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Voltage Sweep Ion Mobility Spectrometry Eric J. Davis, Michael D. Williams, William F. Siems, and Herbert H. Hill, Jr.* Department of Chemistry, Washington State University, Pullman, Washington 99164, United States ABSTRACT: Ion mobility spectrometry (IMS) is a rapid, gas-phase separation technique that exhibits excellent separation of ions as a standalone instrument. However, IMS cannot achieve optimal separation power with both small and large ions simultaneously. Similar to the general elution problem in chromatography, fast ions are well resolved using a low electric field (50-150 V/cm), whereas slow drifting molecules are best separated using a higher electric field (250-500 V/cm). While using a low electric field, IMS systems tend to suffer from low ion transmission and low signal-to-noise ratios. Through the use a novel voltage algorithm, some of these effects can be alleviated. The electric field was swept from low to high while monitoring a specific drift time, and the resulting data were processed to create a `voltage-sweep’ spectrum. If an optimal drift time is calculated for each voltage and scanned simultaneously, a spectrum may be obtained with optimal separation throughout the mobility range. This increased the resolving power up to the theoretical maximum for every peak in the spectrum and extended the peak capacity of the IMS system, while maintaining accurate drift time measurements. These advantages may be extended to any IMS, requiring only a change in software.
I
on mobility spectrometry (IMS) is an analytical technique most commonly used for homeland security applications. These applications utilize IMS in the search for explosives, narcotics, and other trace contraband.1,2 In these roles, the IMS must distinguish between closely related chemical compounds and reliably respond when an illicit material is present. IMS must also produce this information with a minimum of false positive and negative responses, as well as providing the data very quickly in order to maximize sample throughput. However, IMS has lower resolution when compared to mass spectrometry (MS) or chromatography.2,3 This low resolution often produces broad, indistinct peaks in realworld samples, as the complex matrix of environmental compounds overloads the ability of the IMS to resolve distinct peaks. The use of longer drift tube IMS systems are utilized to resolve samples with a complex matrix, and coupling ion mobility spectrometers with mass spectrometers creates a high resolution hybrid ion mobility-mass spectrometry system (IMMS).3 However, the small instrument footprints needed by commercial manufacturers of field-portable IMS systems limit resolution, and bulky vacuum systems preclude the use of mass spectrometers. Thus, improving the ability of a small IMS system to resolve closely related peaks is highly desirable. Several studies have been conducted to increase the resolving power of a small IMS system. These studies included the use of pressure,4,5 temperature,6,7 drift gas selection,8,9 drift tube design,10,11 and voltage.1,4,6,12 Each of these instrumental parameters has a distinct effect on the resolving power of an IMS system. Normally, pressure, temperature, and drift gas are set before a DT-IMS experiment begins and are not changed during r 2011 American Chemical Society
the IMS spectral acquisition. However, Davis et al. (2009) showed that pressure tends to increase resolving power but also increases ion-neutral clustering.4 Temperature decreases clustering but also decreases resolving power. Often, IMS devices are operated at ambient pressure and at temperatures between 100 and 200 °C in order to achieve the highest resolving power possible without clustering effects.1 Increased temperature also tends to help keep an IMS clean of contaminants and reduce cleardown time, allowing for higher sample throughput. The overall design of the drift tube is primarily dependent upon the length of the tube. A longer tube with the same electric field will produce a higher resolving power but sacrifices signal. Finally, the selection of drift gas can significantly alter the separation characteristics of the ion mobility experiment, and drift gas composition is comparable to changing the stationary phase in chromatography.8,9 The use of a specific drift gas alters the polarizability of the gas, leading to differing ion-neutral interactions. These changed interactions can facilitate the separation of one pair of ions while inhibiting the separation of other ions.8,9 Voltage is the only variable that is easily changed during an IMS experiment and has a profound impact on IMS resolving power.1,4,12 However, the optimal drift voltage used to achieve maximum resolving power often results in low signal-to-noise ratios, so nonideal voltage conditions are commonly used to achieve lower detection limits. At low voltages, the peaks of ions with low mobilities are often broad with low signal-to-noise Received: August 9, 2010 Accepted: December 13, 2010 Published: January 21, 2011 1260
