Anal. Chem. 2010, 82, 1867–1880
Chemical Effects in the Separation Process of a Differential Mobility/Mass Spectrometer System Bradley B. Schneider,*,† Thomas R. Covey,† Stephen L. Coy,‡ Evgeny V. Krylov,‡ and Erkinjon G. Nazarov‡ MDS Analytical Technologies, 71 Four Valley Drive, Concord, Ontario, Canada L4K 4V8, and Sionex Corporation, 8-A Preston Court, Bedford, Massachusetts 01730 In differential mobility spectrometry (also referred to as high-field asymmetric waveform ion mobility spectrometry), ions are separated on the basis of the difference in their mobility under high and low electric fields. The addition of polar modifiers to the gas transporting the ions through a differential mobility spectrometer enhances the formation of clusters in a field-dependent way and thus amplifies the high- and low-field mobility difference, resulting in increased peak capacity and separation power. Observations of the increase in mobility field dependence are consistent with a cluster formation model, also referred to as the dynamic cluster-decluster model. The uniqueness of chemical interactions that occur between an ion and cluster-forming neutrals increases the selectivity of the separation, and the depression of lowfield mobility relative to high-field mobility increases the compensation voltage and peak capacity. The effect of a polar modifier on the peak capacity across a broad range of chemicals has been investigated. We discuss the theoretical underpinnings which explain the observed effects. In contrast to the result with a polar modifier, we find that using mixtures of inert gases as the transport gas improves the resolution by reducing the peak width but has very little effect on the peak capacity or selectivity. The inert gas helium does not cluster and thus does not reduce low-field mobility relative to high-field mobility. The observed changes in the differential mobility r parameter exhibited by different classes of compounds when the transport gas contains a polar modifier or has a significant fraction of inert gas can be explained on the basis of the physical mechanisms involved in the separation processes. This paper is the sixth in a series of papers presenting a body of work regarding the theory of operation and optimization of differential mobility and differential mobility spectrometry/mass spectrometry (DMS/MS) instrumentation. The first paper describes the most recent understanding of the theory of differential mobility separations.1 In the second paper we described the * To whom correspondence should be addressed. E-mail: [email protected]
Phone: (905) 660-9006 ext. 2254. Fax: (905) 6602623. † MDS Analytical Technologies. ‡ Sionex Corp. (1) Krylov, E. V.; Nazarov, E. G. Int. J. Mass Spectrom. 2009, 285, 149–156. 10.1021/ac902571u 2010 American Chemical Society Published on Web 02/01/2010
control and optimization of the important physical parameters of such a system including the analyzer geometry, transport gas flow control, and ion transmission efficiency.2 In the third paper we described novel electronics optimized to provide the asymmetric radiofrequency fields at the high voltages required for these devices and the effects of different waveforms on the resolution.3 In the fourth paper we described three important areas that need consideration to capitalize on the chemical processes that dominate a DMS separation.4 These include controlling the dynamic equilibrium of the clustering reactions with high concentrations of specific reagents, dealing with unwanted heterogeneous cluster ion populations that degrade the resolution and sensitivity, and fine control of the temperature and pressure, which influence the fundamental collision processes that lie at the core of the separation phenomena. In the fifth paper we described a biological application of this technology for small molecule biomarker detection.5 In classical ion mobility spectrometry (IMS) ions and ionneutral clusters drift under the influence of a static low electric field.6 When the composition of the transport gas favors the formation of clusters, the cluster ion distribution remains relatively unperturbed during the transit of the ion through the analyzer because the effective temperature of ion-neutral collisions remains constant. With the constantly varying electric field in the DMS analyzer, the effective temperature of ion-neutral collisions changes continuously during each period of the separation field waveform. One proposed model for the separation mechanism is the so-called clustering-declustering model. This model describes the cluster ion population to be continuously changing from a more to a less clustered state during the waveform synchronously with the effective temperature of ion-neutral collisions. Reclustering occurs rapidly because the high collision rate at atmospheric pressure maintains equilibrium.1,7-9 To simplify the (2) Schneider, B. B.; Covey, T. R.; Coy, S. L.; Krylov, E. V.; Nazarov, E. G. Int. J. Mass Spectrom., in press. (3) Krylov, E. V.; Coy, S. L.; Vandermey, J.; Schneider, B. B.; Covey, T. R. Nazarov, E. G. Rev. Sci. Instrum., in press. (4) Schneider, B. B.; Covey, T. R.; Coy, S. L.; Krylov, E. V.; Nazarov, E. G. Eur. J. Mass Spectrom. 2010, 16, 57–71. (5) Coy, S. L.; Krylov, E. V.; Schneider, B. B.; Covey, T. R.; Brenner, D. J.; Tyburski, J. B.; Patterson, A. D.; Krausz, K. W.; Fornace, A. J.; Nazarov, E. G. Int. J. Mass Spectrom., accepted for publication. (6) Revercomb, H. E.; Mason, E. A. Anal. Chem. 1975, 47, 970–983. (7) Krylova, N.; Krylov, E.; Eiceman, G. A.; Stone, J. A. J. Phys. Chem. A 2003, 107, 3648–3654. (8) Levin, D. S.; Vouros, P.; Miller, R.; Nazarov, E. G.; Morris, J. C. Anal. Chem. 2006, 78, 96–106.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
picture, the ion can be described as being in a clustered state during the low electric field portion of the separation field cycle and in an unclustered or less clustered state during the highfield portion of the waveform, this process repeating itself at the frequency of the applied separation field. The size of the molecule and the nature, number, and steric relationships of the functional groups all contribute to the free energy of clustering with particular gas-phase molecules, thereby imparting a high degree of chemical specificity to the separation process. As of yet, available data and theoretical analysis are inadequate to create an integrated model with predictive capabilities for the degree of clustering or the collision cross-sections of the resulting species. In this paper we expand upon our earlier studies4 of the chemical processes involved in a DMS/MS separation by demonstrating the influence of the composition of the transport gas on DMS separations for a diverse library of compounds and by providing the theory underpinning the results. Three general aspects of DMS separations are covered. First, the important metric of peak capacity is described, and the effect of the transport gas composition and other factors on the peak capacity across a broad chemical space is shown. Second, resolution and separation power in relation to the transport gas composition are explored. Third, the dominant physical models of the separation process are described: the dynamic clustering-declustering model,1,7 which appears to govern the separation process in the presence of polar clustering modifiers, and the rigid-sphere scattering model,1,10 which dominates in the absence of clustering with dry inert transport gases. Some light is shed on the physical basis of the three different types of field strength dependent behavior that different ions exhibit in different transport gases. These empirically observed behaviors can be understood in terms of the relative influence of the clustering and the rigid-sphere scattering processes in any particular situation. THEORY OF OPERATION Discussion of the data requires a clear definition of several parameters and scan modes used throughout the discussion. These will be defined in this section. Of central importance is the field dependence of the ion mobility, which describes the R function, a characteristic property of ion-neutral collisions that is directly related to conditions for DMS ion transmission. A definition of peak capacity and resolution in the context of DMS separations is also in order. Density-normalized electric fields (E/ N, Td) and additional DMS-specific parameters are defined here followed by the general instrumentation conditions and experimental details. Ion Mobility and r Function. An electric field of strength E causes ions to move through a dilute gas medium of density N with a velocity that is known to be proportional to the parameter E/N through the coefficient of mobility, K. The ion mobility coefficient can be written as a function of the mean ion-neutral collision energy, which can also be interpreted as a temperature called the effective temperature, Teff.1 This expression for the mobility constant encapsulates the fact that the ion-neutral collision energy is determined by the bulk gas temperature and electric field strength as shown in the following equation: (9) Pervukhin, V. V. J. Anal. Chem. 2008, 63, 1182–1190. (10) Wannier, G. H. Bell Syst. Tech. J. 1953, 32, 170–254.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
