Hyper-fast gas chromatography and single-photon ionisation time-of-flight mass spectrometry with integrated electrical modulator-based sampling for headspace and online VOC analyses
| Autor: | Toni Miersch, Ralf Zimmermann, Kevin Schnepel, Christian Gehm, Hendryk Czech, Sven Ehlert |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Detection limit
Materials science 010504 meteorology & atmospheric sciences Orders of magnitude (temperature) 010401 analytical chemistry Analytical chemistry chemistry.chemical_element Mass spectrometry 01 natural sciences Biochemistry Toluene 0104 chemical sciences Analytical Chemistry chemistry.chemical_compound chemistry Ionization Electrochemistry Environmental Chemistry Gas chromatography Time-of-flight mass spectrometry Spectroscopy Helium 0105 earth and related environmental sciences |
| Zdroj: | Analyst 146, 3137-3149 (2021) |
| Popis: | We developed a novel fast gas chromatography (fastGC) instrument with integrated sampling of volatile organic compounds (VOCs) and detection by single-photon ionisation (SPI) time-of-flight mass spectrometry (TOFMS). A consumable-free electrical modulator rapidly cools down to -55 °C to trap VOCs and inject them on a short chromatographic column by prompt heating to 300 °C, followed by carrier gas exchange from air to helium. Due to the low thermal mass and optical heating, the fastGC is operated within total runtimes including cooling for 30 s and 15 s, referring to hyper-fast GC, and at a constantly increasing temperature ramp from 30 °C to 280 °C. The application of soft SPI-TOFMS allows the detection of co-eluting VOCs of different molecular compositions, which cannot be resolved by conventional GC (cGC) with electron ionisation (EI). Among other analytical figures of merit, we achieved limits of detection for toluene and p-xylene of 2 ppb and 0.5 ppb, respectively, at a signal-to-noise ratio of 3 and a linear response over a range of more than five orders of magnitude. Furthermore, we demonstrate the performance of the instrument on samples from the fields of environmental research and food science by headspace analysis of roasted coffee beans and needles from coniferous trees as well as by quasi-real-time analysis of biomass burning emissions and coffee roast gas. |
| Databáze: | OpenAIRE |
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