Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 240

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

High-Yield Exfoliation of Ultrathin Two-Dimensional Ternary Chalcogenide Nanosheets for Highly Sensitive and Selective Fluorescence DNA Sensors

Tan, Chaoliang, Yu, Peng, Hu, Yanling, Chen, Junze, Huang, Ying, Cai, Yongqing, Luo, Zhimin, Li, Bing, Lu, Qipeng, Wang, Lianhui, Liu, Zheng, Zhang, Hua·2015·Journal of the American Chemical Society

Abstract

High-yield preparation of ultrathin two-dimensional (2D) nanosheets is of great importance for the further exploration of their unique properties and promising applications. Herein, for the first time, the high-yield and scalable production of ultrathin 2D ternary chalcogenide nanosheets, including Ta2NiS5 and Ta2NiSe5, in solution is achieved by exfoliating their layered microflakes. The size of resulting Ta2NiS5 and Ta2NiS5 nanosheets ranges from tens of nanometers to few micrometers. Importantly, the production yield of single-layer Ta2NiS5 nanosheets is very high, ca. 86%. As a proof-of-concept application, the single-layer Ta2NiS5 is used as a novel fluorescence sensing platform for the detection of DNA with excellent selectivity and high sensitivity (with detection limit of 50 pM). These solution-processable, high-yield, large-amount ternary chalcogenide nanosheets may also have potential applications in electrocatalysis, supercapacitors, and electronic devices.

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/jacs.5b06982

Cites

6 of 6 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 240

Metadata

Authors
Tan, C., Yu, P., Hu, Y., Chen, J., Huang, Y., Cai, Y., Luo, Z., Li, B., Lu, Q., Wang, L., Liu, Z., & Zhang, H.
Venue
Journal of the American Chemical Society
Published
2015-08-10
Volume
137
Issue
32
Pages
10430-10436
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2351888710
Cited by
240
References
6
FWCI
12.79
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.