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Analytical model for the signal-to-noise-ratio of drift tube ion mobility spectrometers

  • Ansgar T. Kirk

    Ansgar T. Kirk received his M. Sc. in mechatronics in 2013 and his Dr.-Ing. in electrical engineering in 2020 from the Leibniz Universität Hannover. During 2012 and 2013, he also investigated low-uncertainty measurements in reverberation chambers as a guest researcher in the Electromagnetics Division of the National Institute of Standards and Technology (NIST) in Boulder, Colorado, USA. Since 2013, he is employed as a research engineer at the Institute of Electrical Engineering and Measurement Technology of the Leibniz Universität Hannover. His current research interests center on all aspects of ion mobility spectrometry and ionization-based sensors, ranging from analytical modelling and simulations over design, construction and characterization of mechanical and electrical components to analysis and processing of the acquired data.

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    , Alexander Bohnhorst

    Alexander Bohnhorst received his M. Sc. in nanotechnology in 2014 from the Leibniz Universität Hannover, working on rapid prototyping of nanoscale structures. Since 2014, he is employed as a research engineer at the Institute of Electrical Engineering and Measurement Technology of the Leibniz Universität Hannover, working towards his Dr.-Ing. degree in electrical engineering. His current research focuses on novel types of ion mobility spectrometers and the required data processing.

    and Stefan Zimmermann

    Stefan Zimmermann received his diploma in electrical engineering in 1996 and his Dr.-Ing. in 2001 from the Technical University Hamburg-Harburg, Germany. His research focused on MEMS sensor design and fabrication. In 2001, he joined the Berkeley Sensor and Actuator Center, University of California, Berkeley, USA, as a Postdoctoral Scientist with support of a Feodor-Lynen Fellowship of the Alexander von Humboldt Foundation. His research focused on BioMEMS and in particular the development of a disposable continuous glucose monitor. In 2004, he joined the Research Unit of Dräger, Luebeck, Germany, where he worked on MEMS for medical and safety applications. His latest position at Dräger was Head of Chemical and Biochemical Sensors. In 2009, he joined the Leibniz University Hannover, Germany, as a Full Professor for Sensors and Measurement technology and became Head of Department of Sensors and Measurement Technology. Since 2019, he is Director of Institute of Electrical Engineering and Measurement Technology. From 2017 to 2019, he was Vice Dean, and since 2019, he is Dean of Faculty of Electrical Engineering and Computer Science. His current research is focused on the development of sensors and nanosensors for ultrasensitive and selective trace compound detection.

Published/Copyright: March 20, 2021

Abstract

While the resolving power of drift tube ion mobility spectrometers has been studied and modelled in detail over the past decades, no comparable model exists for the signal-to-noise-ratio. In this work, we develop an analytical model for the signal-to-noise-ratio of a drift tube ion mobility spectrometer based on the same experimental parameters used for modelling the resolving power. The resulting holistic model agrees well with experimental results and allows simultaneously optimizing both resolving power and signal-to-noise-ratio. Especially, it reveals several unexpected relationships between experimental parameters. First, even though reduced initial ion packet widths result in fewer injected ions and reduced amplifier widths result in more noise, the resulting shift of the optimum operating point when reducing both simultaneously leads to a constant signal-to-noise-ratio. Second, there is no dependence of the signal-to-noise-ratio at the optimum operating point on the drift length, as again the resulting shift of the optimum operating point causes all effects to compensate each other.

Zusammenfassung

Während das Auflösungsvermögen von Driftzeit-Ionenmobilitätsspektrometern in den vergangenen Jahrzehnten detailliert untersucht und modelliert wurde, existiert kein vergleichbares Modell für das Signal-Rausch-Verhältnis. Im Rahmen dieser Arbeit wird ein analytisches Modell für das Signal-Rausch-Verhältnis von Driftzeit-Ionenmobilitätsspektrometern hergeleitet, das auf denselben experimentellen Parametern basiert, die auch bei der Modellierung des Auflösungsvermögens zum Einsatz kommen. Das resultierende ganzheitliche Modell stimmt mit experimentellen Resultaten gut überein und erlaubt die gleichzeitige Optimierung von Auflösungsvermögen und Signal-Rausch-Verhältnis. Insbesondere enthüllt es mehrere unerwartete Zusammenhänge zwischen den experimentellen Parametern. Erstens resultieren reduzierte Anfangsbreiten des Ionenpakets zwar in weniger injizierten Ionen und reduzierte Verstärkerbreiten in mehr Rauschen, solange jedoch beide gleich reduziert werden, führt die resultierende Verschiebung des optimalen Arbeitspunkts dennoch zu einem konstanten Signal-Rausch-Verhältnis. Zweitens existiert keinerlei Abhängigkeit des Signal-Rausch-Verhältnisses im optimalen Arbeitspunkt von der Driftlänge, da auch hier die resultierende Verschiebung des optimalen Arbeitspunkts zu einer gegenseitigen Kompensation der einzelnen Effekte führt.

