A Bifunctional Memristor Enables Multiple Neuromorphic Computing Applications

Nikolay Lyapunov, Xiao Dong Zheng, Kevin Yang, Hao Min Liu, Kai Zhou, Song Hua Cai, Tsz Lung Ho, Chun Hung Suen, Ming Yang, Jiong Zhao, Xiaoyuan Zhou, Ji Yan Dai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

As a promising building block of the emerging neuromorphic computing hardware, memristive structures with multi-functionalities are highly desired to implement diversified computing applications in a single device. However, the demonstration of such multi-functional structures remains limited. In this work, an Ag/GeS/Pt-based bifunctional memory structure with both long-term and short-term memristive behaviors is reported, enabling multiple neuromorphic computing applications in a single device. It is found that the unexpected short-term switching in Ag/GeS/Pt can not only be used to simulate learning/relearning and forgetting behavior but can also be implemented for reservoir computing. While for long-term switching memristive behavior, its application is demonstrated as the traditional memory. The work reveals a novel coexistence of the two types of resistive switching, shedding light on various neuromorphic computing applications such as reservoir computing and traditional memory realized in a single memristive device.

Original languageEnglish
Article number2101235
JournalAdvanced Electronic Materials
Volume8
Issue number7
DOIs
Publication statusPublished - Jul 2022

Keywords

  • GeS
  • memristor
  • paired-pulse facilitation
  • reservoir computing
  • resistive switching

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials

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