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. 2022 Aug 1;94(32):11113–11117. doi: 10.1021/acs.analchem.2c02351

Unwrapping Wrap-around in Gas (or Liquid) Chromatographic Cyclic Ion Mobility–Mass Spectrometry

Jake Breen †, Mahin Hashemihedeshi †, Roshanak Amiri †, Frank L Dorman ‡,§, Karl J Jobst †,*
PMCID: PMC9387526  PMID: 35913896

Abstract

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Gas chromatography multiplexed with cyclic ion mobility mass spectrometry is a comprehensive two-dimensional separation technique that can resolve compounds that would otherwise coelute in a single-dimension separation. The cyclic geometry of the ion mobility cell enables ions to travel multiple passes, increasing their drift times to the detector and relative separation. However, the quality of the separation may be obfuscated when “wrap-around” occurs, during which speedier ions catch up with slower ion populations when allowed to travel through more than one pass. Consequently, cyclic ion mobility is incorrectly perceived as a targeted approach that requires preselection of ions prior to separation. The present study demonstrates that “wrap-around” can be mitigated by comparing drift times measured during single- and multipass experiments and extrapolating the number of passes experienced by each ion. This straightforward calculation results in the “unwrapping” of cyclic ion mobility data so that the experiments can be interpreted in a nontargeted way while reaping the benefit of peak capacities that rival those achieved using other comprehensive two-dimensional separations.

1. Introduction

Ion mobility is a technique that enables the separation of gas-phase ions by subjecting them to unreactive collisions with nitrogen or helium that impede their travel to the detector, akin to aerodynamic drag on an aircraft in flight.1 Two ions of the same mass, but different shapes, can thus be separated by ion mobility. There are several ways to achieve this.2 The traditional approach involves measuring the time required for an ion to travel through a drift tube of fixed length. Extending the path through which the ions travel can improve the separation. This motivated the development of a drift cell with a cyclic geometry,3 namely, cyclic ion mobility (cIMS), which allows the analyst to select how many passes an ion travels before being released to the detector. While traveling an infinite number of passes is theoretically possible, signal loss of circa two percent per pass is a limitation. Giles et al.3 have demonstrated up to 100 passes, and most applications of cIMS thus far have employed 4–5 passes.4 This corresponds with a 10–15-fold increase in path length and 5-fold increase in ion mobility resolution over the previous generation of TWIMS-based IMS instruments equipped with a linear drift cell.3 However, the separation may be compromised when slower ions are overtaken by speedier ion populations, a phenomenon coined “wrap-around”,3 leading to a perception that cIMS is a targeted approach that requires preselection of ions prior to separation.

Wrap-around is particularly frustrating when cIMS is hyphenated with gas or liquid chromatography (LC or GC). Practitioners of untargeted metabolomics and nontargeted screening (NTS)5 of environmental pollutants require multidimensional analytical techniques that can comprehensively separate and characterize complex mixtures, especially when the identities of the constituent chemical compounds are unknown. Blumberg and Klee6 define an n-dimensional separation as an analysis that generates n-dimensional displacement information. When wrap-around occurs, this displacement information becomes masked. Strategies to mitigate wrap-around include narrowing the range of ions subjected to cIMS using the quadrupole mass analyzer7 or tandem ion mobility experiments,4 but this is not comprehensive separation because a large fraction of the sample mixture is excluded.6 Herein, we describe how to “unwrap” cIMS data post-acquisition by estimating the number of passes experienced by each ion and determining its periodic drift time, which can also be used to derive collision-cross section (CCS) information using a standard approach.8 This is demonstrated using a novel gas chromatographic cyclic ion mobility–mass spectrometer, and it is anticipated that the same data analysis procedure is applicable to other chromatographic separations, such as liquid chromatography, multiplexed with cIMS.

