# Optical control of multiple resistance levels in graphene for memristic applications

https://mdr.nims.go.jp/datasets/ed2140c0-418f-4f2e-b376-406a53b61a0f

## File

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## Id

ed2140c0-418f-4f2e-b376-406a53b61a0f

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-02-05T05:45:49.520321Z

## Updated at

2025-02-06T03:30:34.714038Z

## Published at

2025-02-06T03:30:34.808903Z

## Doi



## First published url

https://doi.org/10.1038/s41699-024-00503-7

## Date published

2024-10-29

## Recorded date published



## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Optical control of multiple resistance levels in graphene for memristic applications
  title_type: original
  lang: en

## Description

- description: "Neuromorphic computing has emphasized the need for memristors with
    non-volatile, multiple conductance levels. This paper demonstrates the potential
    of hexagonal boron nitride (hBN)/graphene heterostructures to act as memristors
    with multiple resistance states that can be optically tuned using visible light.
    The number of resistance levels in graphene can be controlled by modulating doping
    levels, achieved by varying the electric field strength or adjusting the duration
    of optical illumination. Our measurements show that this photodoping of graphene
    results from the optical excitation of charge carriers from the nitrogen-vacancy
    levels of hBN to its conduction band, with these carriers then being transferred
    to graphene by the gate-induced electric field. We develop a qualitative model
    to describe our observations. Additionally, utilizing our device architecture,
    we propose a memristive crossbar array for vector-matrix multiplications.\r\n"
  description_type: abstract
  lang: und

## Creator

- name: Harsimran Kaur Mann
  role: author
- name: Mainak Mondal
  role: author
- name: Vivek Sah
  role: author
- name: Kenji Watanabe
  role: author
  orcid: https://orcid.org/0000-0003-3701-8119
- name: Takashi Taniguchi
  role: author
  orcid: https://orcid.org/0000-0002-1467-3105
- name: Akshay Singh
  role: author
  orcid: https://orcid.org/0000-0003-1059-065X
- name: Aveek Bid
  role: author
  orcid: https://orcid.org/0000-0002-2378-7980

## Contact agent



## Publisher

organization: Springer Science and Business Media LLC

## Managing organization



## Keyword

- subject: Neuromorphic computing
  schema: not_defined
- subject: memristors
  schema: not_defined
- subject: hexagonal boron nitride
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

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## Embargo



## Journal

- title: npj 2D Materials and Applications
  issn: '23977132'
  volume: '8'
  issue: '1'
  article_number: '69'

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## Specimen



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## Fileset

- id: 2341988b-e1fb-4f07-9ee9-c889fd173c59
  filename: s41699-024-00503-7.pdf
  content_type: application/pdf
  size: 1059625
  md5: c72add61c372f5b209f45bf3dd90d4a2

## Thumbnail

fileset_id: 2341988b-e1fb-4f07-9ee9-c889fd173c59
filename: s41699-024-00503-7.pdf