Ion Trajectories in the Injection Quadrupole for SIFT-MS

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1 WDS' Proceedings of Contributed Papers, Part II, 44 48, 0. ISBN MATFYZPRESS Ion Trajectories in the Injection Quadrupole for SIFT-MS A. Spesyvyi Charles University Prague, Faculty of Mathematics and Physics, Department of Surface and Plasma Science, V Holešovičkách, Prague 8, Czech Republic. P. Španěl J. Heyrovsky Institute of Physical Chemistry, Academy of Sciences of the Czech Republic, Dolejškova 3, Prague 8, Czech Republic. Abstract. Selected ion flow tube mass-spectrometry is a technique for the real time quantification of trace gases in air and breath. The limit of quantification is currently about 0 parts per billion by volume (ppbv). However to extend the range of analytical capabilities much better sensitivity with a detection limit of ppbv is needed. The first step for increasing sensitivity of SIFT-MS is the optimisation of the injection quadrupole resulting in higher ion signal injected from the ion source into the flow tube reactor. This goal can be achieved by the improved focusing using ion optical lens voltages that would result into optimum ion trajectories and ultimately by optimisation of the geometry of ion optics. Introduction Selected ion flow tube mass-spectrometry, SIFT-MS, is a real-time quantification method for analyses of trace amounts of volatile compounds in air in the presence of water vapour. This technique can be used in medicine for diagnosis of disease from breath, in security for detection of explosives and toxic substances, in environmental monitoring and food control, [Smith et al., 005; Španěl et al., 0]. The SIFT-MS technique is based on the quantification of the count rate of product ions formed by reactions of the injected precursor ions with molecules of sample compound by detection quadrupole mass-spectrometer, [Španěl et al., 006]. Using a library of rate coefficients of ionmolecular reactions it is possible to calculate unknown concentrations of analyte compounds in the sample. Precursor ions are selected from a mixture of ions extracted from the ion source by quadrupole mass-filter (see Figure ). This mass-filter with input and output focusing systems represented by electrostatic lenses is called injection quadrupole. Count rate of injected precursor ions in the flow tube reactor is one of the most important parameters for quantification and directly influences the sensitivity of SIFT-MS, [Ross, 008]. The first step in the process of increasing the precursor ion count rate is the optimization of the injection quadrupole via variation of its focusing lenses voltages to reach the best ion optical conditions for ions trajectories. This can be conveniently carried out using a computer model of the investigated system implemented by the specialised simulation environment SIMION 8. The key features of this software are: electrostatic fields solving, particle tracing, user programming and data recording, [Manura et al., 008]. Experimental methods Selected ion flow tube mass spectrometry, SIFT-MS Schematic diagram in Figure shows the microwave discharge ion source, injection mass filter and the detection quadrupole mass spectrometer and the three metal plates D, D and D 3 to which ion current can be measured and which support the orifices O, O and O 3. Ions pass from the ion source into the injection mass filter via O, mass selected ions enter the flow tube via O and the reagent and product ions are sampled into the analytical quadrupole mass spectrometer via O 3. Direct breath sampling into the instrument is illustrated as an example of real time analysis in Figure. For the present experiment a Profile 3 SIFT-MS instrument (manufactured 006 by Instrument Science Limited, Crewe, UK) was used. Experimental determination of reproducibility of SIFT-MS breath analyses Figure shows raw data from SIFT-MS measurements of time dependences of concentrations of 44

2 acetone, ethanol and formaldehyde in exhaled breath of one person. Similar data were obtained for three other persons and then standard deviations and coefficients of variation (c.v. = S.D./mean, [Good et al., 003]) were calculated. Measurements were done at optimal setting of the instrument and then repeated several times at settings leading to lowered count rates of the precursor ions. Thus the dependence of c.v. on the injected ion count rate was obtained. Comparison of model predictions of influence of lens voltage on injected ion current with experiments In order to validate the model calculations the following procedure was used: voltage of one of the lens plates (labelled U on the schematic drawing of the injection quadrupole shown in Figure 3) was varied in a wide range around the optimal setting. Ion currents collected by the plate supporting the injector orifice (designated I ) and injected into the flow tube and collected by the downstream sampling plate (designated I ) were measured using the built in electrometric amplifiers of the SIFT- MS instrument, [Workman, 006]. This series of measurements was carried out to in order to quantify the dependencies of the ions currents at the injector and in the flow tube on voltages of the chosen focusing lens. Numerical model of the injection quadrupole was created in the specialised simulation environment SIMION 8, [Manura et al., 008]. This software was chosen because of the possibility to create customised scripts for changing of voltages on quadrupole rods in time and for recording the output data (counts of ions hitting the electrodes). Geometry was constructed according the schematic arrangement in Figure 3 and the following potentials were used: U =6 V, U l = 5 V, U l = 0 V, U l3 = 35 V. inj Figure. Schematic diagram of the Profile 3 SIFT-MS instrument, [Smith et al., 009]. ppb time [s] Figure. Raw data from SIFT-MS measurements of time dependencies of concentrations of several compounds (in parts per billion, ppb) for ten breath samples. 45

