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Effective Ion Mobility Peak Width as a New Isomeric Descriptor for the Untargeted Analysis of Complex Mixtures Using Ion Mobility-Mass Spectrometry

  • Mathilde Farenc
  • Benoit Paupy
  • Sabrina Marceau
  • Eleanor Riches
  • Carlos Afonso
  • Pierre Giusti
Research Article

Abstract

Ion mobility coupled with mass spectrometry was proven to be an efficient way to characterize complex mixtures such as petroleum samples. However, the identification of isomeric species is difficult owing to the molecular complexity of petroleum and no availability of standard molecules. This paper proposes a new simple indicator to estimate the isomeric content of highly complex mixtures. This indicator is based on the full width at half maximum (FWHM) of the extracted ion mobility peak measured in millisecond or square angstrom that is corrected for instrumental factors such as ion diffusion. This value can be easily obtained without precisely identifying the number of isomeric species under the ion mobility peaks. Considering the Boduszynski model, the ion mobility profile for a particular elemental composition is expected to be a continuum of various isomeric species. The drift time-dependent fragmentation profile was studied and confirmed this hypothesis, a continuous evolution of the fragmentation profile showing that the larger alkyl chain species were detected at higher drift time values. This new indicator was proven to be a fast and efficient method to compare vacuum gas oils for which no difference was found using other analytical techniques.

Graphical Abstract

Keywords

Ion mobility Mass spectrometry Petroleum Isomer Complex mixture 

Introduction

Petroleum is a highly complex mixture presenting molecules with a tremendous number of possible elemental compositions, each of them involving numerous isomeric species. The ultra-high resolving power of mass analyzers, such as Fourier transform ion cyclotron resonance, enable the separation of each ion and the determination of its chemical formula, although no information on isomeric content can be obtained [1]. The development of ion mobility-mass spectrometry (IM-MS) coupling afforded another dimension of gas-phase separation [2]. Ion mobility spectrometry (IMS) separates ions as a function of their size, shape, and charge, and can therefore bring isomeric information [3, 4, 5]. A large number of studies demonstrated the applicability of ion mobility for the separation of isomers [6, 7, 8], and the suitability of this technology for the analysis of petroleum samples was demonstrated by several studies [5, 9, 10, 11, 12, 13].

From the experimental drift time obtained by ion mobility analysis, it is possible to determine the ion collision cross-section (CCS) [14]. This can be done directly in the case of a uniform field ion mobility cell or through a calibration using a non-uniform field cell such as with traveling wave ion mobility (TWIM) [15, 16]. One key advantage of ion mobility compared with other separation methods is the predictability of the CCS values. It is indeed possible to associate putative tridimensional structures to experimental data through their theoretical CCS calculation [17]. CCS can be considered to be a fixed physicochemical property of an ion under specific experimental conditions, just as m/z is a fixed property of an ion. This is a great advantage for the characterization of complex mixtures such as fossil fuels as no standard molecules can generally be used to validate any molecular attribution.

The resolving power of most ion mobility spectrometers is generally low compared with most mass spectrometers and it is typical to obtain unresolved signals from isomeric species. Strategies have been proposed to improve the separation for specific cases using other drift gases such as CO2 or N2O [18], or using complexation with metal ions [19, 20, 21] or other ligands [22]. These approaches are, however, difficult to use for the untargeted analysis of complex mixtures. Some instrumental developments have been accomplished to improve this resolving power by using longer drift tubes or new ion mobility techniques like structure of lossless ion mobility (SLIM) or trapped ion mobility spectrometry (TIMS) [23, 24, 25].

In order to obtain information from unresolved ion mobility spectra, several approaches can be considered based on either peak deconvolution and/or post-IMS fragmentation [26, 27]. As discussed in previous works, the ion peak width is related to the existence of different isomers [3, 28, 29, 30, 31, 32]. With partially resolved signals it is possible to use a peak fitting algorithm to deconvolute ion mobility peaks. Such deconvolution can be in practice very accurate with ion mobility as, unlike with chromatography, peaks are expected to be Gaussian-like [33, 34], and the peak width of a single isomer is predictable [35, 36, 37]. Kim et al. [12] have presented a method to obtain structural information based on the prediction of the structure and the deconvolution of the ion mobility peak. In the same way, Rodgers and coworkers showed how the ion mobility dimension can allow the separation of isomeric and acidic molecules in petroleum [5]. More recently, Solouki et al. have developed a fitting software based on the full width at half height to detected unresolved ion mobility peak for targeted analysis [31].