About the authors

Ansgar T. Kirk

Ansgar T. Kirk received his M. Sc. in mechatronics in 2013 and his Dr.-Ing. in electrical engineering in 2020 from the Leibniz Universität Hannover. During 2012 and 2013, he also investigated low-uncertainty measurements in reverberation chambers as a guest researcher in the Electromagnetics Division of the National Institute of Standards and Technology (NIST) in Boulder, Colorado, USA. Since 2013, he is employed as a research engineer at the Institute of Electrical Engineering and Measurement Technology of the Leibniz Universität Hannover. His current research interests center on all aspects of ion mobility spectrometry and ionization-based sensors, ranging from analytical modelling and simulations over design, construction and characterization of mechanical and electrical components to analysis and processing of the acquired data.

Alexander Bohnhorst

Alexander Bohnhorst received his M. Sc. in nanotechnology in 2014 from the Leibniz Universität Hannover, working on rapid prototyping of nanoscale structures. Since 2014, he is employed as a research engineer at the Institute of Electrical Engineering and Measurement Technology of the Leibniz Universität Hannover, working towards his Dr.-Ing. degree in electrical engineering. His current research focuses on novel types of ion mobility spectrometers and the required data processing.

Stefan Zimmermann

Stefan Zimmermann received his diploma in electrical engineering in 1996 and his Dr.-Ing. in 2001 from the Technical University Hamburg-Harburg, Germany. His research focused on MEMS sensor design and fabrication. In 2001, he joined the Berkeley Sensor and Actuator Center, University of California, Berkeley, USA, as a Postdoctoral Scientist with support of a Feodor-Lynen Fellowship of the Alexander von Humboldt Foundation. His research focused on BioMEMS and in particular the development of a disposable continuous glucose monitor. In 2004, he joined the Research Unit of Dräger, Luebeck, Germany, where he worked on MEMS for medical and safety applications. His latest position at Dräger was Head of Chemical and Biochemical Sensors. In 2009, he joined the Leibniz University Hannover, Germany, as a Full Professor for Sensors and Measurement technology and became Head of Department of Sensors and Measurement Technology. Since 2019, he is Director of Institute of Electrical Engineering and Measurement Technology. From 2017 to 2019, he was Vice Dean, and since 2019, he is Dean of Faculty of Electrical Engineering and Computer Science. His current research is focused on the development of sensors and nanosensors for ultrasensitive and selective trace compound detection.

References

1. G. A. Eiceman, Z. Karpas, H. H. Hill. Ion Mobility Spectrometry. CRC Press, 2013. ISBN: 1439859973.10.1201/b16109Search in Google Scholar

2. A. E. Eiceman. Toward the chemical agent monitor: technologies and developments in England and the United States from 1965 to 1982. Int. J. Ion Mobil. Spec., 2020. DOI: 10.1007/s12127-019-00256-w.Search in Google Scholar

3. H. Borsdorf, G. A. Eiceman. Ion mobility spectrometry: principles and applications. Applied Spectroscopy Reviews, 41(4):323–375, 2006. DOI: 10.1080/05704920600663469.Search in Google Scholar

4. A. T. Kirk. Driftzeit-Ionenmobilitätsspektrometer mit hoher analytischer Leistungsfähigkeit - Modellierung, Entwurf und Umsetzung. Shaker, 2020. ISBN: 9783844074420.Search in Google Scholar