3 Figure 3. Schematic drawing of the injection quadrupole system: U inj ion source voltage, U l, U l, U l3 focusing lenses voltages, U ax quadrupole rods axial voltage, U focusing lens voltage, I injector current, I ions detector current. Ions HO + 3 with m/z 9 were used for the modelling with initial energy 5 6 ev. Quadrupole was modelled with frequency of.6 MHz and optimal voltages for filtering of m/z 9. To check the agreement between the computer model and the processes occurring in the real apparatus, the dependences were obtained of ions numbers reaching the electrode plate I and passing through the injection orifice onto the sampling plate I on the focusing lens voltage U. The output data were averaged for ten equal simulations to achieve more smooth dependence curves. Results Figure 4 shows the decrease of the coefficient of variation with the increase of the ion count i.e. the increase of the number of ions collected by the ion detector of the detection quadrupole mass spectrometer. The theoretical square root dependence of the coefficient of variation c v on the number of detected ions, N, is also shown in Figure 4. as given by the following equation, [Currie, 999]: c v. () N It is clear from the plot that the experimental dependence slightly differs from the theoretical one by its power. This can be explained by the methodology of measurements and calculations. And yet the experimental dependence almost fits square root law. The results of experiments carried out on the real SIFT-MS instrument for variable focusing lenses voltage are shown in Figure 5. The dependence for ion currents on the lens voltage U calculated by the computer simulation in SIMION 8 is shown in Figure 6. Figure 4. A dependence of the coefficient of variation (in percent) on the ion count in the breath analysis experiments fitted by a power law. Theoretical square root dependence is also shown. 46

4 Figure 5. The experimental dependences of ions currents at the injector I and at the detector I on voltages at focusing lens, α scale coefficient. Figure 6. Calculated dependence of the number of filtered ions ( N ) and the number of injected ions N ) on the focusing lens voltage, β scale coefficient. ( Comparing the experimental dependence (Figure 5c) with the calculated one (Figure 6) indicates that these curves have very similar characteristics. The only slight difference is in the slopes of the curves in the region of low voltages. Most likely this is due to the absence of the ion-molecular collisions in the numerical model of the injection quadrupole ion optics, [Forbes et al., 999]. The value of coefficient beta was 3. The difference in magnitude of the experimental currents in Figure 5 (coefficient alpha was 000) is also influenced by diffusion losses in the flow tube that were not included in the numerical model. In the real experiment the ions are colliding with the atoms of carrier gas that penetrate through the injector orifice back into the region of ion optics, [Adams et al., 976]. Conclusions From the dependence of the coefficient of variation on ions count (Figure 4) it is clear that the increase of the ion count transmitted to the flow tube reactor results in the higher sensitivity and reproducibility of SIFT-MS. The primary opportunity for the increasing of ions number entering the flow tube via the SIFT injector is the optimization of the injection quadrupole and in particular of its focusing system. As Figure 5 shows lens has an optimum voltage value corresponding to the detector ion current maximum. In future work the lens geometry will be varied in order to find the optimum ion optics conditions leading into ion trajectories most effectively injecting the ions into the flow tube. The developed numerical model in SIMION 8 corresponds well to the behaviour of the real apparatus (Figures 5c, 6). This indicates that this model can be used with confidence for further investigations. Collisions of ions with the background gas will be added to the computer model to make it more realistic. 47

5 Acknowledgements. The authors thank Kseniya Dryahina for her help with the experiments and to Jan Žabka for useful discussions concerning SIMION modelling. The present work was supported by GACR projects no. 0/09/0800 and 03/09/056. References Adams, N. G. and D. Smith, Selected ion flow tube (SIFT) technique for studying ion-neutral reactions, International Journal of Mass Spectrometry and Ion Processes, , 976. Currie, L. A., Nomenclature in evaluation of analytical methods including detection and quantification capabilities: (IUPAC Recommendations 995), Analytica Chimica Acta 39, 05 6, 999. Forbes, M. W., M. Sharifi, et al., Simulation of ion trajectories in a quadrupole ion trap: a comparison of three simulation programs, Journal of Mass Spectrometry 34, 9 39, 999. Good, P. I. and J. W. Hardin, Common Errors in Statistics (and how to avoid them), Chapter: Ad hoc, Post hoc hypotheses., Hoboken, Wiley, 003. Manura, D. and D. Dahl, SIMION (R) 8.0 User Manual, Ringoes, Scientific Instrument Services, Inc., 008. Ross, B., Sub parts per billion detection of trace volatile chemicals in human breath using selected ion flow tube mass spectrometry, BMC Research Notes, 4, 008. Smith, D., A. Pysanenko, et al., Ionic diffusion and mass discrimination effects in the new generation of short flow tube SIFT-MS instruments, International Journal of Mass Spectrometry 8, 5-3, 009. Smith, D. and P. Španěl, Selected ion flow tube mass spectrometry (SIFT-MS) for on-line trace gas analysis, Mass Spectrometry Reviews 4, , 005. Španěl, P., K. Dryahina, et al., A general method for the calculation of absolute trace gas concentrations in air and breath from selected ion flow tube mass spectrometry data, International Journal of Mass Spectrometry 49, 30 39, 006. Španěl, P. and D. Smith, Progress in SIFT-MS: breath analysis and other applications, Mass Spectrometry Reviews 30, 36 67, 0. Workman, C., Profile Series User Manual, Crewe, UK, Instrument Science Ltd.,