2π 1 µkTeff σ(Teff)
where q is the ion charge, µ is the reduced mass, k is Boltzmann’s constant, and σ(Teff) is the temperature-dependent transport cross-section. The dependence upon the reduced mass and cross-section have been exploited previously to vary the ion mobility.11 If the energy the ion gains from the electric field is small enough in comparison with the thermal energy, K is a constant and independent of E/N. However, with increasing values of E/N the mobility coefficient becomes dependent on the electric field through the R parameter as shown in the following equation:12
( NE ) ) K(0)[1 + R( NE )]
where K(0) is the mobility coefficient under low-field conditions, R(E/N) , 1 is a normalized function describing the field-mobility dependence (referred to as R dependence below), and E/N is the electric field in townsends (1 Td ) 10-17 V cm2). For instance, at 273.15 K and 101.325 kPa (N0 ) 2.687 × 1019 cm-3), 1 Td corresponds to 268.7 V/cm. The field-dependent part of the ion mobility called the R function forms the basis for DMS separation and is shown mathematically in the following equation: R(E) )
K(E) - K(0) K(0)
where R(E) is the R parameter function, K(E) is the high-field mobility, and K(0) is the low-field mobility. R is a dimensionless normalized difference between the high-field and low-field mobility constants. It is a characteristic property of the ion used to describe the field dependence of ion mobility under different field strengths and transport gas conditions. Differential mobility devices filter an ion population by passing them in a transport gas stream through a region with an oscillating field applied transverse to the ion motion. The applied waveform generates net transverse ion motion that depends on the difference between averaged high- and low-field mobility coefficients. The filter is tuned by applying an additional transverse dc field (compensation field) to modify the ion trajectory. The compensation field is generated by applying a dc offset potential (compensation voltage, CV) between the DMS cell electrodes to correct the trajectory for a given ion under the influence of the separation field. A scan of this voltage sequentially transmits ions with different mobility characteristics through the DMS cell. For the experiments described in this paper, CV was stepped in increments of 0.1 or 0.2 V and could be scanned over a range from -100 to +100 V across the 1 mm gap or set to a particular value within that range. The largest number of ions passes successfully through the field region (without contacting the walls and being neutralized) when the net transverse motion due to the total applied field is zero over one period of the field. The electric field (11) Barnett, D. A.; Ells, B.; Guevremont, R.; Purves, R. W.; Viehland, L. A. J. Am. Soc. Mass Spectrom. 2000, 11, 1125–1133. (12) Buryakov, I. A.; Krylov, E. V.; Nazarov, E. G.; Rasulev, U. K. Int. J. Mass Spectrom. Ion Processes 1993, 128, 143–148.
between the DMS electrodes (EDMS) can be written as shown in the following equation: EDMS(t) ) Sf(t) + C
where E(t) is the applied electric field, C is the compensation field, S . C is the amplitude of the separation field, and f (t) is a normalized function describing the waveform field. The dependence of the compensation field on the separation field is closely related to the R function as shown in the following equation: C)
-S〈Rf〉 1 + 〈R〉 + S〈R′f〉
where R′ is the derivative with respect to E/N.12 Thus, knowing the R function, the waveform f (t), and the amplitude of the separation field S, one can calculate the compensation field for various ions. Conversely, if the experimental dependence C(S) is known, it is possible to calculate the R dependence as has been done in this paper using the procedure described below. Calculating r Functions. For practical purposes, the DMS peak position may be simplified significantly by a series expansion12 which follows from fundamental considerations of the nature of the coefficient of mobility.13 The compensation field and field mobility dependence (R) can be expanded as shown in eqs 6 and 7, respectively, where both E and S are expressed in townsends. C(S) ) c3S3 + c5S5 + c7S7 + ...
R(E) ) R2E2 + R4E4 + R6E6 + ...
Substituting into eq 5, the R coefficients can be obtained as shown in the following equation for a three-term approximation: R2 ) R4 ) R6 )
〈f 〉 c5 + 3c3R2〈f 2〉 〈f 5〉 c7 + 5c3R4〈f 4〉 + 3c5R2〈f 2〉
where the separation waveform moments 〈f n〉 are defined as the integrated value of the nth power of the points of one cycle of the normalized waveform, mathematically depicted in the following equation:14 〈f n〉 )
∫ f (t) dt τ n
where τ is the waveform period. The generator used for the present experiments was a custom two-harmonic resonant generator2 that provided a bisinusoidal separation voltage with a fundamental frequency of 3 MHz and a peak magnitude from 0 to 3333 V (from 0 to 5000 V p-p) across the 1 mm gap. The 3 MHz component and the 6 MHz component were applied to (13) Mason, E. A.; McDaniel, E. W. Transport Properties of Ions in Gases; John Wiley & Sons: New York, 1988. (14) Guevremont, R. J. Chromatogr., A 2004, 1058, 3–19.
opposing electrodes, creating an asymmetric bisinusoidal field within the analyzer gap. The amplitude and phase ratio of the two harmonics were adjusted to provide the general waveform shape labeled as “Waveform #2” in Figure 3 of ref 15, with the difference that we report the absolute value of the waveform amplitude. With this configuration, positive ions with positive values for R (i.e., K(E) > K(0)) require a negative CV to be transmitted through the DMS analyzer. However, this behavior is simply an instrumental sign convention since reversing the polarity of the waveform would invert the sign of the required CV. The waveform moments used in these calculations were 〈f 2〉 ) 0.278, 〈f 3〉 ) 0.111, 〈f 4〉 ) 0.153, 〈f 5〉 ) 0.113, and 〈f 7〉 ) 0.102, in agreement with previously published values for the two harmonics.3 The R coefficients were then substituted back into eq 7 to determine the R functions for the experimental data. The R functions were further verified by comparing predicted compensation voltage values to the experimentally determined values at various separation fields. In the vast majority of cases, the agreement between the calculated and experimentally measured compensation voltage curves was better than 0.1%. Peak Capacity. Peak capacity, as used here, is analogous to the peak capacity in chromatography, qualitatively defined as the theoretical number of peaks that can be separated with a given resolution within a given analysis time for a wide range of compounds. In chromatography, the peak capacity depends on the peak width and the total elution time of a set of compounds. With DMS the analogous parameters would be the compensation voltage peak full width at half-height (W) and the CV range. The peak capacity for DMS can then be calculated using the following equation:
CVmax - CVmin Wav
where PC is the peak capacity, CVmax - CVmin is the voltage range within which a set of compounds transmit through the DMS cell, and Wav is the average observed for the peaks during a CV scan. The peak capacity is best calculated using a large set of compounds with widely varying properties and quantifies the voltage range available over which the components of a mixture can be spread. Resolution. The resolution in mobility is related but not identical to the peak capacity. Resolution describes the degree to which the data for a single compound can be confined within a narrow voltage or mobility range as shown in the following equation: R)
