自动起泡萃取机理研究

Chun-Ming Chang, Hao-Chun Yang, P. L. Urban
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引用次数: 6

摘要

气泡萃取(FE)通过促进挥发性溶质从液体到气相的转移来促进挥发性溶质的分析。载气在中压(Δp≈150 kPa)下溶解在样品中,随后突然减压,导致泡沫化。由于压力差很小,释放的气态分析物被导向在线检测器。FE在化学分析中是有利的,因为挥发性物质在短时间间隔内释放,允许脉冲注射,并导致高信噪比。为了阐明FE的作用机理,我们研究了各种可能影响萃取效率的因素,包括:仪器相关因素、方法相关因素、样品相关因素和分析物相关因素。特别是,我们已经评估了挥发性溶质的性质,使它们适合FE。结果表明,有机溶质可能扩散到气泡腔中,特别是在有盐存在的情况下。FE与质谱耦合的高信号强度部分是由于高样品引入率(在减压后)到质量敏感检测器。然而,具有不同性质(分子量,极性)的分析物显示出不同的时间分布,表明气泡暴露于样品基质的影响。需要足够的萃取时间(~ 12s)来萃取挥发性较低的溶质。本报告的结果可以帮助分析人员在分析实际样品时预测基质效应的发生。它们也为提高低丰度分析物的提取效率提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the mechanism of automated fizzy extraction
Fizzy extraction (FE) facilitates analysis of volatile solutes by promoting their transfer from the liquid to the gas phase. A carrier gas is dissolved in the sample under moderate pressure (Δp ≈ 150 kPa), followed by an abrupt decompression, what leads to effervescence. The released gaseous analytes are directed to an on-line detector due to a small pressure difference. FE is advantageous in chemical analysis because the volatile species are released in a short time interval, allowing for pulsed injection, and leading to high signal-to-noise ratios. To shed light on the mechanism of FE, we have investigated various factors that could potentially contribute to the extraction efficiency, including: instrument-related factors, method-related factors, sample-related factors, and analyte-related factors. In particular, we have evaluated the properties of volatile solutes, which make them amenable to FE. The results suggest that the organic solutes may diffuse to the bubble lumen, especially in the presence of salt. The high signal intensities in FE coupled with mass spectrometry are partly due to the high sample introduction rate (upon decompression) to a mass-sensitive detector. However, the analytes with different properties (molecular weight, polarity) reveal distinct temporal profiles, pointing to the effect of bubble exposure to the sample matrix. A sufficient extraction time (~12 s) is required to extract less volatile solutes. The results presented in this report can help analysts to predict the occurrence of matrix effects when analyzing real samples. They also provide a basis for increasing extraction efficiency to detect low-abundance analytes.
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