IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-16766-9.html
   My bibliography  Save this article

Oxidation-boosted charge trapping in ultra-sensitive van der Waals materials for artificial synaptic features

Author

Listed:
  • Feng-Shou Yang

    (National Chung Hsing University
    National Tsing Hua University)

  • Mengjiao Li

    (National Chung Hsing University)

  • Mu-Pai Lee

    (National Chung Hsing University
    National Chiao Tung University)

  • I-Ying Ho

    (National Chung Hsing University
    National Tsing Hua University)

  • Jiann-Yeu Chen

    (National Chung Hsing University)

  • Haifeng Ling

    (Nanjing University of Posts&Telecommunications)

  • Yuanzhe Li

    (Nanjing University of Posts&Telecommunications)

  • Jen-Kuei Chang

    (National Chung Hsing University)

  • Shih-Hsien Yang

    (National Chung Hsing University)

  • Yuan-Ming Chang

    (National Chung Hsing University)

  • Ko-Chun Lee

    (National Chung Hsing University)

  • Yi-Chia Chou

    (National Chiao Tung University)

  • Ching-Hwa Ho

    (National Taiwan University of Science and Technology)

  • Wenwu Li

    (National Chung Hsing University
    East China Normal University)

  • Chen-Hsin Lien

    (National Tsing Hua University)

  • Yen-Fu Lin

    (National Chung Hsing University
    National Chung Hsing University
    National Chung Hsing University)

Abstract

Exploitation of the oxidation behaviour in an environmentally sensitive semiconductor is significant to modulate its electronic properties and develop unique applications. Here, we demonstrate a native oxidation-inspired InSe field-effect transistor as an artificial synapse in device level that benefits from the boosted charge trapping under ambient conditions. A thin InOx layer is confirmed under the InSe channel, which can serve as an effective charge trapping layer for information storage. The dynamic characteristic measurement is further performed to reveal the corresponding uniform charge trapping and releasing process, which coincides with its surface-effect-governed carrier fluctuations. As a result, the oxide-decorated InSe device exhibits nonvolatile memory characteristics with flexible programming/erasing operations. Furthermore, an InSe-based artificial synapse is implemented to emulate the essential synaptic functions. The pattern recognition capability of the designed artificial neural network is believed to provide an excellent paradigm for ultra-sensitive van der Waals materials to develop electric-modulated neuromorphic computation architectures.

Suggested Citation

  • Feng-Shou Yang & Mengjiao Li & Mu-Pai Lee & I-Ying Ho & Jiann-Yeu Chen & Haifeng Ling & Yuanzhe Li & Jen-Kuei Chang & Shih-Hsien Yang & Yuan-Ming Chang & Ko-Chun Lee & Yi-Chia Chou & Ching-Hwa Ho & We, 2020. "Oxidation-boosted charge trapping in ultra-sensitive van der Waals materials for artificial synaptic features," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16766-9
    DOI: 10.1038/s41467-020-16766-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-16766-9
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-020-16766-9?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. 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.

    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:11:y:2020:i:1:d:10.1038_s41467-020-16766-9. 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.