where R is the resolution, CV is the optimal voltage at which a compound transmits through a cell, and W is the full width at half-maximum for the observed peak. A mobility device that has a high resolution does not necessarily have a high peak capacity. With mobility, resolution as defined here gives no tangible indication of the separation power or the ability to separate two compounds that are physically similar, unlike the analogous fwhm (15) Purves, R. W.; Guevremont, R. Anal. Chem. 1999, 71, 2346–2357.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
definition of resolution in mass spectrometry. Peak capacity is a better, although qualitative and highly compound dependent, indicator of the separation power. The DMS peak width is determined by the geometry of ion trajectories in a planar differential mobility spectrometer in a straightforward way.16 The net result is that the empirical formula for peak width can be written as shown in the following equation:
1 d2 〈K〉 tres
where d is the gap, tres is the ion residence time in the analytical region, and K is the ion mobility coefficient averaged over one cycle of the waveform. Because their trajectory is more sensitive to the field, light molecules of high mobility appear in DMS with narrower peak widths. EXPERIMENTAL SECTION DMS devices require a transport gas flow to carry ions from the inlet through the analyzer to the outlet. For the experiments described in this paper, the composition of the transport gas was varied for each of the samples studied in this work and included nitrogen, nitrogen with varying amounts of helium, and nitrogen with 1.5% 2-propanol vapor added as a clustering agent (gas modifier). The polar modifier 2-propanol was selected for this study because previous experimentation showed it to be a particularly useful modifier for improving DMS separations.8 The concentration of modifier in the drift gas was selected to provide a good compromise between peak capacity and sensitivity as discussed in a previous paper.4 The transport gas flow was fixed at an optimal value as described below and further detailed in ref 2. All DMS/MS experiments were run at atmospheric pressure, with the local barometric pressure recorded at the time of the experiment. The barometric pressure was monitored during these experiments to correct17 both the separation voltage and the compensation voltage for fluctuations in the barometric pressure using a model 276 barometer with 0.1% accuracy (Setra, Boxborough, MA). The gap height for the DMS electrodes used in these experiments was 1 mm, and the length and width dimensions were 30 and 10 mm, respectively. The DMS coupling involved sealing the analyzer cell to the inlet orifice of the mass spectrometer, as described previously in ref 2. The transport gas flow through the cell (∼3 L/min) was drawn from the mass spectrometer curtain chamber by the vacuum drag through the inlet orifice. The curtain gas flow was maintained at approximately 3.7 L/min, providing approximately 0.7 L/min of curtain gas outflow from the curtain plate, the remainder serving as the transport gas through the DMS cell and inhaled by the mass spectrometer. Modifiers and/or helium were added to the curtain gas supply line, metered in to achieve the specified gas-phase concentrations. Liquid modifiers were dispensed using an HPLC pump with 1% flow accuracy (Shimadzu model 10A). At a 2-propanol flow of 180 µL/min mixing (16) Krylov, E. V.; Nazarov, E. G.; Miller, R. A. Int. J. Mass Spectrom. 2007, 76, 226. (17) Nazarov, E. G.; Coy, S. L.; Krylov, E. V.; Miller, R. A.; Eiceman, G. A. Anal. Chem. 2006, 78, 7697–7706.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
with a curtain gas flow of 3.7 L/min a 1.5% gas-phase concentration of modifier was produced. More details of the design of the DMS cell and the means utilized to interface to the mass spectrometer are described in ref 2. The mass spectrometer used for these experiments was a modified API 5000 triple-quadrupole system. All experimental data were acquired by electrospray ionization while infusing samples at 10 µL/min from a syringe pump (Harvard Apparatus, Syringe Infusion 22, South Natick, MA) into the standard Turbo V ion source, and no additional source heat was used for these experiments. A modified curtain plate was designed in-house to enclose the DMS cell within the curtain chamber. The curtain plate included a ceramic heat exchanger (Kyocera, Japan) as previously described.2 An extension flange was used to adjust the position of the source relative to the extended protrusion of the curtain plate when the DMS instrument was installed. A custom heater controller was designed in-house to maintain the transport gas temperature at ∼100 °C. All experiments were conducted in multiple-reaction monitoring (MRM) mode using optimized Q1/Q3 m/z values for the particular compounds. The dwell time was 10 ms, and the pause between mass ranges was 20 ms. Under these conditions, an entire cycle for three MRM transitions would require approximately 90 ms. Chemicals and Reagents. A positive ion mode test mixture that yields in electrospray 70 singly charged analytes with diverse chemical structures and a negative ion mode test mixture that results in 24 different singly and multiply charged ions were prepared for these experiments. The list of test chemicals is provided in Tables 1 and 2 with other relevant information. The chemical formulas are also provided in Tables 1 and 2 for each of the compounds used in these studies. These compounds were specifically chosen to span a wide range of chemical space, including diversity in terms of structures, polarity, and acid/base properties. Solutions of standards were diluted in solvent comprising 50/ 50 methanol/water with 0.1% formic acid (Fisher Scientific, Nepean, Ontario, Canada). Safety Considerations. High voltages are required to generate the asymmetric waveforms necessary for DMS operation. Proper interlocks and shielded cables should be used to prevent accidental contact. Many of the chemicals used for these studies are hazardous and should only be used with the safety precautions listed in the relevant MSDS documents. RESULTS AND DISCUSSION Peak Capacity. Peak Capacity and the Effect of the Transport Gas Composition. As defined in the Experimental Section, the peak capacity is a metric to provide some measure of the number of compounds that could potentially be separated in a single CV scan. The data in Figures 1 and 2 demonstrate the effect of the gas composition on the peak capacity across a broad range of chemical space. Figure 1 shows three positive ion analyses for the 70-compound mixture of chemical entities listed in Table 1 taken under different transport gas conditions. Compared to the CV scans in nitrogen (Figure 1A) and helium-doped nitrogen (Figure 1C), the presence of a polar modifier in the transport gas (Figure 1B) shifts the CV values for all compounds toward negative values and spreads them over a wider range. The peak capacity, calculated according to
Table 1. List of Compounds Contained in the Mixture Used for the Positive Ion Separation Shown in Figure 1 Which Include Examples of Bases, Neutrals, and Quaternary Amines Spanning a Range of 112-735 m/za sample
SHe/SN2 at max SV
histamine methylhistamine melamine ammelide leucine acetaminophen ephedrine caffeine nirvanol minoxidil butabarbital mephenytoin bucetin acyclovir naproxen norfentanyl bentazon methoxymephenytoin lamotrigine tramadol tolbutamide nordiazepam clenbuterol venlafaxine imipramine diazepam morphine benzoylecgonine trimipramine dianabol carboxytolbutamide cocaine quinoxyfen phenylbutazone nifenazone warfarin benoxinate cannabinol safranin orange ranitidine bromazepam chlorprothixene clonazepam oxycodone oxfendazole fendiline pamaquine oxyphenbutazone quinine citalopram midazolam 6-acetylmorphine piroxicam buscopan prednisolone hydrocortisone tamoxifen trazodone haloperidol lovastatin beclomethasone verapamil morphine glucuronide testosterone glucuronide sildenafil ketoconazole leucine enkephalin reserpine bromocryptin erythromycin
112.0 126.0 127.1 129.1 132.1 152.2 166.1 195.1 205.3 210.1 213.2 219.1 224.1 226.1 231.1 233.2 241.1 249.2 256.0 264.2 271.1 271.1 277.1 278.2 281.2 285.1 286.1 290.1 295.2 301.1 301.1 304.1 308.0 309.1 309.1 309.1 309.2 311.2 315.1 315.2 316.1 316.1 316.1 316.1 316.1 316.2 316.2 325.1 325.2 325.2 326.1 328.3 332.1 360.1 361.1 363.2 372.1 372.2 376.1 405.2 409.1 455.3 462.1 465.1 475.2 531.1 556.4 609.2 654.1 735.0
