Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 265

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

Quantitative Correlation between Defect Density and Heterogeneous Electron Transfer Rate of Single Layer Graphene

Zhong, Jin-Hui, Zhang, Jie, Jin, Xi, Liu, Jun-Yang, Li, Qiongyu, Li, Mao-Hua, Cai, Weiwei, Wu, De-Yin, Zhan, Dongping, Ren, Bin·2014·Journal of the American Chemical Society
DOI 10.1021/ja508965w
Open this paper in CoChat — free account

Abstract

Improving electrochemical activity of graphene is crucial for its various applications, which requires delicate control over its geometric and electronic structures. We demonstrate that precise control of the density of vacancy defects, introduced by Ar(+) irradiation, can improve and finely tune the heterogeneous electron transfer (HET) rate of graphene. For reliable comparisons, we made patterns with different defect densities on a same single layer graphene sheet, which allows us to correlate defect density (via Raman spectroscopy) with HET rate (via scanning electrochemical microscopy) of graphene quantitatively, under exactly the same experimental conditions. By balancing the defect induced increase of density of states (DOS) and decrease of conductivity, the optimal HET rate is attained at a moderate defect density, which is in a critical state; that is, the whole graphene sheet becomes electronically activated and, meanwhile, maintains structural integrity. The improved electrochemical activity can be understood by a high DOS near the Fermi level of defective graphene, as revealed by ab initio simulation, which enlarges the overlap between the electronic states of graphene and the redox couple. The results are valuable to promote the performance of graphene-based electrochemical devices. Furthermore, our findings may serve as a guide to tailor the structure and properties of graphene and other ultrathin two-dimensional materials through defect density engineering.

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 · 10.1021/ja508965w

Cites

52 of 52 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

Cited by

See all 265

Metadata

Authors
Zhong, J.-H., Zhang, J., Jin, X., Liu, J.-Y., Li, Q., Li, M.-H., Cai, W., Wu, D.-Y., Zhan, D., & Ren, B.
Venue
Journal of the American Chemical Society
Publisher
American Chemical Society (ACS)
Published
2014-11-12
Volume
136
Issue
47
Pages
16609-16617
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
DOI
10.1021/ja508965w
OpenAlex
W2313459513
Cited by
265
References
52
FWCI
9.08
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.