Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 226

The DOI matches its Crossref record.

Visualization and quantification of transition metal atomic mixing in Mo1−xWxS2 single layers

Open access
Dumcenco, Dumitru O, Kobayashi, Haruka, Liu, Zheng, Huang, Ying-Sheng, Suenaga, Kazu·2013·Nature Communications

Abstract

The alloying behaviour of materials is a well-known problem in all kinds of compounds. Revealing the heteroatomic distributions in two-dimensional crystals is particularly critical for their practical use as nano-devices. Here we obtain statistics of the homo- and heteroatomic coordinates in single-layered Mo1−xWxS2 from the atomically resolved scanning transmission electron microscope images and successfully quantify the degree of alloying for the transition metal elements (Mo or W). The results reveal the random alloying of this mixed dichalcogenide system throughout the chemical compositions (x=0 to 1). Such a direct route to gain an insight into the alloying degree on individual atom basis will find broad applications in characterizing low-dimensional heterocompounds and become an important complement to the existing theoretical methods. Understanding the influence of disorder on the properties of two-dimensional materials is of increasing importance, given the interest in these compounds for electronic applications. Using a scanning transmission electron microscope, Dumcencoet al. quantify the atomic mixing in two-dimensional films of Mo1–xWxS2.

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 · 10.1038/ncomms2351

Cites

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

Cited by

See all 226

Metadata

Authors
Dumcenco, D. O., Kobayashi, H., Liu, Z., Huang, Y.-S., & Suenaga, K.
Venue
Nature Communications
Published
2013-01-15
Volume
4
Issue
1
Pages
1351-1351
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2045239794
Cited by
226
References
0
FWCI
10.36
Type
journal article
Language
en
Open access
hybrid

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: Visualization and quantification of transition metal atomic mixing in Mo1−xWxS2 single layers. https://app.cochat.ai/papers/10.1038/ncomms2351
The paper
Dumcenco, D. O., Kobayashi, H., Liu, Z., Huang, Y.-S., & Suenaga, K. (2013). Visualization and quantification of transition metal atomic mixing in Mo1−xWxS2 single layers. Nature Communications. https://doi.org/10.1038/ncomms2351

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.