C5H10N3 C6H12N3 C3H7N6 C3H5N4O2 C6H14NO2 C8H10NO2 C10H16NO C8H11N4O2 C11H13N2O2 C9H16N5O C10H17N2O3 C12H15N2O2 C12H18NO3 C8H12N5O3 C14H15O3 C14H21N2O C10H13N2O3S C13H17N2O3 C9H7Cl2N5 C16H26NO2 C12H19N2O3S C15H12ClN2O C12H18Cl2N2O C17H28NO2 C19H25N2 C16H14ClN2O C17H20NO3 C16H20NO4 C20H27N2 C20H29O2 C12H17N2O5S C17H22NO4 C15H9Cl2FNO C19H21N2O2 C17H17N4O2 C19H17O4 C17H29N2O3 C21H27O2 C20H19N4 C13H23N4O3S C14H10BrN3O C18H19ClNS C15H11ClN3O3 C18H22NO4 C15H14N3O3S C23H26N C19H30N3O C19H21N2O3 C20H25N2O2 C20H22FN2O C18H14ClFN3 C19H22NO4 C15H14N3O4S C21H30NO4 C21H29O5 C21H31O5 C26H30NO C19H23ClN5O C21H23ClFNO2 C24H37O5 C22H29ClO5 C27H39N2O4 C23H28NO9 C25H37O8 C22H31N6O4S C26H28Cl2N4O4 C28H38N5O7 C33H41N2O9 C32H40BrN5O5 C37H68NO13
0.42 1 1 0.32 1 0.32 1 0.01 0.007 1 1 0 1 1 0.004 1 0 0.007 1 0.76 0.09 1 1 0.82 0.67 1 1 1 0.65 0.48 0 0.83 1 1 0.45 0.82 0.74 0.01 1 0.71 1 0.90 1 0.82 0.57 1 0.73 1 0.75 0.56 1 1 1 0.81 0.65 0.05 0.88 0.70 0.76 0.25 0.52 0.92 1 0 0.84 0.68 0.92 0.92 0.44 0.55
0 0.02 0.02 0 0 0.02 0 0.04 0.14 0.25 0.16 0.14 0.15 0.01 0.08 0.23 0 0.37 0.34 0.16 0.41 0.39 0.32 0.52 0.40 0.42 0.84 0.81 0.48 0.31 0.69 0.44 0.56 0.75 0.83 0.57 0.75 0.77 0.65 0.55 0.45 0.62 0.68 0.67 0.82 0.73 0.65 0.6 0.71 0.75 0.49 1 0.58 0.73 0.52 1.12 0.82 0.98 0.93 0 0 0.75 1.2 1.16 0.83 0.89 1.15 1.12 1.14 0.98
0.6028 (2) 0.5285 (3)
-0.0404 -0.0390 (13)
0.2579 0.4282 (4) 0.2966 0.3504 0.2400
0.0030 (9) -0.0157 (10) -0.0309 (12) -0.0289 -0.0263
0.1702 0.2437 (6)
0.1096 (7) 0.1645
The relative signal under conditions of different transport gas compositions is shown in columns 4 and 5. An entry value of 0 means that no ions were observed for the compound. Columns 6-8 are the R parameters for the maximum field data shown in Figure 10. Numbers in parentheses indicate the specific trace from Figure 10.
eq 10, increases from 11 in helium-doped nitrogen to 13 in nitrogen and to 44 in 2-propanol-modified nitrogen. Figure 2 is the same experiment conducted in negative ion mode with a different set of 24 compounds composed primarily
of strong and weak acids as listed in Table 2. Similar to the positive ion data, the peak capacity is amplified with the use of a clustering agent in the transport gas. The peak capacities calculated from these data were 8.0, 8.4, and 22.4 for nitrogen transport gas, the Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
Table 2. List of Compounds Contained in the Mixture Used for the Negative Ion Separation Shown in Figure 2 Which Include Singly and Multiply Charged Acids Spanning a Range of 129-825 m/za sample
SHe/SN2 at max SV
5-fluorouracil aspartic acid glutamic acid hexanoylglycine ibuprofen naproxen amaranth sulfamethazine acid black 1 sulfonic acid efavirenz acid orange furosemide fluorescein estradiol sulfate acid red 88 acid red 151 aztreonam taurocholic acid fosinopril bromophenol acid yellow 151 dimer digitoxin digoxin
-129.1 -132.0 -146.1 -172.1 -205.1 -229.0 -268.3 (2-) -277.1 -285.3 (2-) -301.4 (2-) -314.3 -327.3 -329.0 -331.1 -351.2 -377.3 -431.3 -434.0 -514.3 -562.3 -669.1 -807.3 -809.5 -825.4
C4H2FN2O2 C4H6NO4 C5H8NO4 C8H14NO3 C13H17O2 C14H13O3 C20H13N2O10S3 C12H13N4O2S C22H14N6O9S2 C28H14N2O10S2 C14H8ClF3NO2 C16H11N2O4S C12H10ClN2O5S C20H11O5 C18H23O5S C20H13N2O4S C22H15N4O4S C13H16N5O8S2 C26H44NO7S C30H45NO7P C19H9Br4O5S C32H31N8O10S2Fe C41H63O13 C41H63O14
0 0 0 0.1 0 0 0.05 0.35 0.1 0.16 0.41 0.73 0.64 0.45 0.92 0.72 0.90 0.81 1.20 0.76 0.71 0.42 0.75 0.91
0.4109 (1) 0.4340 0.3973
-0.0247 (11) -0.0280 -0.0191
-0.0427 -0.0333 (17)
0.1695 0.1492 0.1885 -0.0189 0.0944
-0.0318 -0.0206 (15) -0.0307 -0.0315 -0.0226
0.0913 0.0090 -0.0211 0.0394 -0.0073 -0.0194 -0.0214 -0.0178
-0.0153 (14) -0.0357 -0.0395 (18) -0.0358 -0.0354 -0.0243 -0.0288 -0.0288 (16)
a The relative signal with helium in the transport gas is shown in column 4. An entry value of 0 means that no ions were observed for the compound. Columns 6-8 are the R parameters for the maximum field data shown in Figure 10. Numbers in parentheses indicate the specific trace from Figure 10.
mixture of nitrogen and helium, and the nitrogen transport gas modified with 2-propanol, respectively. The diversity of chemical species used in these two experiments in both positive and negative ion mode demonstrates the general nature of these phenomena across a broad chemical space and independence from ion polarity. The dramatic shifts in differential mobility and changes in peak capacity when inert versus polar transport gases are used suggest that different separation mechanisms occur. Other types of modifiers such as water, other alcohols, and halogenated hydrocarbons show effects qualitatively similar to those of 2-propanol.4 The separation theory rationalizing these experimental results is described in the final section of this paper dealing with separation mechanisms. Effect of the Transport Gas Composition on the Effective Gap. The physical distance or gap between the DMS electrodes that form the walls of the chamber through which the ions traverse establishes the maximum radial distance an ion can travel during any single period of the separation waveform. The voltage amplitudes and frequencies of the separation waveform are chosen, for a specific electrode gap width, to maximize the probability that an ion will undergo several oscillations before striking the electrode and provide ample time for the trajectory of the ion to be corrected by the compensation field. Gap dimensions and SV frequencies are typically fixed values for a given instrument because of design constraints.2,3 The concept of the effective gap16 was conceived to define the degree to which the physical gap is effectively reduced by the oscillation amplitude and is determined in the following equation:
SKτ 〈|f |〉 2
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
where g is the effective gap and d is the actual gap. In eq 13 all parameters except for ion mobility are controlled by the instrument design. The magnitude of the mobility of a particular ion in a particular transport gas will reduce the effective gap proportionally. The distance that an ion travels during each period of the waveform is affected by the masses and cross-sections of the ion and transport gas as well as the interactions between them. Ions travel further through low-mass nonpolar transport gases such as helium during a single waveform period because the mobility for a particular ion increases in light gases. Low-mass ions that have inherently high mobilities travel further through these gases and will strike the electrodes under electric field conditions that provide optimal separations for higher mass ions. In the extreme condition, the effective gap can be zero for low-mass ions, resulting in complete elimination from the transport gas stream. The relationship among ion mobility, gas mass, and ion mass scales approximately according to the following equation:
m1m2 m1 + m2
where K is the ion mobility constant, m1 is the mass of the ion, and m2 is the mass of the transport gas. Peak capacity will be affected with the use of gases such as helium because low-mass ions can be lost to the walls of the DMS analyzer for the reasons described above, particularly when high separation fields are used. The net effect is similar to reducing the gap dimensions. Peak capacity is reduced because the range of chemical species that can be separated and observed in a single analysis is restricted, a particularly important consideration when the goal of an analysis is the identification of unknown components
Figure 1. Separation of a 70-compound mixture with various transport gas conditions: (A) nitrogen transport gas, (B) nitrogen with 1.5% 2-propanol, (C) nitrogen gas with 44% helium. MRM transitions were monitored for each compound with a dwell time of 10 ms and total cycle time of 2.1 s. The separation field was 132 Td, and under these conditions the number of compounds observed was 69 for the data presented in (A). Plots B and C only contain data for the compounds that maintained greater than 5% of the original signal observed with nitrogen transport gas. This corresponded to 60 compounds and 58 compounds for the transport gas comprised of nitrogen with 2-propanol (B) and nitrogen with helium (C), respectively. The presence of 44% helium in the transport gas eliminated the signal for all compounds with m/z below 195 for the data presented in (C). In the majority of cases, a single MRM peak was observed for the compounds; however, due to the complexity of the mixture, there were a few cases where two peaks were observed in a single MRM transition. An example of this is the peak at -75 V, which was an additional peak observed in the MRM trace for melamine.
