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

Research output: Contribution to journalArticlepeer-review

28 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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