Article pubs.acs.org/EF
Petroleomics by Traveling Wave Ion Mobility−Mass Spectrometry Using CO2 as a Drift Gas Maíra Fasciotti,*,†,‡,@ Priscila M. Lalli,†,§,# Clécio F. Klitzke,†,∥,∇ Yuri E. Corilo,†,§,# Marcos A. Pudenzi,† Rosana C. L. Pereira,†,⊥ Wagner Bastos,⊥ Romeu J. Daroda,‡ and Marcos N. Eberlin*,† †
Laboratório ThoMSon de Espectrometria de Massas, Instituto de Química, Universidade Estadual de Campinas, Campinas, São Paulo (SP) 13083-970, Brazil ‡ Instituto Nacional de Metrologia, Qualidade e Tecnologia, INMETRO, 25250-020 Duque de Caxias, Rio de Janeiro (RJ), Brazil § Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States ∥ LECO Corporation, St. Joseph, Michigan 49085, United States ⊥ CENPES, PETROBRAS, Rio de Janeiro, Rio de Janeiro (RJ) 21941-909, Brazil S Supporting Information *
ABSTRACT: The technique of choice for petroleomics has been ultra-high-resolution and high-accuracy Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), but other techniques such as ion mobility have been shown to provide additional or alternative information about crude oil composition. Using the traveling wave ion mobility (TWIM) cell of a hybrid Q-TWIM-TOF first-generation Synapt instrument and electrospray ionization in both the positive and negative ion modes, different crude oil samples with different polar compound profiles and petro fuels (diesel and gasoline) with or without additives were analyzed using either CO2 or N2 as the drift gas. Parameters such as gas pressure, velocity, and wave height were optimized for each type of crude oil or fuel sample. The ability of TWIM−MS to separate crude oil components according to their classes was verified by comparison with FT-ICR data. Results showed separation of several classes of polar compounds (NO, O2, and N), and their separation was improved using CO2, which also enhanced the resolution between adjacent m/z species. Additives and contaminants presented in petro fuels could also be easily separated and characterized.
1. INTRODUCTION Crude oil is certainly one of the mixtures found in nature with the highest degree of diversity and chemical complexity, consisting of many thousands of organic and inorganic compounds.1−4 Despite the great challenge, proper characterization of such a diverse multicomponent mixture at the molecular level is fundamental in many processes of the crude oil chain, from exploration to refining. Petroleomics is an area of research that has been motivated by the ultimate goal of characterizing all components present in crude oil samples and how they affect its reactivity and physical and chemical properties.5,6 In petroleomics, techniques used to investigate the composition of nonpolar or less polar components of crude oils, their most abundant components, are well established and of high efficiency, such as gas chromatography with flame ionization detection (GC−FID) and GC coupled to mass spectrometry (GC−MS).7 For the investigation of polar components of crude oils, direct analysis with no previous separation via ultra-high-resolution and ultra-high-accuracy Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and electrospray ionization (ESI) in both the negative and positive ion modes have been the techniques of choice.5−9 Polar molecules with a generic molecular formula of CcHhNnOoSs5 are believed to represent their most ancient components and therefore to be proper target molecules for crude oil analysis.10 The accurate mass measurements and ultrahigh resolution permit the classification of major polar © 2013 American Chemical Society
components as a function of their heteroatom classes (e.g., N, NO, NO2, O, O2, and S) as well as by the number of rings plus double bonds, as measured by the double bond equivalents (DBE).11 The crude oil compositions have therefore been characterized in great detail, and results such as class distributions, DBE versus carbon number plots, and van Krevelen and Kendrick diagrams have been displayed in graphics.12,13 A comprehensive review of the major analytical methods in petroleomics was recently published.7 Ion mobility spectrometry coupled to mass spectrometry (IM−MS) has also been shown to provide a powerful tool for the analysis of complex mixtures.14−16 Ion mobility spectrometry (IMS) also separates ions according to their masses, but other parameters are involved such as collision cross section (“shape” in the gaseous phase), charge, and drift gas polarizability, leading to contrasting binding energies and life times of the ion−molecule complexes with the neutral drift gas molecules.17,18 When coupled to mass spectrometry (IM−MS), the technique offers a powerful tool for structure elucidation and isomer separation19 because it adds a new dimension to the analysis, giving for each m/z an ion mobility spectrum in the third dimension with information about the shape of the ions. The main use of IM−MS for structural elucidation has been in conformational studies of gaseous proteins and peptides.20 Received: August 15, 2013 Revised: November 12, 2013 Published: November 19, 2013 7277
