Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 282

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

Novel and promising electrocatalyst for oxygen evolution reaction based on MnFeCoNi high entropy alloy

Dai, Weiji, Lu, Tao, Pan, Ye·2019·Journal of Power Sources

Abstract

Abstract Efficient oxygen evolution reaction catalysts based on earth-abundant and low-cost elements are urgently required for water splitting devices and metal-air batteries. Herein, for the first time we report a novel and promising MOx (M = Mn, Fe, Co and Ni) nanosheets catalyst for oxygen evolution reaction based on the MnFeCoNi high entropy alloy. By an electrochemical cyclic voltammetry scan activation, the MOx nanosheets can grow directly on the MnFeCoNi high entropy alloy particle surfaces forming a core-shell structure. The core-shell structure exhibits a low overpotential of 302 mV to achieve current density of 10 mA cm−2, a small Tafel slope of 83.7 mV dec−1 and exceptional long-term stability of electrolysis for over 20 h in 1 M KOH alkaline solution, which is comparable to the state-of-the-art oxygen evolution reaction electrocatalyst RuO2. We make an investigation of the MnFeCoNi high entropy alloy before and after cyclic voltammetry scan activation on their morphologies, chemical states and elements composition to understand the materials evolution. The present work not only provides a promising electrocatalyst but also broadens the application areas of high entropy alloys.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jpowsour.2019.05.030

Cites

60 of 60 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Show all 60 references

Cited by

See all 282

Metadata

Authors
Dai, W., Lu, T., & Pan, Y.
Venue
Journal of Power Sources
Publisher
Elsevier BV
Published
2019-08
Volume
430
Pages
104-111
ISSN
0378-7753 (ISSN-L)
OpenAlex
W2945222601
Cited by
282
References
60
FWCI
5.67
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Novel and promising electrocatalyst for oxygen evolution reaction based on MnFeCoNi high entropy alloy. https://app.cochat.ai/papers/10.1016/j.jpowsour.2019.05.030
The paper
Dai, W., Lu, T., & Pan, Y. (2019). Novel and promising electrocatalyst for oxygen evolution reaction based on MnFeCoNi high entropy alloy. Journal of Power Sources. https://doi.org/10.1016/j.jpowsour.2019.05.030

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.