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ratios, but at high voltages the resolving power of ions with high mobilities can be sacrificed. This difficulty of separating a wide range of mobilities in a single run is similar to that experienced in chromatography and defined as the general elution problem. The general elution problem in chromatography has been known for many years and describes the situation where a chromatographic system does not have ideal separation for all compounds throughout the experiment.13-16 Instead, the system can be optimized only for either long or short retention times. Temperature programming solved the general elution problem in gas chromatography (GC) but sacrifices sample throughput due to increased analysis times. Gradient elution solved the general elution problem in liquid chromatography (LC) but is difficult to accurately reproduce among various LC systems and laboratories. Similarly, density programming corrected the general elution problem for supercritical fluid chromatography (SFC).13-17 Currently, no solution to ion mobility spectrometry’s general elution problem has been reported. It is possible to alter IMS conditions to favor increased separation of ion populations containing slow or fast ions but not both types of ions simultaneously. Previous work in the Hill lab has demonstrated that an optimal voltage exists for each mobility to achieve the highest possible resolving power.4,6,12 Thus, the objective of this project was to evaluate the approach of changing the drift voltage during the ion mobility experiment to achieve improved peak capacity and increased resolving power.
’ THEORETICAL CONSIDERATIONS IMS analyte drift times are characterized by calculating reduced mobility values (in cm2 V-1 s-1), where the mobility of an ion is adjusted with respect to standard temperature and pressure to account for differences in operating conditions between separate instruments; these values allow comparison of results throughout the IMS community. Reduced mobility (K0) is defined as:1,18 K0 ¼
L2 P 273:15 Vtd 760 T
ð1Þ
where L is the length of the drift tube (in cm), V is the voltage across the drift tube, td is the drift time of the ion (in seconds), P is the pressure, and T is the temperature of the drift tube. This equation provides a method for comparing results between IMS systems but, in order to compare the relative ability of two separate systems to separate similar compounds, resolving power is used. Resolving power in IMS is defined as:4-7,12 Rp ¼
td fwhm
ð2Þ
where R is the resolving power of the instrument, td is the drift time of a peak, and fwhm is the full width at half of the maximum of the IMS spectral peak. Previously, IMS theory regarding the resolving power was developed, and the resolving power of an IMS system under varying conditions can be described by:4,19 1 Rc ¼ sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2 2 2 2 tg K0 T V 760 16kB Tln 2 þ 4 2 273:15 qV LP
ð3Þ
where tg is the pulse width of the ion gate, K0 is the reduced mobility of the ion of interest, T is the temperature, V is the voltage across the drift space, L is the length of the drift tube, P is
the pressure of the system, kB is the Boltzmann constant, and q is the elementary charge. This is known as the conditional resolving power (Rc) of an IMS instrument and is a theoretical resolving power assuming that the only factors which affect resolving power in an ion mobility experiment are the gate pulse width and simple diffusion. An optimal drift voltage can be calculated by taking the derivative of eq 3 with respect to voltage, producing:4 2 #1=3 4 2 L P ð4Þ Vopt ¼ 0:03954 2 2 t g K0 T Equations 1 and 4 may be combined and solved for drift time to produce an optimal drift time at any voltage: rffiffiffiffiffiffiffiffiffiffiffiffiffi tg 273:15 TV ð5Þ topt ¼ 760 0:0395T 0:0395 This drift time value is independent of the length and pressure of the drift tube (though the mobility of the ion characterized by a specific drift time is dependent on the length and pressure), providing a simple curve which may be applied to any drift tube to achieve similar results. Theoretical results of eqs 3 and 4 may be found in Figure 1a. The curve series presented represents the resolving power predicted by eq 3, plotted versus drift voltage in the range of 0 to 12 000 V. The dashed line represents the resolving power predicted by eq 4, intersecting each curve at the maximum predicted value (optimal voltage). These values correspond to the drift times predicted by eq 5 and are shown in Figure 1b. These plots indicate that as voltage is increased, the IMS spectrum can be monitored at the drift time predicted by this curve to maintain optimal resolving power of the instrument. In this way, the instrument can be optimized by voltage programming in much the same way that a gas chromatograph is optimized through the use of temperature programming.
