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

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

Language

Kurumsal Başvuru

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?

Contact

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.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Homologous Catalysts Based on Fe‐Doped CoP Nanoarrays for High‐Performance Full Water Splitting under Benign Conditions

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

Homologous Catalysts Based on Fe‐Doped CoP Nanoarrays for High‐Performance Full Water Splitting under Benign Conditions

0 Datasets

0 Files

en
2017
Vol 10 (16)
Vol. 10
DOI: 10.1002/cssc.201700693

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.
Abdullah Mohamed Asiri
Abdullah Mohamed Asiri

Institution not specified

Verified
Min Ma
Guilei Zhu
Fengyu Xie
+6 more

Abstract

The design and development of earth-abundant electrocatalysts for efficient full water splitting under mild conditions are highly desired, yet remain a challenging task. A homologous Fe-doped Co-based nanoarray incorporating complementary catalysts is shown to effect high-performance and durable water splitting in near-neutral media. Iron-doped cobalt phosphate borate nanoarray on carbon cloth (Fe-Co-Pi-Bi/CC) derived from iron-doped cobalt phosphide on CC (Fe-CoP/CC) through oxidative polarization behaves as a highly active bimetallic electrocatalyst for water oxidation with an overpotential of 382 mV to afford a catalytic current density of 10 mA cm-2 in 0.1 m potassium borate (K-Bi, pH 9.2). Fe-CoP/CC is also highly active for the hydrogen evolution reaction, capable of driving 10 mA cm-2 at an overpotential of only 175 mV in 0.1 m K-Bi. A two-electrode water electrolyzer incorporating Fe-Co-Pi-Bi/CC as anode and Fe-CoP/CC as cathode achieves 10 mA cm-2 water-splitting current at a cell voltage of 1.95 V with strong long-term electrochemical durability.

How to cite this publication

Min Ma, Guilei Zhu, Fengyu Xie, Fengli Qu, Zhiang Liu, Gu Du, Abdullah Mohamed Asiri, Yadong Yao, Xuping Sun (2017). Homologous Catalysts Based on Fe‐Doped CoP Nanoarrays for High‐Performance Full Water Splitting under Benign Conditions. , 10(16), DOI: https://doi.org/10.1002/cssc.201700693.

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

9

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/cssc.201700693

Join Research Community

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

Get Free Access