In this work, we are proposing a new and general approach based on intrinsic ion mobility peak widths to extract information on isomeric content of unresolved IM-MS data for highly complex mixtures. This approach is here applied to vacuum gas oil samples but can be applied to any untargeted analysis of complex mixtures involving many isomeric species.

Experimental

Sample Preparation

Five vacuum gas oils were supplied by Total Research and Technology (Gonfreville, France). Samples were dissolved in toluene and diluted in methanol/toluene (50/50 v/v) spiked with 1% acetic acid to final concentration of ~1 mg mL–1.

Instrumentation

A Synapt G2 HDMS instrument (Waters Corp., Manchester, U.K.) was used to obtain ion mobility mass spectra. This instrument is a hybrid quadrupole/time-of-flight mass spectrometer, which incorporates a traveling wave (T-Wave)-based mobility separation device used with nitrogen (purity ≥ 99.9999%). The instrument and the T-Wave device have been described in detail elsewhere [16].

Electrospray ionization experimental conditions were set as follows: desolvation gas flow, 800 L h−1; source temperature, 120 °C; desolvation temperature, 400 °C; helium cell gas flow, 180 mL min−1; capillary voltage, 3.5 kV; sampling cone, 40 V; extraction cone, 5 V; IMS gas flow, 90 mL min−1 of N2 (2.96 mbar of N2 IMS cell pressure); IMS traveling wave height/velocity, 40.0 V/1000 m s−1. Data were acquired in positive mode over the m/z 50–1200 range for 10 min.

The TOF analyzer was set in the W reflectron mode with a resolution of 35,000. Instrument control and data acquisition were carried out by MassLynx (ver. 4.1) software. The mass analyzer was externally m/z calibrated using sodium formate solution before sample analysis. Internal calibration was carried out during the data treatment using MassLynx with confidently assigned signals to obtain a mass accuracy of 3 ppm.

The double bond equivalent (DBE) values were calculated from the determined empirical formula using the following equation.
$$ D B E= c\hbox{--} h/2+ n/2+1\ f o r\ a\ f o r mula\ {C}_c{H}_h{N}_n{O}_o $$
(1)

Tandem mass spectrometry experiments were carried out using the “transfer” cell, which is a stack ring ion guide used as collision cell with argon as target gas. The collision voltage was set to 55 V.

The data were externally CCS [38] calibrated using polyalanine solution as described by Smith et al. and using the references in N2 published by Bush et al. [14, 39]. The extracted ion mobility spectra were fitted using Origin pro ver. 9.1 software (OriginLab, Northampton, MA, USA). The graphs and tables were realized using Microsoft Excel software. The double bond equivalent versus carbon number plots were obtained using PetroOrg ver. 10.0 software.

Results and Discussion

Vacuum gas oil (VGO) samples, which are a heavy petroleum fraction, were analyzed by electrospray ionization in positive mode in order to predominantly ionize basic nitrogen-containing compounds [40]. This selective ionization allows the acquisition of relatively simple mass spectra, avoiding the presence of unresolved isobaric species. However, in addition to the N class, the NS class species can also be ionized by ESI yielding isobaric species that cannot be resolved with a high resolution TOF analyzer. Stanford et al. have shown that the NS class represents a very small part of the sample compared with the N class [41, 42]. The NS class can therefore be disregarded in the case of VGO samples. It should be pointed out that under the experimental conditions used, mainly monomeric species are expected in view of the unimodal ion distribution between C#20 and C#45 that is consistent to what is expected with a VGO sample [43, 44].

The series of compounds from the N1 class with eight double bond equivalent (DBE) was assigned and the corresponding ion mobility spectra were extracted with the lowest possible m/z window of 0.01. In these conditions, each extracted ion mobility profile is expected to be related to only one elemental composition.

In our previous paper, it was observed that a multimodal distribution was obtained for ion mobility profile of the C22H32N1 + ions indicating the presence of isomers [45]. It should be noted that in petroleum it is expected that each elemental composition will exists as numerous isomeric species. In most cases, this should result in a broad unresolved ion mobility peak. The method developed by Kim et al. enables the identification of species attributed to one molecular formula [12]; but to characterize an entire sample, a more comprehensive approach is needed as applying this method to signals in multiple samples can be time-consuming. According to the Boduszynski model [46, 47, 48], petroleum is a “continuum distribution of molecular weight, structure, and functionality from the low boiling point to the non-distillable residue.” If we extend this definition to the isomeric distribution, it can be considered that a continuous series of isomeric species is also present under each ion mobility peak and it is therefore complicated to estimate a finite number of isomeric species.

