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Review of applications of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and differential mobility spectrometry (DMS)

Kolakowski, Beata M., Mester, Zoltán·2007·The Analyst

Abstract

High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) and Differential Mobility Spectrometry (DMS) harness differences in ion mobility in low and high electric fields to achieve a gas-phase separation of ions at atmospheric pressure. This separation is orthogonal to either chromatographic or mass spectrometric separation, thereby increasing the selectivity and specificity of analysis. The orthogonality of separation, which in some cases may obviate chromatographic separation, can be used to differentiate isomers, to reduce background, to resolve isobaric species, and to improve signal-to-noise ratios by selective ion transmission. This review will focus on the applications of these techniques to the separation of various classes of analytes, including chemical weapons, explosives, biologically active molecules, pharmaceuticals and pollutants. These papers cover the period up to January 2007.

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Metadata

Authors
Kolakowski, B. M., & Mester, Z.
Venue
The Analyst
Published
2007
Volume
132
Issue
9
Pages
842
ISSN
  • 0003-2654 (ISSN-L)
  • 1364-5528
OpenAlex
W2163546899
Cited by
351
References
0
FWCI
6.39
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Review of applications of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and differential mobility spectrometry (DMS). https://app.cochat.ai/papers/10.1039/b706039d
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Kolakowski, B. M., & Mester, Z. (2007). Review of applications of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and differential mobility spectrometry (DMS). The Analyst. https://doi.org/10.1039/b706039d

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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.