Headspace Injection Method for Intermittent Sampling and Profiling Analyses of Volatile Organic Compounds Using Dielectric Barrier Discharge Ionization (DBDI).

IF 2.7 2区 化学 Q2 BIOCHEMICAL RESEARCH METHODS Journal of the American Society for Mass Spectrometry Pub Date : 2025-04-02 Epub Date: 2025-03-10 DOI:10.1021/jasms.4c00475
Daniel Heffernan, Frederik Oleinek, Ayla Schueler, Paak Wai Lau, Jürgen Kudermann, Alina Meindl, Mathias O Senge, Nicole Strittmatter
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Abstract

A direct headspace injection method is presented and optimized for the analysis of volatile organic compounds (VOCs) using dielectric barrier discharge ionization-mass spectrometry (DBDI-MS), incorporating an intermediate vial in which the sample headspace is injected. The setup is built of commonly available, cheap consumable parts and easily enables the incorporation of different gases for generating different ionization atmospheres. The method can be fully automated by using standard GC autosamplers, and its rapid analysis time is suitable for high-throughput applications. We show that this method is suitable for both profiling analysis of complex samples such as biofluids and quantitative measurements for real-time reaction monitoring. Our optimized method demonstrated improved reproducibility and sensitivity, with detection limits for compounds tested in the high nanomolar to the low micromolar range, depending on the compound. Key parameters for method optimization were identified such as sample vial volume, headspace-to-liquid ratio, incubation temperature, and equilibration time. These settings were systematically evaluated to maximize the signal intensity and improve repeatability between measurements. Two use cases are demonstrated: (i) quantitative measurement of ethanol production by a metal-organic framework from CO2 and (ii) profiling of biofluids following the consumption of asparagus.

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介质阻挡放电电离(DBDI)间歇取样和分析挥发性有机化合物的顶空注射方法。
提出并优化了一种直接顶空进样方法,用于介质阻挡放电电离-质谱(DBDI-MS)分析挥发性有机化合物(VOCs),该方法采用中间小瓶将样品顶空进样。该装置是由常见的,廉价的消耗品组成的,很容易使不同气体的结合产生不同的电离气氛。该方法可通过标准气相色谱自动进样器实现全自动,分析时间短,适用于高通量应用。我们表明,该方法适用于复杂样品(如生物流体)的分析和实时反应监测的定量测量。优化后的方法具有较高的重现性和灵敏度,检测限在高纳摩尔到低微摩尔范围内,具体取决于化合物。确定了优化方法的关键参数,如样品体积、顶液比、孵育温度和平衡时间。系统地评估这些设置,以最大限度地提高信号强度,并提高测量之间的可重复性。演示了两个用例:(i)通过金属有机框架从二氧化碳中定量测量乙醇产量;(ii)在食用芦笋后分析生物流体。
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来源期刊
CiteScore
5.50
自引率
9.40%
发文量
257
审稿时长
1 months
期刊介绍: The Journal of the American Society for Mass Spectrometry presents research papers covering all aspects of mass spectrometry, incorporating coverage of fields of scientific inquiry in which mass spectrometry can play a role. Comprehensive in scope, the journal publishes papers on both fundamentals and applications of mass spectrometry. Fundamental subjects include instrumentation principles, design, and demonstration, structures and chemical properties of gas-phase ions, studies of thermodynamic properties, ion spectroscopy, chemical kinetics, mechanisms of ionization, theories of ion fragmentation, cluster ions, and potential energy surfaces. In addition to full papers, the journal offers Communications, Application Notes, and Accounts and Perspectives
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