dx.doi.org/10.1021/ef401630b | Energy Fuels 2013, 27, 7277−7286
Energy & Fuels
Article
(v/v) methanol/toluene mixture (HPLC grade, Honeywell Burdick & Jackson), adding ammonium hydroxide at optimized concentrations for each sample according to the ionization efficiency, which varied from 1 to 5% (v/v). Then, the samples were directly infused into the ESI source operating in negative ion mode. For petro fuels (diesel and gasoline with or without additives), the samples were directly collected from gas stations (of different companies) in the city of Campinas, São Paulo, Brazil. For sample preparation, 2 μL of each sample was diluted in 5 mL of MeOH with 0.1% (v/v) ammonium hydroxide for the detection of negative ions and with 0.1% (v/v) formic acid for the detection of positive ions. 2.2. Instruments. ESI−TWIM−MS experiments were performed using a Waters (Manchester, U.K.) Synapt G1 HDMS (high-definition mass spectrometer). This instrument has a hybrid quadrupole/ion mobility/orthogonal acceleration time-of-flight (TOF) geometry. In this Synapt HDMS, the diameters of the TWIM entrance and exit apertures were reduced from 2 to 1 mm, thus allowing the drift gas pressure to be efficiently increased without any substantial effect on the vacuum system and TOF-MS performance in terms of m/z resolution. This fact also had improved the IMS resolution, which is better if compared to that of a typical Synapt HDMS, i.e., has an intermediate resolving power (between those of Synapt HDMS and Synapt G2).17 For crude oil, ESI(−)−MS was acquired in a range of m/z 50−800. CO2 and N2 were used as drift gases. Major parameters of the ionization source and the mobility cell were optimized to obtain a higher sensitivity and resolving power (Table 1). The analysis of petro
In petroleomics, high-accuracy Fourier transform MS mass (m/z) measurements, class, DBE, and carbon number assignments are possible but no information about three-dimensional (3D) structures is obtained. IM−MS seems therefore to be attractive as a complementary tool for petroleomic studies because 3D shapes could be added as an additional piece of information at the molecular level for isomeric species. Class assignments could also be determined if different classes display contrasting and systematic changes in the shapes of the gas phase ions.21 Russell and co-workers were the first to apply IM−MS in 2009 in the characterization of crude oils using laser desorption ionization (LDI) and a conventional ion mobility cell filled with helium and a time-of-flight (TOF) mass analyzer.22 They used IM−MS for fast chemical fingerprints of light, medium, and heavy crude oils. They also observed general trends such as the shift from planar to more compact 3D structures with increasing mass, showing that high-mass species in crude oil possibly result from noncovalent aggregation rather than extended planar fused hydrocarbon rings. Later, in 2011, Kim and co-workers23 used TWIM−MS in N2 performed on a Synapt G2 and atmospheric-pressure chemical ionization using an ASAP (atmospheric solids analysis probe) ion source in an attempt to elucidate structural relationships between molecules. They observed that molecules from a homologous series were linearly aligned in the m/z−mobility plot, while molecules differing in the number of hydrogen atoms showing significant changes in the drift times (at three or four ion intervals) presumably because of the addition or removal of a benzene ring. Recently, Ponthus and Riches24 also used TWIM−MS in N2 performed on Synapt G2 samples of the saturate, aromatic, resin, and asphaltene (SARA) fractions of a crude oil sample. They calibrated the TWIMS region of the instrument using polyalanine, which allowed the calculation of the sizes of species within the samples, yielding detailed information about the sizes and shapes of individual components of oil and petroleum samples. DBE and carbon number groups were identified using patterns in the IMS data. The ion mobility data were also compared with FT-ICR MS data, and various nitrogen-containing families were identified. So far therefore, IM−MS analyses of crude oils have been performed using the conventional drift gases He and N2. TWIM cells present several advantages such as high transmission and small sizes but relatively low resolution.25,26 One strategy for improving TWIM resolution is the use of more polarizable drift gases.17,19a,b,21,27,28 The theoretical considerations for the improvement of the separations by ion mobility using drift gases with different polarizabilities and molecular weights have been discussed by Campuzano and co-workers17 and Asbury and Hill.27 A systematic comparison of the resolution of a TWIM cell as measured by peak-to-peak resolution (Rp−p) using N2 and CO2 as drift gases has also been recently reported by Klitzke and co-workers.21 Herein, we have investigated, using a Synapt G1 instrument, the ability of TWIM−MS in CO2 to provide structural and class information about the polar constituents of crude oil samples and petro fuels. To monitor class separation, the TWIM−MS data were compared to FT-ICR MS data.
