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. Reducing the Self-Discharge Rate of Supercapacitors by Suppressing Electron Transfer in the Electric Double Layer

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2021

Reducing the Self-Discharge Rate of Supercapacitors by Suppressing Electron Transfer in the Electric Double Layer

0 Datasets

0 Files

en
2021
Vol 168 (12)
Vol. 168
DOI: 10.1149/1945-7111/ac44b9

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
Mingwei Shi
Zailei Zhang
Man Zhao
+2 more

Abstract

For supercapacitors, high self-discharge rate is an inevitable issue that causes fast decay of cell voltage and loss of stored energy. Designing supercapacitors with suppressed self-discharge for long-term energy storage has been a challenge. In this work, we demonstrate that substantially reduced self-discharge rate can be achieved by using highly concentrated electrolytes. Specifically, when supercapacitors with 14 M LiCl electrolyte are charged to 0.80 V, the open circuit voltage (OCV) drops to 0.65 V in 24 h. In stark contrast, when the electrolyte concentration is reduced to 1 M, the OCV drops from 0.80 to 0.65 V within only 0.3 h, which was 80 times faster than that with 14 M LiCl. Decreased OCV decay rate at high electrolyte concentration is also confirmed for supercapacitors with different electrolytes (e.g., LiNO 3 ) or at higher charging voltages (1.60 V). The slow self-discharge in highly concentrated electrolyte can be largely attributed to impeded electron transfer between the electrodes and electrolyte due to the formation of hydration clusters and reduced amount of free water molecules, thereby faradaic reactions that cause fast self-discharge are reduced. Our study not only supports the newly revised model about the formation of electric double layer with the inclusion of electron transfer, but also points a direction for substantially reducing the self-discharge rate of supercapacitors.

How to cite this publication

Mingwei Shi, Zailei Zhang, Man Zhao, Xianmao Lu, Zhong Lin Wang (2021). Reducing the Self-Discharge Rate of Supercapacitors by Suppressing Electron Transfer in the Electric Double Layer. , 168(12), DOI: https://doi.org/10.1149/1945-7111/ac44b9.

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

2021

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1149/1945-7111/ac44b9

Join Research Community

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

Get Free Access