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

Ansgar T. Kirk; Alexander Bohnhorst; Stefan Zimmermann

doi:10.1515/teme-2021-0013

Article

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.
, 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

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From the journal tm - Technisches Messen Volume 88 Issue 5

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.

Keywords: IMS; ion mobility spectrometer; trace gas detection; resolving power; limit of detection

Schlagwörter: IMS; Ionenmobilitätsspektrometer; Spurengasanalyse; Auflösungsvermögen; Nachweisgrenze

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.

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Received: 2021-02-10

Accepted: 2021-03-14

Published Online: 2021-03-20

Published in Print: 2021-05-26

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Articles in the same Issue

https://doi.org/10.1515/teme-2021-0013

Keywords for this article

IMS; ion mobility spectrometer; trace gas detection; resolving power; limit of detection