Nonlinearity in mass spectrometry for quantitative multi-component gas analysis in reaction processes
Quantitative mass spectrometry analysis for multi-component gas phase reaction processes is a typical multi-input and multi-output (MIMO) nonlinear problem. Conventional calibration and analytical methods that are based on the common hypothesis of linearity of the detected signal and gas parameters,...
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Veröffentlicht in: | Analytica chimica acta 2022-02, Vol.1194, p.339412-339412, Article 339412 |
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Hauptverfasser: | , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Quantitative mass spectrometry analysis for multi-component gas phase reaction processes is a typical multi-input and multi-output (MIMO) nonlinear problem. Conventional calibration and analytical methods that are based on the common hypothesis of linearity of the detected signal and gas parameters, could result in misjudgment of the reaction mechanism and inaccuracy in the determination of the reaction kinetics. In the present work, theoretical derivations based on equivalent characteristic spectrum analysis (ECSA®), discrete mode experiments and continuous mode experiments were performed, and the nonlinearity of mass spectrometry was confirmed. It is only possible to determine the physical parameters such as flow rate and/or concentrations of gases by properly handling the nonlinearity of mass spectrometry. In such case comprehensive reaction mechanisms and even the kinetics of the process can be accurately characterized. Well-handled nonlinear mass spectrometry analysis ensures a reliable and highly accurate identification for the multi-component gas phase reaction processes, and ensures high signal-to-noise ratio for detecting the small-flow gases at a wide range of carrier gas flow.
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•The MS nonlinearity between MI and MO signals is found and expounded firstly.•The MS nonlinearity is confirmed through theoretical derivation and experiments.•Taking the nonlinearity ensures the MS reliability, and high signal-to-noise ratio.•Using ECSA® it was possible to well interpret the nonlinearity. |
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ISSN: | 0003-2670 1873-4324 1873-4324 |
DOI: | 10.1016/j.aca.2021.339412 |