Figure 1 presents extracted ion mobility spectra for a series of ions of the N1 class with DBE = 8. It is interesting to note that only the C#22 ion mobility spectrum shows a multimodal distribution. Under such conditions, using a conventional peak peaking approach, only this ion mobility spectrum will afford direct evidences of the presence of isomeric species. However, one can note a significant change in ion mobility spectral peak width from C#18 to C#23.
Figure 1

Extracted ion mobility spectra for (a) m/z 254.19, (b) m/z 268.21, (c) m/z 282.22, (d) m/z 296.24, (e) m/z 310.25, (f) m/z 324.27 obtained using a m/z window of 0.01 to avoid interferences from isobars

The ion mobility peak width (FWHM) is, in principle, related to the presence of unresolved components but also to instrumental considerations such as ion diffusion, Coulomb repulsion, initial width of the ion injection pulse, and the possible ion molecule reactions with the drift gas. The role of ion molecule reactions in the drift region occurs mainly on ion mobility instruments operated under high pressure and high temperature conditions, and is generally not observed with instruments operated at lower pressures with pure drift gas [49]. For a single isomeric species, the FWHM should be mainly related to the ion diffusion, which explains why ion mobility peak widths increase with the drift time. In order to determine experimentally how the peak width changes according to the drift time, polyalanine ions were used as reference (Figure 2). According to the equations proposed by Mason et al., the highest resolution achievable with a drift tube ion mobility is given by Equation 2 [35].
Figure 2

Overlaid extracted ion mobility spectra of polyalanine peptide ions with increasing numbers of alanine residues

$$ R=\frac{t_D}{\varDelta {t}_{D1/2}}=\sqrt{\frac{zeV}{16 kTln2}} $$
(2)
In Equation 1, t D is the drift time, Δt D1/2 the ion mobility peak width (FWHM), k the Boltzmann constant, T the temperature (K), z the charge number, e the elementary charge, and V the drift tube potential difference. In this case, for a given charge state, a direct proportionality is expected between the ion mobility peak width and the drift time (Equation 3) as explained elsewhere [3].
$$ \varDelta {t}_{D1/2}= A\frac{t_D}{\sqrt{z}} $$
(3)
The FWHM (ΔtD1/2) was obtained after a Gaussian fit as shown in Supplementary Figure S1. For polyalanine, in the considered drift time region, a linear relationship with a determination coefficient (R2) of 0.985 is obtained between the ΔtD1/2 and the drift time (Figure 3). This linear fit defines the minimal ΔtD1/2 for a specific drift time corresponding to one isomeric distribution. The linear correlation indicates that there is no significant change of conformation of the polyalanine ions depending of the number of amino-acid residues.
Figure 3

ΔtD1/2 as a function of tD for the polyalanine ions and for the series of ions with DBE 8 of the N1 class

In principle, the presence of additional isomers with significant CCS differences should yield larger peak widths compared with that of polyalanine at the same drift time.

As shown in Figure 3, the evolution of the ΔtD1/2 for the DBE 8 ion series does not follow a simple linear correlation with drift time; in all cases, the VGO curve is above the polyalanine curve. This higher ΔtD1/2 is consistent with the presence of several isomers. Below 19 carbons the ΔtD1/2 peak width seems to follow a linear correlation with the drift time similar to the polyalanine ions. From 20 to 22 carbons the ΔtD1/2 peak widths rise quickly and after 22 carbons it seems to follows a linear correlation with the drift time.

In principle, with knowledge of the theoretical ΔtD1/2 for a single isomer, it is possible to estimate the number of isomers under an unresolved or partially resolved ion mobility peak. However, as discussed above, owing to the high number of isomers expected for each elemental composition, such an approach cannot be directly applied to estimate the number of isomers below an ion mobility peak of such highly complex mixtures (Supplementary Figure S2).

The difference in terms of ΔtD1/2 between the VGO and polyalanine curves can be called effective ion mobility peak width (ΔtD1/2′). The ΔtD1/2′ should be related to the number of isomeric species and this should allow us to obtain information on the isomeric distribution under each ion mobility peak. In the same way, the effective ion mobility peak width can be given in terms of collision cross-section (ΔCCS′1/2) corresponding to the difference between experimental ΔCCS1/2 and theoretical ΔCCS1/2 calculated from the polyalanine ΔCCS1/2 versus drift time linear fit. Another way to display this information is shown in Supplementary Figure S3 with the overlay of ion experimental and theoretical ion mobility peaks. The ΔCCS′1/2 values were calculated for the ion series with DBE 7, 8,and 9.