in a sample whose mobility characteristics are not determined a priori. Of the 70 positive ion compounds analyzed, 18 showed a greater than 5-fold loss due to this effect when a transport gas containing 44% helium was used compared to pure nitrogen (Table 1). In addition, all compounds with m/z below 195 were lost to the electrode walls when helium was added to the transport gas under these conditions. Of the negative ion compounds analyzed, 9 of 24 showed a 5-fold or greater intensity loss using 44% helium
Figure 2. Separation for a 24-compound mixture in negative ion mode: (A) nitrogen transport gas, (B) nitrogen with 1.5% 2-propanol, (C) nitrogen with 44% helium. MRM transitions were monitored for each compound with a dwell time of 10 ms and a pause between mass ranges of 20 ms for a total cycle time of 750 ms. The separation field was 115.5 Td, and under these conditions the number of compounds observed was 23 for the data presented in (A). Plots B and C only contain data for the compounds that maintained greater than 5% of the original signal observed with nitrogen transport gas. This corresponded to 24 compounds and 19 compounds for the transport gas comprised of nitrogen with 2-propanol (B) and nitrogen with helium (C), respectively.
compared to pure nitrogen transport gas (Table 2). Comparing the data generated with a helium/nitrogen mixture to the data with nitrogen eliminates those losses that are due to ion chemistry effects, to be described in the next section. The losses correlate strongly with ion mobility, as evidenced by dramatic losses for low-m/z ions and almost no losses for high-m/z ions. The effect on low-mass ions when the percentage of helium is increased is shown in Figure 3A for a subset of six compounds ranging from m/z 112 to m/z 556. The intensity of low-mass ions drops off as a result of them striking the walls due to higher mobility. When the separation field is increased (Figure 3B,C), the losses become greater. In general, higher fields provide greater resolution/separation power with DMS because the difference between the low- and high-field mobilities is amplified. Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
Figure 3. Normalized intensity plots for 6 ions from the 70-compound mixture with increasing helium content in the transport gas. The separation field was 99.0, 115.5, and 132 Td for the data present in panels A, B, and C, respectively. The ions are listed in order of increasing molecular weight and were (1) histamine (m/z 111.6), (2) leucine (m/z 132), (3) caffeine (m/z 195), (4) mephenytoin (m/z 219), (5) cocaine (m/z 304), and (6) leucine enkephalin (m/z 556).
Access to the high-voltage conditions is limited by the use of helium and other low molecular weight transport gases unless one is willing to sacrifice low-mass ions, essentially reducing the peak capacity or the range of molecular species that can be analyzed in a single run. Effect of the Transport Gas on the Ionization Efficiency. The concept of peak capacity attempts to quantify the range of chemical species separable under a given set of conditions. We have discussed the enhancement in peak capacity that the use of transport gas modifiers provides as well as the loss of peak capacity when using light transport gases. Physical phenomena that are not directly related to the separation process can restrict the chemical space accessible under a given set of separation conditions. The loss of ions due to competing ion-molecule reaction channels is one of them, particularly when one considers the use of polar modifiers in the transport gas. The principles of gas-phase ion chemistry apply. When the modifier added to the transport gas has gas-phase basicity greater 1874
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
than that of the analyte ion, the analyte ion current will be depleted in positive ion mode. When the modifier has gas-phase acidity greater than that of the analyte ion, the analyte ion current will be depleted in negative ion mode. With the compound set and experimental conditions shown in Figure 1, 10 out of 70 compounds were depleted by 20-fold or greater when using the 2-propanol modifier. However, analytes with higher proton affinities such as leucine (∼917 kJ/mol) and ephedrine (>965 kJ/mol) were not significantly affected by the addition of 2-propanol (∼798 kJ/mol) to the transport gas flow.18,19 For the negative ion mode experimental conditions shown in Figure 2, 2-propanol did not significantly affect the ion intensities. Because the gas-phase reactivity of ions relative to neutral modifiers can be reasonably estimated from chemical structures and database values, in practice this restriction of peak capacity can be managed and the enhancement in peak capacity afforded by the use of modifiers can be leveraged. Under conditions where the compounds are unknown, the possible loss of ions from ion-molecule reactions must be considered. Proton affinities are available for most volatile liquids considered for use as a modifier as well as for many chemical species from various online databases. For targeted analyses adjustment of the gas-phase ion chemistry of the modifier relative to the analyte can be used to advantage to further reduce the chemical noise surrounding high proton affinity analytes. A modifier can be chosen with lower proton affinity than the analyte, but higher than at least a portion of the chemical noise. In this case, the background reduction would be due to a combination of DMS filtering and transfer of charge from background ions to the modifier. From the set of 94 compounds analyzed here, the ion current for two compounds, bentazon in positive ion mode and naproxen in negative mode, were reduced in intensity under some conditions of transport gas composition and separation voltage that cannot be explained by either ion depletion due to the gas-phase ion chemistry or excessive mobility and discharging on the walls. Both compounds have structures that favor fragmentation and produce product ions at low collision energies in a tandem MS experiment. Both compounds fragmented to the point of no remaining ion current under conditions of dry inert transport gases and separation fields in excess of 104 Td. The addition of polar modifiers significantly reduced this fragmentation but did not eliminate it completely. The energy imparted from the collisions is absorbed by the ion-neutral cluster bonds. Fragmentation of covalent bonds at atmospheric pressure from heating caused by the strong separation field has been observed and described.20 Fragile compounds such as acyl glucuronides will fragment under similar conditions described above, but like that of bentazon and naproxen, the fragmentation can be significantly reduced in the presence of clustering agents. The data presented in Figure 1 and Table 1 were generated with a separation field of 132 Td, and under these conditions, bentazon fragmented regardless of the presence or absence of polar modifiers, leading to no observable (18) Lee, V. W. M.; Li, H.; Lau, T.; Guevremont, R.; Siu, K. W. M. J. Am. Soc. Mass Spectrom. 1998, 9, 760–766. (19) Matsumura, S.; Takezawa, H.; Isa, K. J. Mass Spectrom. Soc. Jpn. 2003, 51, 196–200. (20) Kendler, S.; Lambertus, G. R.; Dunietz, B. D.; Coy, S. L.; Nazarov, E. G.; Miller, R. A.; Sacks, R. D. Int. J. Mass Spectrom. 2007, 263, 137–147.
