong Gan

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Huawei Chen

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Xiang Hou

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Yi Ding

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Shunli Ma

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • David Wei Zhang

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

  • Peng Zhou

    (ASIC & System State Key Lab., School of Microelectronics, Fudan University)

Abstract

With the advent of the big data era, applications are more data-centric and energy efficiency issues caused by frequent data interactions, due to the physical separation of memory and computing, will become increasingly severe. Emerging technologies have been proposed to perform analog computing with memory to address the dilemma. Ferroelectric memory has become a promising technology due to field-driven fast switching and non-destructive readout, but endurance and miniaturization are limited. Here, we demonstrate the α-In2Se3 ferroelectric semiconductor channel device that integrates non-volatile memory and neural computation functions. Remarkable performance includes ultra-fast write speed of 40 ns, improved endurance through the internal electric field, flexible adjustment of neural plasticity, ultra-low energy consumption of 234/40 fJ per event for excitation/inhibition, and thermally modulated 94.74% high-precision iris recognition classification simulation. This prototypical demonstration lays the foundation for an integrated memory computing system with high density and energy efficiency.

Suggested Citation

  • Shuiyuan Wang & Lan Liu & Lurong Gan & Huawei Chen & Xiang Hou & Yi Ding & Shunli Ma & David Wei Zhang & Peng Zhou, 2021. "Two-dimensional ferroelectric channel transistors integrating ultra-fast memory and neural computing," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20257-2
    DOI: 10.1038/s41467-020-20257-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-20257-2
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-020-20257-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dongyang Yang & Jing Liang & Jingda Wu & Yunhuan Xiao & Jerry I. Dadap & Kenji Watanabe & Takashi Taniguchi & Ziliang Ye, 2024. "Non-volatile electrical polarization switching via domain wall release in 3R-MoS2 bilayer," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    2. Sahar Pakdel & Asbjørn Rasmussen & Alireza Taghizadeh & Mads Kruse & Thomas Olsen & Kristian S. Thygesen, 2024. "High-throughput computational stacking reveals emergent properties in natural van der Waals bilayers," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Yong Liu & Mingjian Zhang & Zhuan Wang & Jiandong He & Jie Zhang & Sheng Ye & Xiuli Wang & Dongfeng Li & Heng Yin & Qianhong Zhu & Huanwang Jing & Yuxiang Weng & Feng Pan & Ruotian Chen & Can Li & Fen, 2022. "Bipolar charge collecting structure enables overall water splitting on ferroelectric photocatalysts," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    4. Guangdi Feng & Qiuxiang Zhu & Xuefeng Liu & Luqiu Chen & Xiaoming Zhao & Jianquan Liu & Shaobing Xiong & Kexiang Shan & Zhenzhong Yang & Qinye Bao & Fangyu Yue & Hui Peng & Rong Huang & Xiaodong Tang , 2024. "A ferroelectric fin diode for robust non-volatile memory," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Sangyong Park & Dongyoung Lee & Juncheol Kang & Hojin Choi & Jin-Hong Park, 2023. "Laterally gated ferroelectric field effect transistor (LG-FeFET) using α-In2Se3 for stacked in-memory computing array," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    6. Rong Bao & Shuiyuan Wang & Xiaoxian Liu & Kejun Tu & Jingquan Liu & Xiaohe Huang & Chunsen Liu & Peng Zhou & Shen Liu, 2024. "Neuromorphic electro-stimulation based on atomically thin semiconductor for damage-free inflammation inhibition," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20257-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.