2. Experimental Methods

2.1. Instrumental Analysis

Gas chromatography–cyclic ion mobility mass spectrometry (GC-cIMS) experiments were performed using a Waters cyclic ion mobility mass spectrometer (Wilmslow, U.K.) coupled to an Agilent 8890 gas chromatograph using atmospheric pressure chemical ionization (APCI). Analyte separation was performed with an Rtx-5 column (30 m × 0.25 mm × 0.25 μm). The initial temperature was set to 90 °C; the oven was then ramped to 325 °C at 8.4 °C/min and held at that temperature for 6 min. Sample extracts and standard solutions (1 μL) were injected in the splitless mode. The inlet temperature was set to 280 °C, and the helium carrier gas flow was set to 1.4 mL/min. GC eluant exiting the column was swept through the ion volume using a makeup flow of nitrogen (∼99.99% purity) at 350 mL/min. Atmospheric pressure chemical ionization was initiated by a corona discharge (3 μA) in both positive and negative ion modes. The source conditions were as follows: source temperature, 150 °C; sampling cone, 40 V; extraction cone, 10 V; cone gas, 175 L/hour; auxiliary gas, 100 L/hour. Column bleed (C9H27O5Si5+: m/z 355.0705) and background ions (C16H31O2–: m/z 255.2324; C18H35O2–: 283.2637) were used to internally correct the measured m/z in the positive and negative ion modes, respectively. Mass spectra were collected from m/z 50 to m/z 1200. The cyclic ion mobility cell was operated with a traveling wave (TW) height of 22 V. Cyclic and array TW velocities were 375 m/s. The separation time refers to the time during which the T-wave array at the base of the cyclic ion mobility cell is set to direct incoming ions onto the cyclic cell. After this time, the T-wave array reverts to the default configuration wherein ions are directed off the cell and toward the detector. The separation time was set to 2 ms to acquire single pass data and 0.01 ms to determine the drift time of ions that bypass the cyclic drift cell and travel directly to the detector without separation. Separation times of 3.79, 6.40, 9.00, 11.61, and 14.21 ms were also employed to study the effects of wrap-around. Details on the design of the cIMS and the unique tandem IMS experiments that can be performed are described by Giles et al.3

2.2. Indoor Dust Samples and Analytical Standards

SRM 2585, a reference material of indoor dust, was purchased from the National Institute of Standards and Technology (NIST). To extract the sample, approximately 2 g of dust was sonicated for 30 min each using 5 mL of hexane, 5 mL of acetone, and 5 mL of 1:1 methanol/acetonitrile. The extracts were concentrated to dryness and reconstituted into 100 μL of hexane. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (2378-TCDD), 1,3,7,8-tetrachlorodibenzo-p-dioxin (1378-TCDD), and 1,2,3,4-tetrachlorodibenzo-p-dioxin (1234-TCDD) were obtained from Wellington Laboratories (Guelph, Ontario).

2.3. Data Processing

DriftScope (v. 3.0) was used to create GC × cIMS contour plots and perform peak-picking on the raw data. Manipulation of peak lists obtained from DriftScope was performed using RStudio. Alignment of experiments was performed by matching GC retention times and m/z values using rudimentary functions in RStudio. Sample data and calculations are provided in the SI.

3. Results and Discussion

Figure 1a displays the contour plot of drift time versus retention time obtained from SRM 2585, a reference material created with indoor dust. During this experiment, the ions are allowed to travel a single pass through the cyclic ion mobility cell. Figure 1a illustrates the benefits of comprehensive two-dimensional separation9,10 because many compounds are separated by ion mobility that would otherwise coelute from the GC. We also note that Figure 1a is structured in appearance and displays patterns that can aid the analyst in identifying compounds belonging to the same class, akin to how chromatographers interpret GC × GC and LC × LC contour plots. For example, Figure 1a displays nine siloxane homologues (1–9) originating from the injector septum with the general formula C2n–1H6n–3OnSin+ (n = 3–11) that fall upon a diagonal line. This is because lengthening the siloxane chain will result in a predictable, stepwise increase in a compound’s GC retention time while decreasing its mobility.

Figure 1.

Figure 1

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Contour plots displaying gas chromatographic retention time (minutes) vs ion mobility drift time when separation times of (a) 2, (b) 7, and (c) 14 ms are used; Panels (d)–(f) display m/z vs ion mobility drift time for the same experiments.

When the separation time is increased to 7 ms (see Figure 1b), “wrap-around” occurs, as witnessed by the observed shift in drift time of the siloxane ions 1 in Figure 1b. Ions 1 are now characterized by a longer drift time and lower apparent mobility compared to ions 2, even though ions 2 are larger in size and molecular weight. This is because the separation time (7 ms) is enough to allow swift moving ions 1 to travel the cyclic cell twice, whereas ions 2 only experience a single pass. After 14 ms of separation (Figure 1c), ions 1 have now traveled three passes and wrapped around twice, ions 2–4 have traveled two passes and wrapped around once, and ions 6–9 have traveled only one pass. The population of ions 5 has been split almost evenly, with one part undergoing two passes, while the other traveling only one pass.

