Abstract
In the last decade or two, it seems that the trend of technological advance in NMR spectroscopy cannot follow the trend of desire to measure NMR samples with gradually lower response signals. Recently, an accurate noise model, based on the concept of noise figure, of the most sensitive part of the NMR spectroscopy system from the aspect of noise, which is its probe-to-spectrometer receiving chain, was introduced. The main purpose of this model is to optimize the used NMR spectroscopy system and, ultimately, enable measuring NMR samples with even lower response signals than the ones measured today. All the parameters of the NMR spectroscopy system, used in the introduced model, can be easily measured using vector network analyzers and noise figure meters, or can be found in the datasheets of the respective elements, except the spectrometer’s receiving chain noise figure. In this contribution, the process of spectrometer’s receiving chain noise figure measurement, performed using the Twice Power Method, is described. A block diagram representation of the spectrometer’s receiving chain is presented here, as well as its approximative model. The respective noise figure measurement results, which are also presented, explain the general tendency of using the mid-range of the spectrometer’s gain control level when performing the actual NMR measurements.
Zusammenfassung
In den letzten ein bis zwei Jahrzehnten sieht es so aus, als ob die Entwicklung des technologischen Fortschrittes in der NMR-Spektroskopie dem Wunsch, Stichproben mit stufenweise niedrigerem Antwortsignal zu messen, nicht folgen kann. Letztens wurde ein genaues Rauschmodell, auf dem Konzept der Rauschzahl basierend, als eines der meist empfindlichen Teile der NMR-Spektroskopiesystem von der Ansicht des Rausches, was seine Spektrometersondeempfangskette ist, eingeleitet. Der Hauptzweck dieses Models ist, das verwendete NMR-Spektroskopiesystem zu optimieren und schließlich das Messen der NMR-Stichproben mit sogar niedrigerem Antwortsignal als die heutzutage messbaren zu ermöglichen. Alle Parameter des NMR-Spektroskopiesystems, die in dem eingefűhrten Model verwendet waren, kőnnen leicht mittels Vektor-Netzwerkanalysator und Rauschzahlmesser gemessen oder in Datenblätter der jeweiligen Elementen gefunden werden, bis auf die Rauschzahl des Empfangsteils des Spektrometers. Hier wird das Verfahren des Messens der Rauschzahl des Empfangsteils vom Spektrometer, durchgeführt mit der Methode doppelter Leistung, beschrieben. Eine Blockdiagrammdarstellung vom Empfangsteil des Spektrometers, als auch sein approximatives Model, liegen hier vor. Die Resultate der Messungen der entsprechenden Rauschzahlen, die auch dargestellt sind, klären die allgemeine Tendenz, Spannweitenmitte des Verstärkungsregelunggrades bei Ausfűhrung derzeitigen NMR-Messungen zu verwenden, auf.
About the authors
Petar Kolar was born in Koprivnica, Croatia in 1992. He received the B. S. degree in electrical engineering and information technology, the M. S. degree in information and communication technology, and the Ph. D. degree in the scientific field of electrical engineering from the Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, in 2013, 2015 and 2020, respectively. From 2016 to 2019 he was a Research and Teaching Assistant with the Experimental Physics Division of the Department of Physics at the Faculty of Science, University of Zagreb, Zagreb, Croatia. Since 2019, he has been a Senior Software Developer with Ericsson Nikola Tesla d. d., Zagreb, Croatia. He is the author of two international journal papers and three conference papers. He also participated in two conference papers as a co-author. His research interests include computer programming, microwave and RF engineering, electronics, and embedded electronics.
Lovro Blažok was born in Koprivnica, Croatia in 1994. He received the B. S. degree in geological engineering and the M. S. degree in geological engineering from the Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb, Zagreb, Croatia in 2016 and 2018, respectively. From 2018 to 2020 he was a Geological Engineer/Hydro-geologist with FIL.B.IS. projekt d. o. o., Zagreb, Croatia. Since 2020 he is working as a Geological Engineer with Geotech d. o. o., Rijeka, Croatia. He participated in one international journal paper and two conference papers as a co-author. His research interests include computer programming, geological engineering, hydro-geology and drilling.