Figure 4. Comparison of the separation of 3 selected ions from the 70-compound mixture, demonstrating the differences in peak position and peak fwhm observed when operating with (A) nitrogen transport gas, fwhm ≈ 1.87 V, (B) nitrogen with 1.5% 2-propanol, fwhm ≈ 2.13 V, and (C) nitrogen with 44% helium transport gas, fwhm ≈ 1.47 V. The ions are (1) dianabol, (2) benoxinate, and (3) clenbuterol, and the separation field is 132 Td.
signal. The data presented in Figure 2 and Table 2 were generated with a separation field of 115.5 Td, and under these conditions, naproxen fragmented completely in the absence of the polar modifier. In the presence of nitrogen modified with 2-propanol transport gas, fragmentation only reduced the ion current for naproxen by ∼25%. Resolution and Separation Power. Effect of Transport Gases. As will be discussed further the ability to separate two components (separation power) with DMS is difficult to predict apriori because the separation mechanism is driven by the interactions of an ion and its clusters with the background gas. Specificity is gained largely from the chemical properties of an ion in relation to its surroundings. As such, resolution, as defined in the Experimental Section, gives little tangible indication of whether or not a separation will occur. Cases in point are the data shown in Figure 4. From eq 11, the highest resolution was obtained with helium in the transport gas (13.6), intermediate with nitrogen (5.3), and lowest with
nitrogen modified with 2-propanol (4.7), as measured on the dianabol peak, but separation was the greatest in the lowest resolution case. The narrowing of peaks in the presence of helium is very much in accordance with our discussion of the mobility coefficient (eq 1) and of resolution (eq 12). In agreement with these equations, the width is smallest in the He mixture because of the higher mobility in He and largest in 2-propanol because of the reduced mobility with strong ion-neutral interactions. Mobility is increased in helium because the reduced mass for the ion-helium system is low (eq 1) and because the polarizabilty of He is lower than that of N2 (0.2 and 1.7 Å3, respectively).21 Peaks further increase in width (mobility decreases) in the presence of polar modifiers because of additional long-range interactions that increase the cross-section, σ, and clustering, which also increases the cross-section. These observations are left at a qualitative level because of the heterogeneous nature of electrospray conditions. Despite the lower resolution, an improvement in selectivity is observed with the use of modifiers. The peak capacities in these three cases were calculated to be 4.1 in helium-doped nitrogen, 2.7 in nitrogen, and 21.6 in 2-propanol-modified nitrogen, which reflects the improvement to the separation more realistically than the resolution value. An improvement in separations was observed in almost all cases for the compounds shown in Figures 1 and 2. The chemical specificity inherent in the formation and dissociation of clusters of different sizes, shapes, and internal bond strengths is the overriding determinant for whether a separation will occur. However, there were a few cases where compounds that did separate using nitrogen or nitrogen/helium transport gas did not separate with the 2-propanol modifier. Examples were acetaminophen and melamine as well as quinine and piroxicam. The dominant separation mechanism changes when polar modifiers are added to the transport gas, and because separations are chemically specific under clustering conditions, this adds an additional axis in a multidimensional separation space. There was one example where two compounds were not separated under any of the transport gas conditions, prednisolone and morphine glucuronide. Separation Theory. Clustering Model. The theory that underlies the behavior of ions in the presence of polar transport gases is best understood in terms of reversible cluster formation, the “clustering” model.1 The asymmetric waveform used in DMS varies between high-field and low-field regimes at a rate in the megahertz range. Ions are clustered during the low-field portion of the waveform and undergo declustering due to heating during the high-field portion of the waveform. This variation can be modeled as a field-dependent effective temperature synchronous with the separation field because of the high collision frequency at atmospheric pressure. When ion-neutral clustering is occurring to a significant extent, the time-varying effective temperature can cause a time-varying change in the ion size and, therefore, a synchronous change in the ion mobility cross-section. The extent of clustering and the relative change in mobility due to clustering dictates the magnitude of the CV, with increased clustering driving the CV voltage toward more negative values in our sign convention established by our arrangement of voltages on the electrodes. (21) Computational Chemistry Comparison and Benchmark DataBase. http:// cccbdb.nist.gov/.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
During clustering the R parameter, as described earlier, is moved toward more positive values in all instrument configurations independent of the voltage arrangement. This reversible cluster formation during each cycle of the separation waveform provides a method for the amplification of differential mobility effects in DMS. Because the change in cluster number occurs between the low- and high-field regimes during the separation waveform, with the low-field mobility reduced more than the high-field mobility, the differential mobility is greatly enhanced (relative to that of the nondoped system). Hard-Sphere Scattering Model. The hard-sphere scattering model has been a reference point throughout the history of ion mobility studies. It was the basis of some of the earliest work by Wannier,22 has been the subject of several theoretical papers during the past decade, and, furthermore, has formed the basis of ion mobility computational software packages such as Mobcal (for more background, see ref 23 and references therein). Hardsphere scattering is computationally tractable and provides reasonable agreement with experiment, especially for low-field mobility coefficients under ideal conditions. In one recent example, the mobilities of 50 aromatic cations were studied and compared to hard-sphere calculations, with good results that aided in the assignment of conformers.24 It is rather more difficult to predict the field dependence of the ion mobility because of the importance of long-range (chemical) forces in determining the change of the mobility with the field. When long-range attractive interactions are strong (for example, ion-dipole interactions of an ion interacting with a polar gas), the ion mobility will increase with the field, while, for systems dominated by pure hard-sphere interactions, the ion mobility will decrease with the field. Intermediate interactions, such as the polarization of a neutral by an ion and Leonard-Johnson 12-4 potentials with an added repulsive hard-sphere core, can cause intermediate behaviors, with the mobility increasing and then decreasing. At field strengths where the hard-sphere behavior is expected to dominate, the differential ion mobility coefficient is expected to decrease with the field. This essentially universal result is illustrated in the following equation, where R can be shown to decrease with the field:1 RHSS(Teff) )
K -1f K0
T -1) Teff
3kT -1 (3kT + MK2E2) (15)
Thus, hard-sphere scattering corresponds to R(E) being negative and decreasing. Physically, the random-walk nature of hard-sphere collisions prevents the ion velocity from increasing purely linearly with the field, causing the ion mobility coefficient to fall off with the field strength. As a result of these general considerations, the hard-sphere model is expected to work well for ions in helium, both for lowfield mobility and for the field dependence, and will usually predict mobility coefficients falling with the field/effective temperature. Mobility in helium is so much higher than in polarizable gases (22) Wannier, G. H. Bell Syst. Tech. J. 1953, 32, 170–254. (23) Shvartsburg, A. A.; Mashkevich, S. V.; Baker, E. S.; Smith, R. D. J. Phys. Chem. A 2007, 111, 2002–2010. (24) Beitz, T.; Laudien, R.; Loehmannsroeben, H.; Kallies, B. J. Phys. Chem. A 2006, 110, 3514–3520.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