Table 1 presents the results for the DBE 8 species in terms of drift time (ΔtD1/2) and collision cross-section (ΔCCS′1/2) based on CCS calibration from the polyalanine CCS known values [38]. Interestingly, for the species with 17 to 19 carbons, ΔCCS′1/2 values are relatively low, indicating that for each m/z value, isomeric structures with similar CCS are detected. However, for species with more than 19 carbons, the ΔCCS′1/2 increases sharply with the number of carbons until it stabilizes for the species with more than 22 carbons.
Table 1

Drift Time, Experimental N2CCS, and ΔCCS′1/2 Corresponding to the C17 to C24 DBE 8 ions

C#

tD (ms)

CCS (Å2)

ΔtD1/2 (ms)

ΔCCS1/22)

Theoretical

ΔCCS1/2 a

2)

ΔCCS′1/2

2)

17

4,04

158,5

0,28

35,84

29,13

6,71

18

4,33

164,3

0,31

37,72

30,55

7,16

19

4,60

169,5

0,32

38,53

31,82

6,71

20

4,88

174,7

0,43

45,36

33,09

12,27

21

5,12

179,0

0,57

52,75

34,13

18,62

22

5,35

183,1

0,68

58,15

35,11

23,04

23

5,62

187,8

0,70

59,33

36,23

23,10

24

5,88

192,3

0,72

59,99

37,29

22,71

aFrom the polyalanine FWHM versus drift time linear fit plot.

To rationalize these results, it can be considered that the ions with low ΔCCS′1/2 indicate the presence of species with a small change in their structure and may correspond to position or chain isomers. On the other hand, the higher ΔCCS′1/2 obtained above 19 carbons could indicate the presence of isomeric species with important structural differences. The variations in ΔCCS′1/2 are represented in Figure 4 for the DBE values of 7, 8, and 9.
Figure 4

ΔCCS′1/2 as a function of carbon number 18 to carbon number 29 for the series of ions with DBE 7; 8 and 9 of the N1 class

DBE 8 shows the largest slope as the ΔCCS′1/2 quadruples for a 3 carbon number increase whereas the DBE 7 species exhibits only a small change in ΔCCS′1/2 values according to the carbon number. On the other hand, DBE 9 species show a continuous evolution of ΔCCS′1/2 as a function of the carbon number with almost no plateau.

As DBE 8 shows a significant change in ΔCCS′1/2, this series was investigated further. To better understand the structural difference between isomers, tandem mass spectrometry experiments were performed. The ions that show the higher ΔCCS′1/2 and so the higher amount of isomeric species (C#20-23) have been studied. The m/z of interest was selected in the quadrupole and collisionally activated after the ion mobility separation. In this case, product ions are formed but their drift times align with that of the precursor ion. Tandem mass spectra were extracted at specific drift times for the m/z 310 ions (Figure 5). The relatively low selectivity of the quadrupole does not allowed fragmenting only the C22H32N+ ion; however, the mass defect of the isobars are sufficiently different to not confuse them with the fragment ions of interest. Interestingly, the fragmentation profile changes depending on the drift time and therefore on the CCS value of the ions. In all cases, fragment ions are the same but their relative intensities are significantly different. In addition, in Figure 5 the relative abundance of the precursor ion appears to be very dependent on the drift time. This indicates that the ions at higher CCS values (higher drift time) (Figure 5b) are more fragile than the lower CCS value ions. Furthermore, the main product ion series corresponds to neutral losses of alkane molecules (C n H 2n+2 , n = 1–10); losses of alkene and/or cycloalkane molecules are also observed, although to a lesser extent. Such losses of alkanes are typically obtained from protonated quinolines under low energy collisional activation [50]. For smaller CCS isomers, the relative intensities of the fragment ions formed after fewer neutral losses are significantly higher than the same fragment ions formed from the larger CCS isomers.
Figure 5

CID spectra obtained from post ion mobility fragmentation of m/z 310 (C22H32N+ DBE 8) at (a) 5.0 ms and (b) 5.3 ms recorded with a collision voltage of 55 V. The weighted average loss by intensity calculated using Equation 2 is indicated by the red arrows

