Versatile NbOx-Based Volatile Memristor for Artificial Intelligent Applications

Dongyeol Ju, Sungjun Kim

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

To achieve cost-effectiveness, researchers are exploring various memristors for their adaptation in neuromorphic computing. Recent studies have focused on developing versatile functioning singular memristors, such as those involved in on-receptor computing, which integrates sensory functions into current neuromorphic computing paradigms. Additionally, adaptations like reservoir computing are being investigated for computing systems. In this study, a memristor composed of a stack of Ti/NbOx/Pt layers is fabricated to explore multifunctional behaviors within a single memristor. By applying bias toward the top Ti electrode, gradual current changes with volatile features are demonstrated, revealing an ion-migration-based nonfilamentary switching memristor. Leveraging this volatile functionality, an artificial nociceptor is first implemented, demonstrating key functions of biological nociceptors including thresholding, relaxation, no-adaptation, and sensitization. Subsequently, synapse emulation akin to the biological brain is achieved through easy conductance potentiation and depression with diverse synapse functions, enabling the memristor to mimic learning activities with spike firing. Lastly, computational applications are explored by adapting edge computing and multi-bit reservoir computing, expanding the memristor's applications across diverse fields with versatile behaviors.

Original languageEnglish
Article number2409436
JournalAdvanced Functional Materials
Volume34
Issue number49
DOIs
StatePublished - 2 Dec 2024

Keywords

  • artificial synapse
  • associative conditioning
  • neuromorphic computing
  • niobium oxide
  • volatile memristor

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