4.6 Article

Analysis of fluorinated compounds by micellar electrokinetic chromatography-mass spectrometry

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1645, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.chroma.2021.462123

关键词

Micellar electrokinetic; chromatography-mass spectrometry; Fluorinated compounds; Fluorous-flourous interaction; Herbicides

资金

  1. National Natural Science Foundation of China [82073808, 81872828, 81573384]

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Micellar electrokinetic chromatography (MEKC) is an efficient and selective separation technique with simple preparation process. By hyphenating MEKC with mass spectrometry (MS) using volatile ammonium perfluorooctanoate as a surfactant, this study successfully analyzed two herbicides in lake water samples.
Micellar electrokinetic chromatography (MEKC) is a good separation technique with high efficiency, high selectivity and simple preparation process. Hyphenation of MEKC with mass spectrometry (MS) could extend its application in complex sample analysis. However, direct coupling MEKC using commonly used surfactants like sodium dodecyl sulfate (SDS) with ESI-MS will lead to strong signal suppression. In this work, a MEKC-MS method using volatile ammonium perfluorooctanoate as surfactant was developed. The MS compatibility of ammonium perfluorooctanoate was investigated. The result revealed that there is no signal suppression even the concentration of ammonium perfluorooctanoate was up to 300 mM. Meanwhile, we found that ammonium perfluorooctanoate used as surfactant in MEKC provided powerful F-F interaction and hydrophobic interaction, which was beneficial for separation of fluorinated compounds. Using the ammonium perfluorooctanoate based MEKC method, several groups of fluorinated compounds, which cannot be separated using non-fluorinated surfactants like lauric acid and SDS based MEKC method, were baseline separated. Finally, the MEKC-ESI-MS method was successfully applied for analysis of two herbicides including fluometuron and fenuron in lake water samples with high separation efficiency, high sensitivity, good linearity and reproducibility. (c) 2021 Elsevier B.V. All rights reserved.

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