’ EXPERIMENTAL SECTION Reagents and Gases. All compounds used were reagent grade, neat liquids from Sigma-Aldrich (St. Louis, MO). These compounds were diluted in HPLC grade methanol at concentrations which maintained a vapor pressure of 1 Torr for the analyte of interest. This allowed the use of multiple compounds simultaneously while maintaining equal amounts of sample entering the system. Throughout the experiments, ultrahigh purity compressed air was used as the drift gas, with a flow rate of 1.5 L/min. IMS Cell and Hardware. The IMS drift tube used in this work was built using the traditional stacked-electrode design, consisting of 22 stainless steel electrodes separated by alumina (99%, Bolt Technical Ceramics, Fairfield, NJ) spacers to provide electrical isolation. Each resistor was connected to its neighbor through 1 MΩ resistors ((1%, Caddock, Riverside, CA), and the high voltage was applied to the first ring in the series, which provided an electric field gradient the length of the drift tube. An ion packet was selected through the use of a Bradbury-Nielsen style ion gate, pulsed at 0.2 ms throughout these experiments. The entire tube was heated using two 300 W Watlow cartridge heaters (St. Louis, MO), controlled using an Omega CN9000A temperature controller (Stamford, CT). This provided a constant temperature throughout the drift region of the IMS cell, controlled from room temperature up to 200 °C. High voltage was provided using a Bertan 230 (Hauppauge, New York) power supply, and drift gas flow rate was controlled using an MKS M100B mass-flow 1261
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Figure 1. (a) Plot of conditional resolving power (Rc) versus voltage over the range of 0 to 12 000 V for several reduced mobility values. Calculated using eq 3, each mobility value has an optimal voltage, as indicated by the dashed line. (b) Plot of optimal drift time versus voltage. Calculated using eq 5, this line is scanned as the voltage is increased to maintain optimal drift time and voltage.
controller (Andover, MA). Voltage and drift gas flows were controlled and maintained through the operating software of the IMS. Ionization was achieved using a 50 mCi 63Ni foil affixed to a screen on the first ring in the reaction region. The high energy β particles from this foil provided initial ionization of the drift gas, after which samples were ionized through atmospheric pressure chemical ionization processes. Sample Introduction. Diluted samples were pipetted into 5 mL glass sample vials which were placed in a stainless steel sample chamber. This chamber was heated and had a controlled flow of air across the headspace of the sample vial. This carrier gas transported the vapor through a 300 μm heated fused-silica capillary transfer line into a specially designed electrode ring within the IMS. The ring allowed a fused-silica capillary carrying the sample vapor to penetrate into the reaction region of the IMS immediately before the ion gate. In this position, the introduced sample vapors were carried by the drift gas toward the front of the IMS tube and the ionization source, where the sample was ionized. Software. All software used in this study was designed inhouse using the LabView (National Instruments, Austin, TX) 2009 Professional Development System. A National Instruments NI PCI-MIO-16XE-10 DAQmx board (Austin, TX) provided
analog input and output capabilities and allowed the control of the voltage and gas flow rate, as well as monitoring these values and collecting the IMS signal. The software allowed the experimenter to operate the system in either the traditional drift time mode, or in the novel voltage sweep mode. In the drift time mode, the software provided the pulse sequence for the ion gate, as well as spectral averaging routines for the ion signal. The voltage sweep mode provided the ability to dynamically control the voltage applied to the IMS, while simultaneously controlling the pulsing sequence and signal averaging within the IMS system. The software was designed to increase the voltage by a set amount at a specific frequency. Typically in these studies, the voltage was increased by 10 V/s, with a 25 ms scan time for the IMS, and 40 averages per point. These conditions were selected to provide signal above the limit of detection (LOD) for each peak. For data output, the software provided the ability to select a specific drift time to monitor or view the data as a two-dimensional plot of drift time versus applied voltage. The software automatically saved both forms of the data output, allowing the experimenter to easily manipulate the data. A data analysis package was also created to coincide with the voltage-sweep software, providing a two-dimensional drift time 1262
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Figure 2. Screen shot of a 2D drift time (ms) versus voltage plot with color scale intensity of n-butylamine. The curved red trace indicates the optimized voltage sweep curve, while the horizontal and vertical red traces indicate the voltage sweep and single gate modes, respectively. The intensity of the response is measured at each point along one of these traces to form a spectrum.
