# Graphene nanoribbons with hBN passivated edges grown by high-temperature molecular beam epitaxy

https://mdr.nims.go.jp/datasets/85d61823-7637-4aa9-a15d-a2f84dec9e46

## File

- [Bradford_2023_2D_Mater._10_035035.pdf](https://mdr.nims.go.jp/filesets/a397896a-ddc0-44c1-ba9b-6012cceef765/download) ([Detail](https://mdr.nims.go.jp/filesets/a397896a-ddc0-44c1-ba9b-6012cceef765.md))

## Id

85d61823-7637-4aa9-a15d-a2f84dec9e46

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-02-13T06:30:23.187952Z

## Updated at

2025-02-14T03:30:41.516722Z

## Published at

2025-02-14T03:30:41.597571Z

## Doi



## First published url

https://doi.org/10.1088/2053-1583/acdefc

## Date published

2023-07-01

## Recorded date published

2023-7-1

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Graphene nanoribbons with hBN passivated edges grown by high-temperature
    molecular beam epitaxy
  title_type: original
  lang: en

## Description

- description: Integration of graphene and hexagonal boron nitride (hBN) in lateral
    heterostructures has provided a route to broadly engineer the material properties
    by quantum confinement of electrons or introduction of novel electronic and magnetic
    states at the interface. In this work we demonstrate lateral heteroepitaxial growth
    of graphene nanoribbons (GNRs) passivated by hBN using high-temperature molecular
    beam epitaxy (HT-MBE) to grow graphene in oriented hBN trenches formed ex-situ
    by catalytic nanoparticle etching. High resolution atomic force microscopy (AFM)
    reveals that graphene nanoribbons grow epitaxially from the etched hBN edges,
    and merge to form a graphene nanoribbon network passivated by hBN. Using conductive
    AFM we probe the nanoscale electrical properties of the nanoribbons and observe
    quasiparticle interference patterns caused by intervalley scattering at the graphene/hBN
    interface, which carries implications for the potential transport characteristics
    of hBN passivated GNR devices.
  description_type: abstract
  lang: und

## Creator

- name: Jonathan Bradford
  role: author
- name: Tin S Cheng
  role: author
- name: Tyler S S James
  role: author
- name: Andrei N Khlobystov
  role: author
- name: Christopher J Mellor
  role: author
- name: Kenji Watanabe
  role: author
  orcid: https://orcid.org/0000-0003-3701-8119
  organization: National Institute for Materials Science
- name: Takashi Taniguchi
  role: author
  orcid: https://orcid.org/0000-0002-1467-3105
  organization: National Institute for Materials Science
- name: Sergei V Novikov
  role: author
- name: Peter H Beton
  role: author

## Contact agent



## Publisher

organization: IOP Publishing

## Managing organization



## Keyword

- subject: Graphene nanoribbons
  schema: not_defined
- subject: lateral heteroepitaxial growth
  schema: not_defined
- subject: molecular beam epitaxy
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: 2D Materials
  issn: '20531583'
  volume: '10'
  issue: '3'
  article_number: '035035'

## Conference



## Related item



## Funding

- identifier: EP/K040243/1
  funder_name: Engineering and Physical Sciences Research Council

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: a397896a-ddc0-44c1-ba9b-6012cceef765
  filename: Bradford_2023_2D_Mater._10_035035.pdf
  content_type: application/pdf
  size: 6804591
  md5: ab74a75d166f9988faefc48ccbb78dff

## Thumbnail

fileset_id: a397896a-ddc0-44c1-ba9b-6012cceef765
filename: Bradford_2023_2D_Mater._10_035035.pdf