Three Musketeers: demonstration of multilevel memory, selector, and synaptic behaviors from an Ag-GeTe based chalcogenide material

  • Min Ji Yu
  • , Kyung Rock Son
  • , Atul C. Khot
  • , Dae Yun Kang
  • , Ji Hoon Sung
  • , Il Gyu Jang
  • , Yogesh D. Dange
  • , Tukaram D. Dongale
  • , Tae Geun Kim*
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    55 Citations (Scopus)

    Abstract

    Functional neuronal computing systems that support information diversification require high-density memory with selector devices to reduce leakage current in cross-point architectures, which drives us to develop a functional switching layer that operates as three distinct devices, namely non-volatile memory, selector, and synaptic devices, using a GeTe-based single material system. In this study, amorphous Ag-GeTe switching layers are engineered by doping with Te species to achieve either resistive switching (RS) or threshold switching properties. The Ag/Ag-GeTe/Ag memory device exhibits multilevel characteristics via a tunable compliance current approach. By comparison, Ag/Ag-GeTex/Ag selector device provides excellent selectivity (>106) with a very low OFF-current (∼10−11 A). The RS mechanism for memory and selector devices is interrogated by using conductive atomic force microscopy. Moreover, the Ag/Ag-GeTe/Ag RS device mimics a cohort of basic and complex synaptic plasticity properties, including potentiation-depression and four-spike time-dependent plasticity rules that include asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The capability of the synaptic devices to detect image edges is demonstrated by using a convolution neural network. The present work showcases the multi-functionality of Ag-GeTe materials, which will likely emerge as a prominent candidate for high-density cross-point architecture-based neuromorphic computing systems.

    Original languageEnglish
    Pages (from-to)1984-1995
    Number of pages12
    JournalJournal of Materials Research and Technology
    Volume15
    DOIs
    Publication statusPublished - 2021 Nov 1

    Bibliographical note

    Funding Information:
    This work was supported by the National Research Foundation of Korea grant funded by the Korean government (No. 2016R1A3B1908249 ) and the Samsung Semiconductor Research Center in Korea University ( IO201211-08116-01 ).

    Publisher Copyright:
    © 2021 The Author(s)

    Keywords

    • Amorphous Ag-GeTe
    • Convolutional neural network edge detection
    • Multilevel resistive switching
    • Neuromorphic computing
    • Selector device

    ASJC Scopus subject areas

    • Ceramics and Composites
    • Biomaterials
    • Surfaces, Coatings and Films
    • Metals and Alloys

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