versus voltage plot. By superimposing software-generated cursors over this plot, either the averaged IMS spectrum for any voltage or the voltage-sweep plot could be viewed at any selected drift time. In addition, from either of these plots, the resolving power of a single, selected peak, or the resolution of two adjacent peaks could be automatically calculated. The reduced mobility could also be calculated for any point in the spectrum, assuming the appropriate instrumental parameters (T, P, etc.) were input into the software. Finally, according to eq 5, this software could dynamically change the drift time which was being monitored. In this way, for each voltage setting, the intensity of the spectrum was monitored at the optimal drift time as predicted by eq 5 and shown in Figure 1b. This line was calculated automatically according to the parameters input by the user and changed dynamically if parameters were altered. Voltage Sweep Parameters. In order to investigate the effect of the voltage sweep scan rate on the resolving power, several different voltage curves were investigated. In selecting these values, the power supply limited the voltage resolution (volts/ step) to a minimum of 5 V, and the IMS gate pulsing allowed any update frequency below 40 Hz (to allow at least one spectrum before the voltage was increased, assuming a 25 ms scan time). The values of the voltage curve had a significant impact on the experimental time period, as well as the number of IMS averages obtained for each data point. For example, a voltage resolution of 10 V, swept from 1000 to 10 000 V, with 40 IMS spectral averages per point had an experimental time of approximately 15 min. However, a voltage resolution of 5 V, the same voltage range, and the same number of IMS spectral averages took 30 min. Finally, a resolution of 20 V with 80 IMS averages required 15 min. However, an increased voltage resolution decreased the number of points available for the voltage sweep and optimized spectra, which resulted in a point-to-point averaging effect across theses spectra, reducing the apparent resolving power. Thus, a significant tradeoff existed between the IMS averages (and thus signal-to-noise), voltage resolution, and time of experiment. Overall, the number IMS spectral averages as used in this work were determined primarily by a compromise between the length of experimental time and the S/N ratio of the instrument. A parameter set used was 80 IMS spectral averages for each point, swept from 1000 to
10 000 V, with a voltage resolution of 10 V, resulting in a 20 min experimental period.
