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
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Rolling Friction Enhanced Free‐Standing Triboelectric Nanogenerators and their Applications in Self‐Powered Electrochemical Recovery Systems

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2015

Rolling Friction Enhanced Free‐Standing Triboelectric Nanogenerators and their Applications in Self‐Powered Electrochemical Recovery Systems

0 Datasets

0 Files

en
2015
Vol 26 (7)
Vol. 26
DOI: 10.1002/adfm.201504396

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.
Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

Verified
Min‐Hsin Yeh
Hengyu Guo
Long Lin
+4 more

Abstract

Heavy metals contained in wastewater are one of the most serious pollutions in natural resources. A self‐powered electrochemical recovery system for collecting Cu ions in wastewater by incorporating a rolling friction enhanced freestanding triboelectric nanogenerator (RF‐TENG) is developed here. The RF‐TENG utilizes integrated cylindrical surfaces using the conjunction of rolling electrification and freestanding electrostatic induction, which shows outstanding output performance and ultrarobust stability. By using the kinetic energy of flowing water, a collection efficiency of up to 80% for Cu 2+ ions in wastewater has been achieved. Self‐powered electrochemical systems are one of the most promising applications of TENGs for independent and sustainable driving of electrochemical reactions without the need for any additional power supply. This research is a substantial advancement towards the practical applications of triboelectric nanogenerators and self‐powered electrochemical systems.

How to cite this publication

Min‐Hsin Yeh, Hengyu Guo, Long Lin, Zhen Wen, Zhaoling Li, Chenguo Hu, Zhong Lin Wang (2015). Rolling Friction Enhanced Free‐Standing Triboelectric Nanogenerators and their Applications in Self‐Powered Electrochemical Recovery Systems. , 26(7), DOI: https://doi.org/10.1002/adfm.201504396.

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

2015

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/adfm.201504396

Join Research Community

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

Get Free Access