5. A. T. Kirk, S. Zimmermann. Bradbury-Nielsen vs. Field switching shutters for high resolution drift tube ion mobility spectrometers. Int. J. Ion Mobil. Spec., 17(3-4):131–137, 2014. DOI: 10.1007/s12127-014-0153-9.Search in Google Scholar

6. A. T. Kirk, D. Grube, T. Kobelt, C. Wendt, S. Zimmermann. A high resolution high kinetic energy ion mobility spectrometer based on a low-discrimination tristate ion shutter. Anal. Chem., 90(9):5603–5611, 2018. DOI: 10.1021/acs.analchem.7b04586.Search in Google Scholar PubMed

7. S. Rokushika, H. Hatano, M. A. Baim, H. H. Hill. Resolution measurement for ion mobility spectrometry. Anal. Chem., 57(9):1902–1907, 1985. DOI: 10.1021/ac00286a023.Search in Google Scholar

8. W. F. Siems, C. Wu, E. E. Tarver, Hill, Herbert H. Jr., P. R. Larsen, D. G. McMinn. Measuring the resolving power of ion mobility spectrometers. Anal. Chem., 66(23):4195–4201, 1994. DOI: 10.1021/ac00095a014.Search in Google Scholar

9. A. B. Kanu, M. M. Gribb, H. H. Hill. Predicting optimal resolving power for ambient pressure ion mobility spectrometry. Anal. Chem., 80(17):6610–6619, 2008. DOI: 10.1021/ac8008143.Search in Google Scholar PubMed PubMed Central

10. A. T. Kirk, M. Allers, P. Cochems, J. Langejürgen, S. Zimmermann. A compact high resolution ion mobility spectrometer for fast trace gas analysis. Analyst, 138(18):5200–5207, 2013. DOI: 10.1039/c3an00231d.Search in Google Scholar PubMed

11. M. Grabarics, M. Lettow, A. T. Kirk, G. von Helden, T. J. Causon, K. Pagel. Plate-height model of ion mobility-mass spectrometry. Analyst, 2020. DOI: 10.1039/d0an00433b.Search in Google Scholar PubMed

12. G. E. Spangler, C. I. Collins. Peak shape analysis and plate theory for plasma chromatography. Anal. Chem., 47(3):403–407, 1975. DOI: 10.1021/ac60353a013.Search in Google Scholar

13. P. Watts, A. Wilders. On the resolution obtainable in practical ion mobility systems. Int. J. Mass Spectrom. Ion Process., 112(2-3):179–190, 1992. DOI: 10.1016/0168-1176(92)80003-J.Search in Google Scholar

14. G. E. Spangler. Expanded theory for the resolving power of a linear ion mobility spectrometer. Int. J. Mass Spectrom., 220(3):399–418, 2002. DOI: 10.1016/S1387-3806(02)00841-2.Search in Google Scholar

15. H. Lai, T. R. McJunkin, C. J. Miller, J. R. Scott, J. R. Almirall. The predictive power of SIMION/SDS simulation software for modeling ion mobility spectrometry instruments. Int. J. Mass Spectrom., 276(1):1–8, 2008. DOI: 10.1016/j.ijms.2008.06.011.Search in Google Scholar

16. J. Langejürgen, P. Cochems, S. Zimmermann. Results of a transient simulation of a drift tube ion mobility spectrometer considering charge repulsion, ion loss at metallic surfaces and ion generation. Int. J. Ion Mobil. Spec., 15(4):247–255, 2012. DOI: 10.1007/s12127-012-0095-z.Search in Google Scholar

17. G. E. Spangler, K. N. Vora, J. P. Carrico. Miniature ion mobility spectrometer cell. J. Phys. E: Sci. Instrum., 19(3):191–198, 1986. DOI: 10.1088/0022-3735/19/3/005.Search in Google Scholar

18. G. A. Eiceman, E. G. Nazarov, J. E. Rodriguez, J. A. Stone. Analysis of a drift tube at ambient pressure. Rev. Sci. Instrum., 72(9):3610–3621, 2001. DOI: 10.1063/1.1392339.Search in Google Scholar

19. E. A. Mason, E. W. McDaniel. Transport Properties of Ions in Gases. Wiley-VCH Verlag GmbH & Co. KGaA, 1988. ISBN: 9783527602858.10.1002/3527602852Search in Google Scholar

