Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,045

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Reduced Mesoporous Co3O4 Nanowires as Efficient Water Oxidation Electrocatalysts and Supercapacitor Electrodes

Wang, Yongcheng, Zhou, Tong, Jiang, Kun, Da, Peimei, Peng, Zheng, Tang, Jing, Kong, Biao, Cai, Wen‐Bin, Yang, Zhongqin, Zheng, Gengfeng·2014·Advanced Energy Materials

Abstract

While electrochemical water splitting is one of the most promising methods to store light/electrical energy in chemical bonds, a key challenge remains in the realization of an efficient oxygen evolution reaction catalyst with large surface area, good electrical conductivity, high catalytic properties, and low fabrication cost. Here, a facile solution reduction method is demonstrated for mesoporous Co 3 O 4 nanowires treated with NaBH 4. The high‐surface‐area mesopore feature leads to efficient surface reduction in solution at room temperature, which allows for retention of the nanowire morphology and 1D charge transport behavior, while at the same time substantially increasing the oxygen vacancies on the nanowire surface. Compared to pristine Co 3 O 4 nanowires, the reduced Co 3 O 4 nanowires exhibit a much larger current of 13.1 mA cm‐2 at 1.65 V vs reversible hydrogen electrode (RHE) and a much lower onset potential of 1.52 V vs RHE. Electrochemical supercapacitors based on the reduced Co 3 O 4 nanowires also show a much improved capacitance of 978 F g‐1 and reduced charge transfer resistance. Density‐functional theory calculations reveal that the existence of oxygen vacancies leads to the formation of new gap states in which the electrons previously associated with the Co‐O bonds tend to be delocalized, resulting in the much higher electrical conductivity and electrocatalytic activity.

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 · 10.1002/aenm.201400696

Cites

2 of 2 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

Show all 2 references

Cited by

Metadata

Authors
Wang, Y., Zhou, T., Jiang, K., Da, P., Peng, Z., Tang, J., Kong, B., Cai, W., Yang, Z., & Zheng, G.
Venue
Advanced Energy Materials
Publisher
Wiley
Published
2014-07-14
Volume
4
Issue
16
ISSN
  • 1614-6832 (ISSN-L)
  • 1614-6840
OpenAlex
W2017279964
Cited by
1,045
References
2
FWCI
19.65
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

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.