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Cited by 704

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Ultrasensitive surface-enhanced Raman scattering detection in common fluids

Open access
Yang, Shikuan, Dai, Xianming, Stogin, Birgitt Boschitsch, Wong, Tak-Sing·2016·Proceedings of the National Academy of Sciences

Abstract

Significance: Many analytes in real-life samples, such as body fluids, soil contaminants, and explosives, are dispersed in liquid, solid, or air phases. However, it remains a challenge to create a platform to detect these analytes in all of these phases with high sensitivity and specificity. Here, we demonstrate a universal platform termed slippery liquid-infused porous surface-enhanced Raman scattering (SLIPSERS) that enables the enrichment and delivery of analytes originating from various phases into surface-enhanced Raman scattering (SERS)-sensitive sites and their subsequent detection down to the subfemtomolar level (<10 −15 mol⋅L −1 ). Based on SLIPSERS, we have demonstrated detection of various chemicals, biological molecules, and environmental contaminants with high sensitivity and specificity. Our platform may lead to ultrasensitive molecular detection for applications related to analytical chemistry, diagnostics, environmental monitoring, and national security.

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Metadata

Authors
Yang, S., Dai, X., Stogin, B. B., & Wong, T.-S.
Venue
Proceedings of the National Academy of Sciences
Published
2015-12-30
Volume
113
Issue
2
Pages
268-273
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2207307278
Cited by
704
References
1
FWCI
20.18
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Ultrasensitive surface-enhanced Raman scattering detection in common fluids. https://app.cochat.ai/papers/10.1073/pnas.1518980113
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Yang, S., Dai, X., Stogin, B. B., & Wong, T.-S. (2016). Ultrasensitive surface-enhanced Raman scattering detection in common fluids. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1518980113

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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