RDL logo
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
​
​
Sign inGet started
​
​

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

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
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. A Force‐Engineered Lint Roller for Superclean Graphene

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
English
2019

A Force‐Engineered Lint Roller for Superclean Graphene

0 Datasets

0 Files

English
2019
Advanced Materials
Vol 31 (43)
DOI: 10.1002/adma.201902978

Get instant academic access to this publication’s datasets.

Create free accountHow it works

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
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.
Konstantin ‘kostya’  Novoselov
Konstantin ‘kostya’ Novoselov

The University of Manchester

Verified
Luzhao Sun
Li Lin
Zihao Wang
+15 more

Abstract

Contamination is a major concern in surface and interface technologies. Given that graphene is a 2D monolayer material with an extremely large surface area, surface contamination may seriously degrade its intrinsic properties and strongly hinder its applicability in surface and interfacial regions. However, large-scale and facile treatment methods for producing clean graphene films that preserve its excellent properties have not yet been achieved. Herein, an efficient postgrowth treatment method for selectively removing surface contamination to achieve a large-area superclean graphene surface is reported. The as-obtained superclean graphene, with surface cleanness exceeding 99%, can be transferred to dielectric substrates with significantly reduced polymer residues, yielding ultrahigh carrier mobility of 500 000 cm2 V-1 s-1 and low contact resistance of 118 Ω µm. The successful removal of contamination is enabled by the strong adhesive force of the activated-carbon-based lint roller on graphene contaminants.

How to cite this publication

Luzhao Sun, Li Lin, Zihao Wang, Dingran Rui, Zhiwei Yu, Jincan Zhang, Yanglizhi Li, Xiaoting Liu, Kaicheng Jia, Kexin Wang, Liming Zheng, Bing Deng, Tianbao Ma, Ning Kang, H. Q. Xu, Konstantin ‘kostya’ Novoselov, Hailin Peng, Zhongfan Liu (2019). A Force‐Engineered Lint Roller for Superclean Graphene. Advanced Materials, 31(43), DOI: 10.1002/adma.201902978.

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

2019

Authors

18

Datasets

0

Total Files

0

Language

English

Journal

Advanced Materials

DOI

10.1002/adma.201902978

Join Research Community

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

Get Free Access