Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Sign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Tunable giant valley splitting in edge-free graphene quantum dots on boron nitride

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
English
2017

Tunable giant valley splitting in edge-free graphene quantum dots on boron nitride

0 Datasets

0 Files

English
2017

Get instant academic access to this publication’s datasets.

Create free accountHow it works
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Konstantin ‘kostya’  Novoselov
Konstantin ‘kostya’ Novoselov

The University of Manchester

Verified
Nils M. Freitag
Tobias Reisch
Лариса А. Чижова
+10 more

Abstract

Coherent manipulation of binary degrees of freedom is at the heart of modern quantum technologies. Graphene, the first atomically thin 2D material, offers two binary degrees: the electron spin and the valley degree of freedom. Efficient spin control has been demonstrated in many solid state systems, while exploitation of the valley has only recently been started without control for single electrons. Here, we show that van-der Waals stacking of 2D materials offers a natural platform for valley control due to the relatively strong and spatially varying atomic interaction between adjacent layers. We use an edge-free quantum dot, induced by the tip of a scanning tunneling microscope into graphene on hBN. We demonstrate a valley splitting, which is tunable from -5 meV to +10 meV (including valley inversion) by sub-10-nm displacements of the quantum dot position. This boosts controlled valley splitting of single electrons by more than an order of magnitude, which will probably enable robust spin qubits and valley qubits in graphene.

How to cite this publication

Nils M. Freitag, Tobias Reisch, Лариса А. Чижова, Péter Nemes–Incze, Christian Holl, Colin R. Woods, Р. В. Горбачев, Yang Cao, A. K. Geǐm, Konstantin ‘kostya’ Novoselov, Joachim Burgdörfer, Florian Libisch, Markus Morgenstern (2017). Tunable giant valley splitting in edge-free graphene quantum dots on boron nitride.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2017

Authors

13

Datasets

0

Total Files

0

Language

English

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access