Table 1. Optimized Parameters for ESI and TWIM−MS Analysis of Crude Oil Samples parameter
optimized value
capillary (kV) sample cone (V) extraction cone (V) source temperature (°C) desolvation temperature (°C) desolvation gas flow rate (L/min) bias
2.8 50 3.0 150 200 300 35 100 300 900 5.0 0.838 450 30
manual profile (m/z) LM/HM resolution CO2 pressure (mbar) wave velocity (m/s) wave height (V)
fuels was conducted in both negative and positive ion modes, using CO2 as the drift gas, in the range of m/z 50−2000. For crude oil derivatives, the values used for ESI conditions were the same as those described in Table 1. Specific conditions of wave parameters and drift gas pressure will be mentioned throughout the text. The equipment was calibrated daily using a phosphoric acid solution. The mass spectra were recorded using MassLynx version 4.1, and mobility data were obtained and interpreted via DriftScope version 2.1, using the tool of automatic detection of peaks, with detection of ions with a minimal intensity of 80 counts and a mass resolution of 4000. The results of TWIM−MS for crude oil samples were compared with the data of ultra-high-resolution MS obtained with a Thermo Scientific 7.2 T electrospray ionization Fourier transform ion cyclotron resonance mass spectrometer (Thermo Scientific, Bremen, Germany). A scan range of m/z 200−1000 was used, and 100 microscans were collected in each acquisition. The average resolving power (Rp) was 400000 at m/z 400. Time-domain data (ICR signal or transient signal) were acquired for 700 ms. Microscans were co-added using Xcalibur version 2.0 (Thermo Scientific). In addition to external calibration, an internal recalibration was applied to the peak list using PetroMS
2. EXPERIMENTAL SECTION 2.1. Samples and Reagents. Samples of approximately 2 mg of crude oil from different reservoirs in Brazil, provided by CENPES/ PETROBRAS, were diluted (without prior treatment) in 1 mL of a 1:1 7278
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software29,30 prior to final peak assignment. This software was specifically developed for the analysis of FT-ICR MS spectra in petroleomics studies. Graphs of the class of polar compound distribution and DBE versus carbon number plots for each class were plotted using this software and compared with the data from the TWIM−MS analysis.
transmission ability of the FT-ICR analyzer for low-m/z ions. The FT-ICR mass spectra were internally recalibrated on the basis of the most abundant homologous alkylation series (compounds that differ by integer multiples of CH2), and molecular formulas were assigned via the PetroMS software.29,30 Then, the Synapt mass spectra were calibrated by comparison of the m/z values of the most abundant series with the FT-ICR data. Samples of crude oil were analyzed by TWIM−MS, under optimized conditions, and the results from two of the most representative samples (S1 and S2) are presented. Figure 2
3. RESULTS AND DISCUSSION 3.1. Crude Oil Samples. As previously mentioned, the separation of ions in an ion mobility cell is based on several parameters such as the cross section that reflects its 3D structure (shape) in the gas phase, charge, and polarizability. Parameters such as the wave parameters in the TWIM cell31,32 and the physicochemical properties of the drift gas may be optimized to increase resolution. Better performance in terms of the resolution for TWIM cells has usually been obtained with the use of more polarizable and heavier drift gases,17,21,27 but loss of transmission may occur. N2 and CO2 gases can be quite adequate, because these features are more pronounced compared with those of other commonly used gases, such as helium. In addition, a drift gas must be capable of providing sufficient sensitivity to allow the transmission and detection of the compounds present at relatively low concentrations and higher resolving power, even when using smaller mobility cells, such as T-wave cells. First, N2 and CO2 pressures were optimized for the best TWIM resolution and ion transmission. The best pressure for CO2 was found to be 0.85 mbar and for N2 2.00 mbar (N2 is less massive than CO2, and hence, higher N2 pressures could be employed). ESI and MS parameters of both instruments were also optimized to provide the best possible sensitivity and better spectral shape. The overall shape of the mass spectrum obtained by TWIM−MS (Figure 1a) was compared with that obtained by FT-ICR MS (Figure 1b), and both were similar with respect to the expected Gaussian distribution and maximal intensities. The major difference observed was for ions of low m/z (