The mobility of an ion is also partly related to the mass of the analyte ions, and consequently, the m/z and drift times are correlated in Figure 1d. During the course of a single pass, ions of greater molecular weight are characterized by longer drift times. However, the appearance of the contour plot changes dramatically when generated from multipass data, as shown in Figure 1e–f. The wrap-around reveals itself by the formation of multiple bands of peaks. The slope of each band of peaks reflects the number of passes experienced by the ions. Increasing the number of passes lengthens the drift time and enhances the separation between ions. Thus, if one were to fit a line through each band of peaks, the slope increases with the number of passes. In Figure 1e, most of ions are subject to one pass, with the remainder experiencing up to three passes. When the separation time is increased to 14 ms, the distribution shifts further, with the plurality of ions subject to two passes, and the remainder experiencing up to eight passes. One may reasonably expect that further increasing the separation time will further shift the distribution of ions to a greater number of passes.

The experiments (Figure 1a vs c or Figure 1d vs e) show that the displacement information in the ion mobility dimension becomes masked during multipass experiments. While the drift time is correctly measured, the distance traveled by an ion cannot be known from a single experiment performed at one separation time point. However, the progression of experiments at different separation times (see Figure 1) show that even visual analysis can help identify the number of passes experienced by a series of ions (e.g., ions 1–9) and thus recover the displacement information. This requires the determination of the time during which each ion travels through a single pass, that is, its periodic drift time (t1p). The relationship between periodic drift time and number of passes is linear, see eq 1. Note that the arrival time (ta) measured during a single pass represents the sum of t1p, during which ion mobility separation occurs, and the time required for the ions to travel between the accumulation trap and the detector, during which ion mobility does not occur. The latter time frame is coined “zero-pass” time (t0p) or, to borrow a term from chromatography, “dead time”.

3. 1

This linear relationship is observed when a constant T-wave height (22 V) was used to separate three isomeric model compounds, 2,3,7,8-, 1,2,3,4-, and 1,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), see Figure 2. Their mean periodic drift times 11.35 ± 0.08, 11.19 ± 0.20, and 11.25 ± 0.08 ms (R2 = 1.00) over 35 passes are consistent with those measured during a single pass experiment (11.68, 11.15, and 11.55 ms, respectively), as well as the order of the CCSs, 163.7 ± 2, 157.9 ± 0.9, and 160.93 ± 2 Å2, computed using MobCal-MPI.13

Figure 2.

Figure 2

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Relationship between the arrival time (ms) and the number of passes is linear using a model compound (2,3,7,8-tetrachlorodibenzo-p-dioxin). Data were collected for most data points up to 35 passes.

To unwrap multipass data, one only needs to perform two experiments to extrapolate the slope and intercept in eq 1. Without knowing the number of passes in a multipass experiment, a priori, it is convenient to perform two experiments where n = 0 and 1. First, the t0p times can be obtained by setting the separation time to 0.01 ms, allowing all ions to bypass the ion mobility cell. Then, a single pass experiment is performed to estimate t1p using a relatively short separation time of 1–2 ms. Finally, the multipass experiment is performed, and the number of passes traveled by each ion is determined using the arrival time values (ta) observed in the multipass experiment and the t0p and t1p values extrapolated from eq 1 using the zero-pass and single-pass experiments. In order to apply this procedure to complex mixtures of unknown chemicals, the data must be exported (using the peak-picking algorithm in DriftScope) and aligned according to m/z and chromatographic retention time. The alignment can be achieved using a variety of commercial and open-source software packages. A simple R-based script to align the data is provided in the SI. Figure 3a and b display exported peak lists, depicted as m/z versus drift time and obtained from single-pass and multipass experiments, respectively. When the data in Figure 3b are aligned with the single pass data in Figure 3a and zero-pass data (not shown), the number of passes for each ion can be determined. From the derived number of passes, the average period can be calculated for each ion and graphed against m/z or chromatographic retention time to yield an unwrapped plot, see Figure 3c. In the same vein, the wrapped retention time versus drift time plot (Figure 4a) can also be unwrapped, see Figure 4b. The y-axes in Figures 3b and 4b correspond with the periodic drift time, which are virtually identical to the values computed from single pass data. Consequently, deriving CCS data therefrom can be achieved using a standard approach.8 This approach is also applicable to unwrapping isomers. Figure 2b and 2c show the separation of the three isomeric compounds (2378-TCDD, 1234-TCDD, and 1378-TCDD) using a single pass and multiple passes, respectively. When the arrival times in Figure 2c are converted to periodic drift times (see Figure 2d), one observes that the ion mobility separation is preserved and the most compact isomer, 1234-TCDD, is correctly displayed with the shortest periodic drift time.