or in polar gases that, when helium behavior is being tested, small admixtures of polar molecules can dominate the ion-helium interaction. Mobility in mixtures is predicted by Blanc’s law and shows that small amounts of polar gases can prevent the expected hard-sphere mobility coefficients from being observed. For instance, the comprehensive drift gas IMS results from the Hill group25 scale for each ion as expected with the reduced mass for several drift gases, but not to the full extent predicted for helium, while low-pressure, fully declustered experiments by Bierbaum and Leone26 do scale as expected, showing the very high mobility in helium of 11.8 cm2/(V · s) for C6H6+. This polar-nonpolar mixing effect has also been examined for t-C4H9+ in ref 27. As another example of the applicability of the hard-sphere model under highly controlled conditions, calculations of the mobility of cluster ions drifting in helium and in nitrogen were made using hard-sphere and polarizability interactions in ref 28. For nitrogen, which has a large permanent quadrupole moment and significant polarizability, deviations from hard-sphere predictions are seen to occur when compared to helium. Regardless of the details of the experimental conditions, the hard-sphere model should be qualitatively relevant to admixtures of helium to the N2 drift gas, according to Blanc’s law. Because of the absence of long-range interactions, this model predicts mobility decreasing with the field, corresponding to CV values becoming more positive in our sign convention. In summary, the two ion-drift gas interaction mechanisms are highly orthogonal. The clustering mechanism is dominated by gas-phase ion-neutral chemical effects that decrease low-field mobility coefficients more than high-field mobility coefficients, making CV dramatically more negative and sensitive to chemical interactions. The rigid scattering model is dominated by the shortrange scattering effects during ion-neutral collisions. Because of the lack of long-range terms and of chemical interactions, CV values become more positive without any increase in chemical specificity. Classifying the Field Dependence of R. As far back as 1992 three distinguishable types of ion mobility behavior were observed and classified in DMS, each exhibiting different trends in the mobility coefficient and R parameter as the SV is increased.1,3,12,15,29,30 The mobility has been observed to increase strongly with the field, to increase and then decrease with the field, or to decrease with the field as shown in Figure 5. Because ion-neutral interactions have a hard repulsive core that becomes important at high energies, the mobility and R must eventually decrease with the field, although that field may be difficult to apply experimentally, and fragmentation or charge loss may dominate at very high energies, preventing the eventual decrease from being observed. Different nomenclature has been assigned to each behavior by (25) Steiner, W. E.; English, W. A.; Hill, H. H., Jr. J. Phys. Chem. A 2006, 110, 1836–1844. (26) Krishnamurthy, M.; de Gouw, J. A.; Bierbaum, V. M.; Leone, S. R. J. Phys. Chem. 1996, 100, 14908–14913. (27) Haber, L. H.; Husband, J.; Plenge, J.; Leone, S. R. Chem. Phys. Lett. 2004, 384, 219–223. (28) de Gouw, J. A.; Krishnamurthy, M.; Bierbaum, V. M.; Leone, S. R. Int. J. Mass Spectrom. Ion Processes 1997, 167/168, 281–289. (29) Eiceman, G. A.; Karpas, Z. Ion Mobility Spectrometry, 2nd ed.; CRC Press: Boca Raton, FL, 2004. (30) Shvartsburg, A. A. Differential Ion Mobility: Non-linear Ion Transport and Fundamentals of FAIMS; CRC Group, Taylor and Francis LLC: Boca Raton, FL, 2008.
Figure 5. Three types of R behavior. The general trends are R monotonically increasing (type A), R monotonically decreasing (type C), and intermediate behavior with R increasing at low separation fields and decreasing at high separation fields (type B).
different authors. The three behaviors (strongly increasing, increasing and then decreasing, and decreasing) are labeled by Purves et al.15 as A, B, and C and by Shvartsburg30 in his section 2.2.2 as 1, 1, and 2. The latter description combining types A and B acknowledges the theoretical understanding that mobility should decrease at high field even if the ions cannot survive those conditions. The first description is more applicable to experimental results. The A, B, and C notation has been used more frequently in the literature and is also used here. There is an evident connection between mobility type and the ion-neutral interaction mechanism dominant at a particular field amplitude, with type C behavior observed when hard collisions dominate (at low field for nonpolar systems and at very high field for most systems) and types A and B when clustering and long-range forces are important. Our data demonstrate that there is a close relationship between this mobility classification and the interaction mechanisms at play between ions and the transport gas environment. For molecular systems, we find that these interactions are in turn predominantly controlled by the degree to which an ion is clustered or adducted to neutral polar or nonpolar molecules. Because of the complexity of interactions between ions and mixtures of polar and nonpolar neutrals at atmospheric pressure, this relationship has been largely neglected in previous work in favor of analysis of simpler, computationally accessible, models. Because of the startling enhancement to the resolving power of these chemical effects in planar DMS instrumentation, we are exploring them in detail in this paper, building on a previous paper.4 We find that types A and C represent limits (extremes) where one mechanism dominates and type B is observed under conditions such that a mixture of mechanisms is apparent. Type A: Strongly Increasing Mobility. Figure 6A shows CV scan data with four different transport gas conditions for the molecule norfentanyl, each scan operated at six different field strengths. What is readily apparent is that the CV values shift negatively in the presence of a polar modifier and positively in the presence of dry, nonpolar transport gases and the shifts increase in magnitude with increasing separation field. The data in Figure 6 are used to calculate the R plots in Figure 7 as described in the Experimental Section. Type A behavior is observed in the case of polar modifiers, showing the R function to become increasingly positive with increasing SV. Higher fields reduce clustering, accentuating the difference in the mobility of
Figure 6. CV scans for norfentanyl (MW ) 233) under four different transport gas conditions and six different field strengths for each transport gas. The transport gas composition was (A) nitrogen with 1.5% 2-propanol, (B) nitrogen, (C) nitrogen with 28% helium, and (D) nitrogen with 37% helium. The six separation fields were (i) 0 Td, (ii) 69 Td, (iii) 87 Td, (iv) 104 Td, (v) 121 Td, and (vi) 138 Td. The data are normalized to illustrate the peak position more clearly. The absolute signals are within a factor of 2 across all transport gas compositions and separation voltage settings.
the ion under low- and high-field conditions. The slope of this curve reflects the peak capacity which is much greater for chemically dominated separations (type A) than for physically dominated separations (type C). Type C: Decreasing Mobility. Under transport gas conditions where clustering and adduct ion formation are minimized or nonexistent, the behavior of the norfentanyl ion shifts to a type C classification. The R curve plots, calculated from the data in Figure 6B-D, are constructed in Figure 7, plots ii-iv. Under high-field conditions the mobility is decreasing relative to the low-field value. In high fields and in the absence of clusters, the rigid-sphere scattering mechanism becomes dominant, as we have discussed above. At high interaction energies the short-range repulsive potential becomes important, resulting in a decreasing mobility consistent with eq 15. With increasing concentrations of helium the R function continues to become more negative, again consistent with the rigid-sphere mechanism. In contrast to the situation Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
Figure 7. R plot for norfentanyl under four different transport gas conditions generated from the data in Figure 6: (i) nitrogen with 1.5% 2-propanol, (ii) nitrogen, (iii) nitrogen with 28% helium, and (iv) nitrogen with 37% helium.