’ RESULTS AND DISCUSSION Separation Using Optimal Drift Time/Voltage Curve. Figure 2 shows a software screenshot of a 2D drift time versus voltage plot for n-butylamine. The software allowed the user to select any voltage (using the vertical red trace) to produce a drift time spectrum at that voltage. The horizontal trace allowed any drift time to be selected, producing a voltage sweep spectrum of intensity versus voltage, and the curved red trace indicates the results of eq 5 for the parameters used in this study. A plot of the intensity at each point along this trace produced the optimized spectrum. Figure 3 shows four spectra of n-butylamine as obtained using the cursors mentioned above. Figure 3a shows the mobility spectrum of n-butylamine with the IMS set to operate at the optimal voltage for this compound (1920 V, 180 V/cm). Figure 3b shows the mobility spectrum of n-butylamine at a voltage of 4032 V, or 400 V/cm. As expected, a lower electric field produced a decreased signal, but facilitated separation, whereas the higher field produced increased intensities at the sacrifice of resolution. Similar results would be expected if a faster drift time were selected for the voltage sweep spectrum displayed in Figure 3c. Both spectra used the same carrier gas flow rate and quantity of n-butylamine, but the spectrum obtained at 400 V/cm indicated a significantly higher signal-to-noise ratio (S/N), 178 as compared to 85 for the optimal voltage. However, the spectrum obtained at 180 V/cm provided a resolving power of 33, whereas the spectrum obtained at 400 V/cm had a resolving power of 25. This is compared to the conditional resolving power (theoretical, as calculated from eq 3) of 59. When the system was used in the voltage sweep mode, similar resolving powers were obtained. At the optimal drift time of 21.14 ms for n-butylamine, the voltage sweep (Figure 3c) provided a resolving power of 34. However, if the voltage and drift times were scanned according to eq 5 (Figure 3d), the resolving power increased to a value of 49, near the conditional resolving power according to eq 3. This optimal resolving power was due to the system automatically maintaining the 1263
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Figure 3. (a) Ion mobility spectrum of n-butylamine operated at 1920 V (optimal voltage as calculated by eq 3). (b) IMS Time Scan spectrum of n-butylamine operated at 4032 V (common voltage for good signal-to-noise ratios). (c) IMS Voltage Scan spectrum of n-butylamine monitored at 19.32 ms (optimal drift time for K0 of 1.95 as calculated by eq 3). (d) IMS Optimized scan of n-butylamine where drift time and voltage were scanned simultaneously according to eq 5.
optimal drift time as the voltage was changed throughout the experiment. The spectra displayed showed highly varied maximum intensity values. The highest signal intensity was found using the drift time mode at the highest voltage (4032 V, 400 V/cm) (Figure 3b). However, the maximum signal observed in Figure 3a,c,d, where the optimized voltages and drift times were utilized, was much lower. This was due to the low electric fields produced by optimizing the system for resolving power. By decreasing the monitored drift time, the electric field is increased, resulting in an increased S/N ratio. Finally, the optimized mode spectrum displayed in Figure 3d could be manipulated to higher signal intensity values through a multiplier within the software. This shifted the selected drift time/voltage curve, as calculated by eq 5, to values above or below that calculated as the theoretical maximum. By selecting a faster drift time, signal intensities could be increased in the same way as described for the voltage sweep mode. Optimized resolving power through the use of the simultaneous voltage and drift time programming algorithm was consistent regardless of the compound chosen. For example, 4-methyl-2pentanone has a conditional resolving power of 61 under the conditions presented. In the drift time mode (traditional IMS), a resolving power of 44 was obtained at the optimal voltage for a K0 of 1.39 cm2 V-1 s-1 (2296 V). In the voltage-sweep mode, a resolving power of 42 was obtained at the optimal drift time for this same K0 (21.33 ms). Finally, under the optimized drift time/ voltage conditions, a resolving power of 56 was obtained. Table 1 contains the results of several compounds tested using this method and lists the reduced mobility (K0), the conditional resolving power (Rc), the Time Scan mode resolving power (Rt, obtained at the optimal voltage for the specified K0), the Voltage Scan mode resolving power (Rv, obtained at the optimal drift
