Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 286

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

Inkjet-printed paper-based SERS dipsticks and swabs for trace chemical detection

Yu, Wei W., White, Ian M.·2013·The Analyst

Abstract

We demonstrate a paper-based surface swab and lateral-flow dipstick that includes an inkjet-printed surface-enhanced Raman spectroscopy (SERS) substrate for analyte detection. Due to capillary-action wicking of cellulose, the paper dipstick enables extremely simple and pump-free loading of liquid samples into the detection device, and in addition provides inherent analyte concentration within the detection volume. Furthermore, the flexible nature of the paper-based SERS device also enables it to act as a swab to collect analyte molecules directly from a large-area surface; the collected analyte molecules can then be focused into a small-volume SERS-active region by lateral-flow concentration. These capabilities are unseen in today's SERS substrates and microfluidic SERS devices. Using these novel lateral-flow paper SERS devices, we achieved detection limits as low as 95 fg of Rhodamine 6G (R6G), 413 pg of the organophosphate malathion, 9 ng of heroin, and 15 ng of cocaine. Moreover, the measurements show that the technique is quantitative and is repeatable across multiple swabs and dipsticks. The results reported here may lead to ultra-low-cost portable applications in trace chemical detection.

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 · 10.1039/c2an36116g

Cites

36 of 36 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 36 references

Cited by

See all 286

Metadata

Authors
Yu, W. W., & White, I. M.
Venue
The Analyst
Published
2013
Volume
138
Issue
4
Pages
1020-1025
ISSN
  • 0003-2654 (ISSN-L)
  • 1364-5528
OpenAlex
W2141501403
Cited by
286
References
36
FWCI
11.86
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: Inkjet-printed paper-based SERS dipsticks and swabs for trace chemical detection. https://app.cochat.ai/papers/10.1039/c2an36116g
The paper
Yu, W. W., & White, I. M. (2013). Inkjet-printed paper-based SERS dipsticks and swabs for trace chemical detection. The Analyst. https://doi.org/10.1039/c2an36116g

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.