20. H. E. Revercomb, E. A. Mason. Theory of plasma chromatography/gaseous electrophoresis. Review. Anal. Chem., 47(7):970–983, 1975. DOI: 10.1021/ac60357a043.Search in Google Scholar

21. A. T. Kirk, S. Zimmermann. Pushing a compact 15 cm long ultra-high resolution drift tube ion mobility spectrometer with R=250 to R=425 using peak deconvolution. Int. J. Ion Mobil. Spec., 18(1-2):17–22, 2015. DOI: 10.1007/s12127-015-0166-z.Search in Google Scholar

22. A. T. Kirk, K. Bakes, S. Zimmermann. A universal relationship between optimum drift voltage and resolving power. Int. J. Ion Mobil. Spec., 20(3-4):105–109, 2017. DOI: 10.1007/s12127-017-0219-6.Search in Google Scholar

23. A. T. Kirk, S. Zimmermann. An analytical model for the optimum drift voltage of drift tube ion mobility spectrometers with respect to resolving power and detection limits. Int. J. Ion Mobil. Spec., 18(3-4):129–135, 2015. DOI: 10.1007/s12127-015-0176-x.Search in Google Scholar

24. A. T. Kirk, M. J. Küddelsmann, A. Bohnhorst, M. Lippmann, S. Zimmermann. Improving ion mobility spectrometer sensitivity through the extended field switching ion shutter. Anal. Chem., 92(7):4838–4847, 2020. DOI: 10.1021/acs.analchem.9b04259.Search in Google Scholar PubMed

25. A. T. Kirk, T. Kobelt, H. Spehlbrink, S. Zimmermann. A simple analytical model for predicting the detectable ion current in ion mobility spectrometry using corona discharge ionization sources. J. Am. Soc. Mass Spectrom., 2018. DOI: 10.1007/s13361-018-1970-6.Search in Google Scholar PubMed

26. M. Tabrizchi, T. Khayamian, N. Taj. Design and optimization of a corona discharge ionization source for ion mobility spectrometry. Rev. Sci. Instrum., 71(6):2321–2328, 2000. DOI: 10.1063/1.1150618.Search in Google Scholar

27. J. B. Johnson. Thermal agitation of electricity in conductors. Phys. Rev., 32(1):97–109, 1928. DOI: 10.1103/PhysRev.32.97.Search in Google Scholar

28. H. Nyquist. Thermal agitation of electric charge in conductors. Phys. Rev., 32(1):110–113, 1928. DOI: 10.1103/PhysRev.32.110.Search in Google Scholar

29. Burr-Brown. Noise Analysis of FET Transimpedance Amplifiers. Burr-Brown Application Bulletin, 1994.Search in Google Scholar

30. P. Horowitz, W. Hill. The Art of Electronics. Cambridge University Press, 2017. ISBN: 9780521809269.Search in Google Scholar

31. P. Cochems, A. T. Kirk, S. Zimmermann. In-circuit-measurement of parasitic elements in high gain high bandwidth low noise transimpedance amplifiers. Rev. Sci. Instrum., 85(12):124703, 2014. DOI: 10.1063/1.4902854.Search in Google Scholar PubMed

32. T. Reinecke, C. N. Naylor, B. H. Clowers. Ion multiplexing: Maximizing throughput and signal to noise ratio for ion mobility spectrometry. TrAC, Trends Anal. Chem., 2019. DOI: 10.1016/j.trac.2019.03.014.Search in Google Scholar

33. A. Bohnhorst, A. T. Kirk, S. Zimmermann. Simulation aided design of a low cost ion mobility spectrometer based on printed circuit boards. Int. J. Ion Mobil. Spec., 19(2):167–174, 2016. DOI: 10.1007/s12127-016-0202-7.Search in Google Scholar

34. A. Ahrens, M. Hitzemann, S. Zimmermann. Miniaturized high-performance drift tube ion mobility spectrometer. Int. J. Ion Mobil. Spec., 22(2):77–83, 2019. DOI: 10.1007/s12127-019-00248-w.Search in Google Scholar

Received: 2021-02-10
Accepted: 2021-03-14
Published Online: 2021-03-20
Published in Print: 2021-05-26

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