Table 1. Reduced Mobilities (K0), Conditional Resolving Powers (as calculated by eq 3) (Rc), Drift Time IMS Resolving Powers (Rt), Voltage Sweep IMS Resolving Powers (Rv), Drift-Time Optimized Voltage Sweep IMS Resolving Power (Ropt), and Reduced Mobility Values (K0lit) from Literature for Several Common Compounds in IMS K0
K0lit
Rc
Rt
Rv
Ropt
2,4-lutidine
1.95
1.951
60
40
35
48
di-tert-butylpyridine
1.43
1.422,4
66
44
40
56
dimethyl methylphosphonate
1.91
1.911
60
24
31
43
n-butylamine
1.95
1.931
60
37
31
39
hexylamine cyclohexylamine
1.69 1.81
1.681 1.8120
63 61
40 43
35 31
52 50
heptylamine
1.59
1.581
64
40
37
51
cycloheptylamine
1.71
1.7120
62
40
38
62
benzylamine
1.75
1.731
62
38
31
47
2-butanone
2.03
2.001
59
33
36
51
4-Mmethyl-2-Pentanone
1.39
61
44
42
56
2-hexanone
1.78
1.791
61
36
33
48
cyclohexanone cycloheptanone
1.85 1.71
1.841
61 62
35 40
34 36
48 50
methyl salicylate
1.57
1.5621
60
34
32
43
compound
time), the optimized Voltage Scan mode resolving power (Ropt) for the monomer peak of each compound, and the literature value for the reduced mobility of each compound (K0,lit). The experimental data obtained by this method gave an average Rt that corresponds to 62% of the expected Rc, the Rv gave an average of 57%, and the Rvopt gave an average of 81% of Rc. Thus, the use of the drift time algorithm provided a 31% increase 1264
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Figure 4. (a) Software screenshot of a 2D drift time vs voltage of a mixture of 4-methyl-2-pentanone, 2-butanone, and heptylamine with intensity indicated by color. (b) Single gate spectra taken from the screenshot in part a at 3800 and 1730 V, compared to the optimized spectrum obtained from the curved red trace in part a. Intensity values have been offset for simultaneous display. Peak identities displayed on the optimized spectrum were determined using reduced mobility values. Through the use of the optimized mode spectrum, peaks of both high and low mobility values were simultaneously baseline separated, while they could not be well separated using either the high or low voltage drift time IMS.
in resolving power, 19% relative to the conditional resolving power. Separation of a Mixture. 4-Methyl-2-pentanone, 2-butanone, and heptylamine were combined and separated using voltagesweep IMS. Figure 4a shows the 2D drift time versus voltage intensity plot of this separation. Drift time mode IMS spectra of this separation were compared to the optimized spectra in Figure 4b. Peak identification shown in Figure 4b was achieved through the use of reduced mobility values. At high field (3800 V, 350 V/cm), seven peaks are visible, but several were not baseline separated, especially noted between the two RIP peaks and between the RIP and the 2-butanone peaks. However, when drift time mode spectra were obtained under lower field conditions (1730 V, 160 V/cm);optimal for a K0 of 1.95 cm2V-1s-1;the peaks were well-separated, but with a loss in signal-to-noise ratio, as the 4-methyl-2-pentanone peak had an intensity value very close to the LOD for this instrument (the intensity of the
4-methyl-2-pentanone peak was 0.015 nA, the LOD was 0.012 nA). When the optimized mode was used, all seven peaks were resolved. In addition, in the voltage sweep mode the intensities of the peaks were much more uniform across the mobility range. This was due to the increased voltage at which the longer-drifting peaks were measured, resulting in increased signals for these peaks that are often difficult to detect at low voltages (as seen in the 1730 V spectrum). As with most analytical methods, absolute quantification may not be possible with IMS, as all of the ion losses are not well characterized. For quantification, standards would have to be used for the voltage sweep mode as well as with the constant voltage mode of operation, similar to those required in GC for both isothermal and temperature-programmed modes. In this way, the use of optimized voltage-sweep IMS solves the general-elution problem of IMS, allowing peaks of low and high mobility to be simultaneously separated within one experiment. 1265
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Figure 5. Vopt spectra of 2,4-lutidine during a 7 min (short), 25 min (medium), and 126 min (long) voltage sweep experimental period. The time difference between these runs was produced by increasing the number of averages per IMS spectra (short: 20, medium: 80, and long: 300), and decreasing the voltage interval between points (short: 20, medium: 10, and long: 5). The change from short to long experimental periods caused a significant increase in signal-to-noise between the three spectra. Note: medium and long scans have been offset for plotting on a single graph.