In order to compare the different fragmentation profiles, the weighted average mass loss by intensity was calculated using Equation 4. Only the fragments with intensity above 1000 counts were considered.
$$ \mathrm{Weighted}\ \mathrm{average}\ \mathrm{mass}\ \mathrm{loss}\ \mathrm{b}\mathrm{y}\ \mathrm{intensity}=\frac{{\displaystyle {\sum}_i}{\mathrm{I}}_i\left( m/{z}_{\mathrm{P}}- m/{z}_{\mathrm{F} i}\right)}{i} $$
(4)
In Equation 4, i is the number of fragment considered, I i is the intensity of the fragment ion, m/z P is the m/z of the precursor ion, and m/z F is the m/z of the fragment ion. The weighted average mass loss by intensity can be calculated for all the drift times of the mobility spectrum. In Figure 6, the weighted average mass loss by intensity is displayed as a function of the collision cross-section for the ions from 20 to 25 carbon number of the N1 class with DBE = 8.
Figure 6

Weighted average loss by intensity as a function of the CCS value for the ions from 20 to 25 carbon number of the N1 class with DBE = 8

Interestingly, in all cases the average mass loss increases with the CCS value. This indicates that larger CCS values correspond to longer alkyl chain species and to lower amounts of branching. On the other hand, the smaller CCS species suggest short alkyl chains and higher amounts of branching. Yet, for the largest CCS values, a change in the trend was observed as the average mass loss became almost constant for C# 20, 21, and 22. This may be related to a change in the type of molecular core resulting in a more elongated molecule with a similar amount of branching. These results are consistent with the CCS determination performed in our previous work [45].

To demonstrate the utility of the ΔCCS′1/2 isomeric indicator, three other VGOs were studied. Usually these complex mixtures are represented using isoabundance-contoured plots of DBE versus carbon number allowing to compare different samples easily [41]. Such 2D plots of the N1 class for three VGOs samples are given in Supporting Information (Supplementary Figure S4). In this case, no significant differentiation was obtained using the DBE versus carbon number plots for the three studied VGOs as the 2D plots are very similar. The ΔCCS′1/2 values were determined for the N1 class of compounds with carbon number 20. The results obtained for the three different samples are reported in Figure 7. Some trends were observed, such as the common increase of ΔCCS′1/2 values for DBE 8 and the decrease of ΔCCS′1/2 values for DBE 9. However, all samples seem to present very different profiles, indicating that they present different isomeric content. For example, VGO 1 and VGO 3 present very different values of ΔCCS′1/2 for DBE 13 but have close values of ΔCCS′1/2 for DBE 12. The isomeric differentiation can be easily evidenced and may give key information to rationalize specific properties of the samples.
Figure 7

Evolution of the ΔCCS′1/2 as a function of the CCS value for the compounds of 20 carbon number with different DBE values for three samples. The DBE values are indicated above the points on the graph

Conclusion

Ion mobility spectrometry affords a bidimensional separation generating a comprehensive molecular map and gives specific information on the isomeric distribution. In this work, an indicator of the isomeric distribution was proposed, corresponding to the experimental ion mobility peak width corrected for the contribution of ion diffusion within the drift cell and other instrumental behaviors such as the ion injection time. The indicator corresponds to a difference between experimental FWHM and calculated FWHM obtained from a reference. This approach is particularly interesting for the characterization of highly complex mixtures presenting a high number of isomers as the ion mobility peaks do not need to be deconvoluted and so no specific number of isomers is defined. This indicator was given as collision cross-section (ΔCCS′1/2) values. The evolution of ΔCCS′1/2 appears to be particularly useful to evidence the presence of isomeric structures within an ion mobility peak. Study of post-ion mobility fragmentation confirmed the presence of a continuum of isomeric species under each ion mobility peak in agreement with the Boduszynski model extended to isomeric species. This approach is very promising for the analysis of complex mixtures by ion mobility and mass spectrometry. We believe that this isomeric indicator will be particularly useful as a new descriptor to compare highly complex mixtures using chemometrics approaches. This value is obtained with a simple Gaussian fit that can be fully automated to treat a large amount of data for untargeted analysis.

Notes

Acknowledgements

This work was supported by the European Regional Development Fund (ERDF) no. 31708, the Normandie Region (Crunch Network, no. 20−13), the Labex SynOrg (ANR-11-LABX-0029) and the national FT-ICR network (FR 3624 CNRS).

Supplementary material

13361_2017_1749_MOESM1_ESM.docx (725 kb)
ESM 1 (DOCX 724 kb)

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Copyright information

© American Society for Mass Spectrometry 2017

Authors and Affiliations

  1. 1.TOTAL Refining and ChemicalsTRTG Gonfreville l’OrcherRogervilleFrance
  2. 2.Normandie Université, INSA Rouen, UNIROUEN, CNRS, COBRARouenFrance
  3. 3.TOTAL RC - CNRS Joint Laboratory C2MC: Complex Matrices Molecular CharacterizationPauFrance
  4. 4.Waters CorporationWilmslowUK

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