with modifiers present, the separation process and the selectivity achieved are less under these conditions, since they are controlled solely by geometric cross-sections with no influence from chemical effects. Type B: Increasing and Then Decreasing Mobility. The data from an experiment similar to that for which the data are shown in Figure 6 are shown in Figure 8 for methylhistamine, with the corresponding R plot constructed from those data shown in Figure 9. Type A behavior dominates with polar modifiers present as seen in Figures 8A and 9, plot i, consistent with the clustering model of ion separation. With inert gases the bimodal R parameter curve typical of type B ions is observed, as best seen in Figure 9B, plots ii-iv. With low SV amplitudes a positive trend in R is observed followed by an inflection and marked negative trend at higher separation fields. This bimodal behavior can be explained by the presence of trace clustering agents in the otherwise dry gases that cluster with susceptible ions, typically low in molecular weight, where a single cluster adduct can represent a large relative change in mobility. Under low field strengths type A behavior and the clustering mechanism drive the separation. As the field strength increases, type B behavior and the rigid-sphere model dominate. With these cases, the concentration of the clustering species may be very low and during the high-field portion of the waveform the clusters are destroyed and not re-formed. This effect could occur as the result of interaction with residual species from the electrospray process. The negative R trend is stronger in helium/nitrogen mixtures than in nitrogen, once again consistent with the hard-sphere mechanism dominating under high SV amplitudes. Type B behavior results from a mixed mechanism situation with the clustering model dominating at low voltages and the rigid-sphere model at high voltages. Chemical Specificity in the R Parameter. When R plots are generated with different transport gas compositions for a large number of compounds of diverse chemistries, as shown in Figure 10, several generalizations become apparent. First, all separations fall into one of three categories, each of which can be rationalized on the basis of the clustering model, rigid-sphere model, or mixtures of both as described in the previous sections. In the presence of polar modifiers compounds are predominantly type A and separate according to the clustering model (Figure 10A). In the presence of dry transport gases some ions exhibit mixed mode separations (Figure 10B) and others separate exclusively according to the rigid-sphere model (Figure 1878
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
Figure 8. Methylhistamine (MW ) 125) data under four different transport gas conditions and six different field strengths for each transport gas. The transport gas composition was (A) nitrogen with 1.5% 2-propanol, (B) nitrogen, (C) nitrogen with 28% helium, and (D) nitrogen with 37% helium. The six separation fields were (i) 0 Td, (ii) 52 Td, (iii) 70 Td, (iv) 87 Td, (v) 105 Td, and (vi) 122 Td. The data are normalized to illustrate the peak position more clearly. In (D) no signal was obtained at the highest field due to the loss of this lowmass ion at the walls, a consequence of a reduced effective gap in helium.
10C). There is some mass dependency where lower molecular weight species tend to have higher R values in polar gases and also tend toward type B (mixed mode) behavior in dry gases. This is explained by the relative mobility difference between the clustered and declustered states, which is greater for small ions than for large ones. Some of the traces in the R plots of Figure 10 can be cross-referenced to Table 1 to illustrate these trends. Second, and with potentially more practical importance, the slopes of these curves are different for the various compounds and each compound generates different curves under different transport gas conditions. Specific chemical interactions between an ion and the transport gas are reflected in these measurements. In general, chemical interactions dominate the separation, particularly when modifiers are used. The specificity inherent in these chemical interactions increases the resolving power of DMS in a
Figure 9. (A) R curve plots for methylhistamine under four different transport gas conditions generated from the data in Figure 8: (i) nitrogen with 1.5% 2-propanol, (ii) nitrogen, (iii) nitrogen with 28% helium, and (iv) nitrogen with 37% helium. (B) Expansion of the y axis of (A) to more clearly demonstrate the bimodal behavior in (ii)-(iv).
manner orthogonal to that of mass spectrometry and offers possible increases in specificity and chemical noise reduction for mass spectrometry based analyses. The use of several different types of modifiers has been reported for this purpose.31 The clusters that lie at the heart of these mechanisms are in the form of weakly bound ion-neutral interactions that span a wide cluster number ranging from a small number of adducts to higher cluster numbers. It is difficult to quantify precisely the number of these adduct molecules because these entities have bond energies substantially less than 1 eV and they do not survive the free jet expansion from the atmospheric source to the vacuum conditions of the mass spectrometer regardless of the declustering field in the interface region of the mass spectrometer. As a result, we have not been able to observe these clusters in the mass spectrum. Their properties have not been studied by mass spectrometry techniques in vacuo because they do not remain intact in the atmosphere to vacuum optics where collisions and energy transfer are unavoidable. Their existence is however confirmed by the differential mobility separation at atmospheric pressure, and the value of the R parameter is a relative measure of the size and shape of these clusters. The selectivity of the separations reflects the subtle nature of these interactions which appear to conserve the chemical specificity of individual molecules in relationship to the high gas density medium through which they travel. It is possible that there may be a much stronger correlation between solution-based physical chemical parameters and the R trends observed with different modifiers and field conditions. Solvent-solvent distribution coef(31) Levin, D. S.; Miller, R. A.; Nazarov, E. G.; Vouros, P. Anal. Chem. 2006, 78, 5443–5452.
Figure 10. R versus separation field for 36 compounds from Tables 1 and 2 under different transport gas conditions: (A) data for all 36 compounds with nitrogen transport gas modified with 1.5% 2-propanol, (B) 11 of the compounds demonstrate type B behavior with nitrogen transport gas, (C) 25 of the compounds demonstrate type C behavior with nitrogen transport gas. Numbers on some of the curves cross-reference to Tables 1 and 2.
ficients and solubility are just two possibilities. This is an area worthy of future investigations. CONCLUSIONS Planar DMS has been recognized as having resolution advantages over other configurations32 and has been the subject of recent papers from other groups.33 However, the results presented here indicate that DMS resolution can be increased dramatically beyond results that have been presented previously. Peak capacity and separation power with ESI/DMS/MS are highly influenced by the composition of the transport gas. The differential mobility of compounds in the presence of polar modifiers versus inert gas mixtures show enhanced peak capacity and selectivity. Factors such as the increased amplitude of ion oscillations with helium/ (32) Shvartsburg, A. A.; Li, F.; Tang, K.; Smith, R. D. Anal. Chem. 2006, 78, 3706–3714. (33) Mabrouki, R.; Kelly, R. T.; Prior, D. C.; Shvartsburg, A. A.; Tang, K.; Smith, R. D. J. Am. Soc. Mass Spectrom. 2009, 20, 1768–1774.
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
nitrogen transport gases, ion chemistry effects with modifiers, and fragmentation can serve to reduce the peak capacity particularly for situations where the compounds are unknowns and their behavior under these conditions cannot be compensated. The theory underlying the separation mechanisms at play with DMS explains the amplification in peak capacity and separation power observed in the presence of polar-modified transport gases versus inert gases. The consistency of the correlation of the mechanisms, described here and elsewhere as the “clustering model” and the “rigid-sphere model”, and the experimental data across a broad chemical space demonstrates the generalization. In the past the mobility behavior that various compounds exhibited with respect to the field dependence of the R parameter had been classified into three general types of behavior. It is shown here that these classifications reflect the dominant separation mechanism at play, whether it is clustering or rigid-sphere or a gradual switch between the two at different field strengths. The electric field dependence on the mobility is influenced by the degree to which the ion exists as a naked molecular ion or whether it is clustered in the gas phase, which has correlation to other physical chemical properties of a molecule, including the charge distribution. The energy involved in the formation and dissociation of the clusters is highly specific to the chemical interactions between a particular ion and neutral gas-phase molecules. The cluster distributions appear to be preserved in
Analytical Chemistry, Vol. 82, No. 5, March 1, 2010
the mild conditions of the atmospheric pressure separation but are lost during the free jet expansion into vacuum. The state of the ion generated by electrospray and transported through the DMS cell, and thus its mobility behavior, is determined by several factors in addition to the composition of the transport gas such as the mode of ionization, the liquid flow rate under which ionization is performed, and any other accommodations to enhance or minimize the clustering process such as heat or dry countercurrent gas flows. The conditions under which the data in this paper were taken are narrow, well-defined, and reproducible. Mechanistic generalizations from the results presented here are broadly applicable, but specific values for R functions for individual compounds will be affected by the experimental conditions. These values are stable and reproducible when the separation conditions are kept consistent. ACKNOWLEDGMENT We are very appreciative of the assistance of Deolinda Fernandes at MDS Analytical Technologies for the preparation of the samples. This work was partially supported by the Columbia University Center for Medical Countermeasures against Radiation (P. I. David Brenner) and NIH (NIAID) Grant U19 AI067773-02. Received for review November 10, 2009. Accepted January 14, 2010. AC902571U