Figure 6. Reduced mobility values (in cm2 V-1 s-1) for several compounds plotted versus voltage from 1800 to 4000 V. For each compound, a single voltage sweep experiment was conducted and contains data points obtained at 10 V increments.
Voltage-Sweep Parameters. The application of the optimized drift time scanning curve increased the resolving power but also increased the length of the experimental period. The voltage scan experiments took significantly longer than a standard, drift time IMS experiment. Averaged IMS spectra were collected within a few seconds, but voltage-sweep IMS took at least several minutes and up to 2 h depending on parameters
previously mentioned. Thus, the effects of scan time on the voltage-sweep spectra were investigated to identify analytical trade-offs as a function of experimental period. Voltage sweep spectra were obtained for three condition sets: `a short method’ used 20 averaged IMS spectra per point and 20 V increments, with an experimental period of about 7 min. A `medium method’ used 80 averaged IMS spectra per point and 10 V increments, 1266
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Analytical Chemistry with an experimental period of about 25 min, and a `long method’ used 300 averaged IMS spectra per point and 5 V increments, with an experimental period of just over 2 h (126 min). Figure 5 shows V-sweep spectra for 2,4-lutidine for each of these scan times. As expected, the signal-to-noise ratios for these spectra increased as the scan time increased. However, from the medium scan to the long scan, an increase of only 25% was observed, whereas the short to medium scan gave a signal-to-noise increase of 185%. The decreased resolving powers for the short and medium scans were caused by the decreased number of data points in these spectra. By reducing the number of data points available, a point-to-point averaging effect was induced, causing the peak to broaden. The primary effect of experimental time on the spectra obtained was in the S/N ratios observed. In summary, the primary disadvantage of the optimized voltagesweep mode is the increase in experimental time. However, these time periods assume a complete voltage sweep. If speed was required, the voltage/drift time curve could be programmatically jumped to regions of interest, skipping over regions where the desired peaks do not appear. As an example, often the reactant ion peak is not of interest when other peaks are present, so the region of the voltage/drift time curve that contains only the reactant ions could be skipped. This corresponds to about 1500 V on the curve presented in Figure 1b, and at 10 V per second, saves 15 s. System Characterization through Voltage Sweep. Using the voltage sweep method allowed rapid system and compound characterization without the need for multiple experiments. Figure 6 shows the reduced mobility values for several compounds characterized in this study. The values shown in Table 1 indicate the reduced mobility values calculated for at the optimal voltage or drift time, whereas Figure 6 shows the reduced mobility calculated for each point along the voltage axis. In this case, the voltage sweep algorithm used a single experiment to replace several independent spectral acquisitions to produce reduced mobility values across a voltage range. Notable in Figure 6 was the apparent slope of the reduced mobility versus voltage of some of the compounds, especially 4-methyl-2-pentanone, DMMP, and n-butylamine. The range in reduced mobility for the compounds was no greater than 0.025 cm2V-1s-1, well within the expected error of (0.04 cm2 V-1 s-1. Thus, this was most likely due to a change in atmospheric pressure over the course of the experiment or some other parametric conditions that could not be controlled. However, this method allowed more accurate measurement of reduced mobility values as compared to a single drift time experiment, as the series of drift times measured can be plotted against the ratio of drift tube length squared over voltage. The slope of the resulting line is 1/K, providing a mobility value calculated over a range of conditions. Previously, this method for calculating mobility values was time and labor intensive, as each point required a separate experiment.
