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Cited by 296

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Surface‐Enhanced Raman Spectroscopy for Trace Arsenic Detection in Contaminated Water

Mulvihill, Martin, Tao, Andrea, Benjauthrit, Kanokraj, Arnold, John, Yang, Peidong·2008·Angewandte Chemie International Edition

Abstract

Getting to the bottom of groundwater: The development of a reliable, portable, and simple-to-use device for detecting arsenic in groundwater is urgently needed in developing nations such as Bangladesh, where contaminated groundwater is at the root of a public health crisis. Toward this end, a highly sensitive platform utilizing surface-enhanced Raman spectroscopy (SERS, see picture) is used to quantitatively detect arsenate in water down to 1 ppb.

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Crossref · 10.1002/anie.200800776

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Metadata

Authors
Mulvihill, M., Tao, A., Benjauthrit, K., Arnold, J., & Yang, P.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2008-08-04
Volume
47
Issue
34
Pages
6456-6460
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2127340518
Cited by
296
References
2
FWCI
5.95
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Surface‐Enhanced Raman Spectroscopy for Trace Arsenic Detection in Contaminated Water. https://app.cochat.ai/papers/10.1002/anie.200800776
The paper
Mulvihill, M., Tao, A., Benjauthrit, K., Arnold, J., & Yang, P. (2008). Surface‐Enhanced Raman Spectroscopy for Trace Arsenic Detection in Contaminated Water. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.200800776

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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.