Highly-packed self-assembled graphene oxide film-integrated resistive random-access memory on a silicon substrate for neuromorphic application

Hyun Seok Choi, Jihye Lee, Boram Kim, Jaehong Lee, Byung Gook Park, Yoon Kim, Suck Won Hong

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Resistive random-access memories (RRAMs) based on metal-oxide thin films have been studied extensively for application as synaptic devices in neuromorphic systems. The use of graphene oxide (GO) as a switching layer offers an exciting alternative to other materials such as metal-oxides. We present a newly developed RRAM device fabricated by implementing highly-packed GO layers on a highly doped Si wafer to yield a gradual modulation of the memory as a function of the number of input pulses. By using flow-enabled self-assembly, highly uniform GO thin films can be formed on flat Si wafers in a rapid and simple process. The switching mechanism was explored through proposed scenarios reconstructing the density change of the sp2 cluster in the GO layer, resulting in a gradual conductance modulation. We analyzed that the current in a low resistance state could flow by tunneling or hopping via clusters because the distance between the sp2 clusters in closely-packed GO layers is short. Finally, through a pattern-recognition simulation with a Modified National Institute of Standards and Technology database, the feasibility of using close-packed GO layers as synapse devices was successfully demonstrated.

Original languageEnglish
Article number435201
JournalNanotechnology
Volume33
Issue number43
DOIs
StatePublished - 22 Oct 2022

Keywords

  • graphene oxide
  • neuromorphic system
  • resistive random-access memory
  • synaptic device

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