Figure 3.

Figure 3

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Comparison of m/z vs drift time measurements obtained under (a) single pass and (b) multipass conditions. The wrap-around effect observed in (b) is unwrapped in (c) by extrapolating the number of passes experienced by each ion. The periodic drift time can be used to derive the CCS using a standard approach.8

Figure 4.

Figure 4

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Comparison of (a) “wrapped” and (b) “unwrapped” retention time vs drift time contour plots obtained by GC × cIMS. The horizontal lines bisect populations of ions that travel a different number of passes through the cyclic ion mobility cell.

Akin to other two-dimensional separation techniques, such as GC × GC9 and LC × LC,10 multiplexing GC and single-pass IMS results in a separation is “comprehensive” because it meets the following criteria:11,12 (i) Every part of the sample is subjected to both gas chromatography and ion mobility separations; (ii) Equal amounts of all sample components pass through both dimensions of separation and eventually reach the detector; and (iii) The separation obtained in the chromatographic dimension is maintained. The apparent loss of displacement information in the ion mobility dimension would suggest that GC coupled with cIMS is not a comprehensive multidimensional separation technique. However, we show that this information can be recovered by performing the experiment at multiple separation times so that the number of passes and average periodic drift time can be determined.

4. Conclusion

The present study demonstrates how to “unwrap” chromatographic cyclic ion mobility data and recover ion mobility displacement information that are masked when speedier ions catch up with slower ion populations during separation. The number of passes experienced by each ion can be determined by (i) performing three cIMS experiments in which the separation times are set to 0 ms, ∼2 ms, and a value >10 ms to obtain zero-, single-, and multipass data, respectively; (ii) aligning the peak lists obtained from these experiments by m/z and chromatographic retention time; (iii) calculating the amount of time required for each ion to travel a single pass by subtracting the drift time obtained in the zero pass experiment from that of the single pass experiment; and (iv) dividing the actual arrival time in a multipass experiment by the estimated time each ion requires to travel one pass. From the derived number of passes, the average period can be calculated for each ion and graphed against m/z or chromatographic retention time to yield an unwrapped plot. This procedure is applicable to any combination of cIMS and chromatography. While the solution to wrap-around presented herein requires more than one sample injection, it may eventually be possible to perform the “unwrapping” procedure in a single experiment. However, this will require modification of the software and firmware to allow switching between multiple tandem ion mobility sequences, akin to monitoring multiple dissociation reactions using a tandem mass spectrometer.

Acknowledgments

This research was funded by the Canada Foundation for Innovation (CFI) and the Natural Sciences and Engineering Research Council (NSERC). Computing resources were provided by ACEnet (www.acenet.ca) and Compute Canada (www.computecanada.ca). The authors gratefully acknowledge Waters Corp. for contributing the gas chromatograph and GC-APCI ion source used in this research.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.analchem.2c02351.

  • R-based script to unwrap cyclic ion mobility; Template spreadsheet to help create input files; Sample data cIMS data for evaluation and testing (PDF)

  • Sample data (XLSX)

  • Template spreadsheet (XLSX)

The authors declare no competing financial interest.

Supplementary Material

ac2c02351_si_001.pdf (213.1KB, pdf)
ac2c02351_si_002.xlsx (14.1MB, xlsx)
ac2c02351_si_003.xlsx (10.3KB, xlsx)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

ac2c02351_si_001.pdf (213.1KB, pdf)
ac2c02351_si_002.xlsx (14.1MB, xlsx)
ac2c02351_si_003.xlsx (10.3KB, xlsx)

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