Dario Bojanjac was born in Zagreb, Croatia in 1986. He received dipl.ing. and Ph. D. degree in electrical engineering from the Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, in 2009 and 2015 respectively and B. S. degree in mathematics from the Faculty of Science, University of Zagreb. From 2009 to 2019 he was a Research and Teaching Assistant at the Department of Wireless Communications, Faculty of Electrical Engineering and Computing, University of Zagreb. Since 2019 he is Assistant Professor at the same department. He is the author or co-author of 4 international journal papers and 7 conference papers. His research interests include numerical methods for Maxwell’s equations, mathematical modelling of electromagnetic scattering problems and homogenization techniques for PDEs.
Acknowledgment
A huge thanks to Mario-Osvin Pavčević, PhD and Bernhard Zagar, PhD, for their help with the translation to German language.
References
1. D. D. Traficante, “Time averaging. Does the noise really average toward zero?,” Concepts in Magnetic Resonance, vol. 3, no. 2, pp. 83–87, Apr. 1991.10.1002/cmr.1820030203Search in Google Scholar
2. I. R. Kleckner and M. P. Foster, “An introduction to NMR-based approaches for measuring protein dynamics,” Biochimica et Biophysica Acta (BBA) – Proteins and Proteomics, vol. 1814, no. 8, pp. 942–968, Aug. 2011.10.1016/j.bbapap.2010.10.012Search in Google Scholar PubMed PubMed Central
3. P. Kolar, M. S. Grbić and S. Hrabar, “Sensitivity enhancement of NMR spectroscopy receiving chain used in condensed matter physics,” Sensors, vol. 19, no. 14, pp. 3064, Jul. 2019.10.3390/s19143064Search in Google Scholar PubMed PubMed Central
4. “NMRCalc: NMR Spectroscopy Rx Chain Noise Figure Calculator,” website, available: https://nmrcalc.github.io/.Search in Google Scholar
5. “NMR Spectroscopy Rx Chain Noise Figure Calculator,” GitHub, available: https://github.com/5ARK/NMR_F_Calc.Search in Google Scholar
6. “NMR Spectroscopy Rx Chain Noise Figure Calculator,” Dropbox, available: https://www.dropbox.com/s/ah3fl94zxshya7q/NMR_Rx_NF_Calculator.rar?dl=0.Search in Google Scholar
7. M. Hiebel, Fundamentals of Vector Network Analysis, 6th ed. Germany: Rohde & Schwarz, 2014.Search in Google Scholar
8. Keysight Technologies, “Fundamentals of RF and Microwave Noise Figure Measurements,” Application note, 2017.Search in Google Scholar
9. P. Kolar, Optimization of radio frequency components of cryogenic Nuclear Magnetic Resonance spectroscopy system, Doctoral thesis, University of Zagreb, Zagreb, Croatia, Feb. 2020.Search in Google Scholar
10. A. Kay, Operational Amplifier Noise, Waltham, USA: Newnes, 2012.10.1016/B978-0-7506-8525-2.00009-5Search in Google Scholar
11. C. D. Motchenbacher and J. A. Connelly, Low-Noise Electronic System Design, Toronto, Canada: John Wiley & Sons, Inc., 1993.Search in Google Scholar
12. Tecmag Redstone spectrometer, available: http://www.tecmag.com/redstone/.Search in Google Scholar
13. D. M. Pozar, Microwave Engineering, 4th ed., USA: John Wiley & Sons, Inc., 2011.Search in Google Scholar
14. E. Fukushima and S. B. W. Roeder, Experimental Pulse NMR: A Nuts and Bolts Approach, Reading, Massachusetts, USA: Addison-Wesley Publishing Company, Inc., 1981.Search in Google Scholar
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