’ CONCLUSIONS The general elution problem of ion mobility spectrometry, in which optimized conditions for both low and high mobility ions cannot be achieved with a signal voltage, can be solved by sweeping the voltage during the analysis of a sample. In a method analogous to temperature programming gas chromatography and gradient elution liquid chromatography, voltage-sweep ion mobility spectrometry (VSIMS) provides a novel analytical approach which increases the peak capacity of ion mobility spectrometry. In addition to increased peak capacity, the voltage sweep can be programmed to operate under optimal voltage conditions for
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each drift time. By creating conditions wherein every peak in an IMS spectrum is detected under its specific optimal voltage, the resolving power of the instrument is maximized. Along with increased peak capacity and optimized resolving power, VSIMS permits the calculation of an ion’s mobility at a number of voltages, producing an average mobility value over a range of voltages. Similar to other analytical methods which program an instrumental parameter during the analysis (temperature program GC and gradient elution LC), the primary disadvantage of VS-IMS is an increase in analysis time. However, because voltages can be rapidly jumped from one setting to another, analysis time for known samples may be reduced by jumping the drift voltage to the appropriate settings for each component of the mixture. Finally, an operational advantage of VS-IMS is that it can be incorporated into any existing IMS instrument by the simple addition of software to sweep the voltage and analyze the data.
’ AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected]. Tel: 509-335-5648.
’ ACKNOWLEDGMENT This project was supported in part by NSF grant no. 0731306. ’ REFERENCES (1) Eiceman, G. A., Karpas, Z. Ion Mobility Spectrometry; CRC Press, Inc.: Boca Raton, FL, 1994. (2) Eiceman, G. A.; Nazarov, E. G.; Stone, J. A. Anal. Chim. Acta 2003, 493, 185–194. (3) Kanu, A. B.; Dwivedi, P.; Tam, M.; Matz, L.; Hill, H. H. J. Mass Spectrom. 2008, 46, 1–22. (4) Davis, E. J.; Dwivedi, P.; Tam, M.; Siems, W. F.; Hill, H. H. Anal. Chem. 2009, 81, 3270–3275. (5) Tabrizchi, M.; Rouholahnejad, F. Talanta 2006, 69, 87–90. (6) Rokushika, S.; Hatano, H.; Baim, M. A.; Hill, H. H., Jr. Anal. Chem. 1985, 57, 1902–1907. (7) Tabrizchi, M. Talanta 2004, 62, 65–70. (8) Kanu, A. B.; Hill, H. H. Talanta 2007, 73, 692–699. (9) Beegle, L. W.; Kanik, I.; Matz, L. M.; Hill, H. H. Int. J. Ion Mobility Spectrom. 2002, 216, 257–268. (10) Wu, C.; Steiner, W. E.; Tornatore, P. S.; Matz, L. M.; Siems, W. F.; Atkinson, D. A.; Hill, H. H. Talanta 2002, 57, 123–134. (11) Tolmachev, A. V.; Clowers, B. H.; Belov, M. E.; Smith, R. D. Anal. Chem. 2009, 81, 4778–4787. (12) Siems, W. F.; Wu, C.; Tarver, E. E.; Hill, H. H., Jr. Anal. Chem. 1994, 66, 4195–4201. (13) Ashbury, G. K.; Davies, A. J.; Drinkwater, J. W. Anal. Chem. 1957, 29, 918–925. (14) Greene, S. A.; Moberg, M. L.; M., W. E. Anal. Chem. 1956, 28, 1369–1370. (15) Nogare, S. D.; Bennett, C. E. Anal. Chem. 1958, 30, 1157–1158. (16) Patton, H. W.; Lewis, J. S.; Kaye, W. I. Anal. Chem. 1954, 27, 170–174. (17) Miller, J. M. Chromatography Concepts and Contrasts, 2nd ed.; John Wiley & Sons, Inc.: Hoboken, NJ, 2005. (18) Revercomb, H. E.; Mason, E. A. Anal. Chem. 1975, 47, 970–983. (19) Kanu, A. B.; Gribb, M. M.; Hill, H. H. Anal. Chem. 2008, 80, 6610–6619. (20) Kanu, A. B.; Haigh, P. E.; Hill, H. H. Anal. Chim. Acta 2005, 553, 148–159. (21) Ross, S. K.; Bell, A. J. Int. J. Mass Spectrom. 2002, 218, L1–L6.
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