Characterization of Saturates, Aromatics, Resins, and Asphaltenes

May 8, 2012 - ABSTRACT: In this study, a heavy crude oil sample was separated on the basis of solubility and polarity, resulting in saturates, aromati...
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Characterization of Saturates, Aromatics, Resins, and Asphaltenes Heavy Crude Oil Fractions by Atmospheric Pressure Laser Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Andras Gaspar, Elio Zellermann, Sami Lababidi, Jennifer Reece, and Wolfgang Schrader* Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, D-45470 Mülheim an der Ruhr, Germany ABSTRACT: In this study, a heavy crude oil sample was separated on the basis of solubility and polarity, resulting in saturates, aromatics, resins, and asphaltenes (SARA) fractions. The fractions were analyzed by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) coupled to atmospheric pressure laser ionization (APLI). On the basis of the APLI−FT-ICR MS results, the molecular formulas and their corresponding aromaticity were compared to the bulk crude oil. The maltenes showed almost identical compound class distribution to the bulk sample, while the subfractions of the maltenes denoted unique distributions in compound classes and aromaticity. The aromaticity distributions of the fractions were in good agreement with expectations; however, the resins fraction showed higher aromaticity than the aromatics fraction. The potential of the SARA fractionation method as a sample-simplification tool that allows for a reduction of components present during the measurements was also demonstrated using APLI−FT-ICR MS.



INTRODUCTION Over the last few decades, an increase in the demand for commercial light oil and the decline of the quality of crude oil have been observed.1 As petroleum reserves move toward heavier crude oils, effective processing is necessary to fully use the heavy residue. Heavy petroleum is an extremely complex mixture with relatively high aromaticity and heteroatom moieties.2 Many of the problems associated with either recovery, separation, or processing of those crude oils are related to the presence of high concentrations of asphaltenes.3,4 The properties of these asphaltenes have an effect on the behavior of the crude oil during the refining process, making an in-depth characterization of these heavy crude oils necessary.5 Methods such as elemental analysis, nuclear magnetic resonance (NMR), small-angle neutron scattering, and various fluorescence measurements only describe an average molecular characteristic, while the detailed description of individual constituents remains unresolved.6−9 Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), with its unsurpassed high resolution, enables the analysis of complex petroleum mixtures on a molecular level.10−12 High-resolution MS data have shown that a discrimination of different compounds can be observed13 because of the different ionization efficiencies of crude oil constituents.14 A samplesimplification step, such as a chromatographic separation, is introduced prior to the high-resolution MS analysis, reducing the complexity of the heavy crude oil, which can result in a higher yield of assigned molecules.15,16 One of the most common methods to separate components of the crude oil is the saturates, aromatics, resins, and asphaltenes (SARA) fractionation.17−21 The asphaltenes are initially precipitated using nonpolar solvents (i.e., n-heptane), while the remaining crude oil residues or maltenes are fractionated further according to polarity, resulting in saturates, aromatics, and resins fractions. Atmospheric pressure laser ionization (APLI) was found to be a sensitive and selective ionization method for nonpolar © 2012 American Chemical Society

compounds, such as polyaromatic condensed structures, which may also contain heteroatoms.22 Additionally, the performance of APLI in the analysis of vacuum gas oil was also investigated, and the outcome showed good response for nonpolar aromatic hydrocarbons.16 APLI is a (1 + 1) resonance-enhanced multiphoton ionization (REMPI) method operating at 248 nm. APLI can be compared to one-photon ionization at 124 nm [usually used in atmospheric pressure photoionization (APPI)], where more components have an absorption band. One major compound class that has an absorption band at 248 nm is aromatic hydrocarbons. Therefore, APLI presents an excellent tool for petroleum analysis because of the high content of aromatic compounds. In this study, the recently developed APLI method was combined with high-resolution FT-ICR MS to study the range of characterized constituents in the SARA fractions.



MATERIALS AND METHODS

SARA Fractionation of Crude Oil. Heavy crude oil for this study was obtained from a North American source and stored under argon. The asphaltene fraction was precipitated from the corresponding heavy crude oil using n-heptane (HPLC grade, Merck, Germany). To obtain the asphaltene, a slightly modified SARA fractionation procedure was used (Scheme 1).23 A total of 30 mL of n-heptane/g of crude oil was added, and the mixture was refluxed for 2 h at 150 °C in a Soxhlet apparatus. The precipitated portion was filtered and dried under inert gas flow. The sample (with the filter) was extracted with 300 mL of toluene (HPLC grade, Overlack, Germany) in a Soxhlet apparatus until no color changes were observed. The redissolved asphaltene fraction was rotary-evaporated and, afterward, dried under a continuous stream of nitrogen. The extracted solution (maltenes fraction) was rotovapped until a stable mass was achieved. The dried maltenes were then diluted with n-heptane and Received: January 24, 2012 Revised: May 8, 2012 Published: May 8, 2012 3481

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Scheme 1. SARA Fractionation According to the Solubility of Each Fraction

mixed with activated alumina (80−200 mesh, Acros Organics, Germany). The slurry was dried and loaded on the top of a glass column, packed with neutral alumina sorbent. In sequence, n-heptane, toluene, and toluene/methanol (9:1, v/v) (HPLC grade, Baker, Germany) mixtures were used to elute saturates, aromatics, and resins. A total of 350 mL of solvent/g of maltenes was used for the chromatographic separation. Thin-layer chromatography was used to monitor the complete separation of each fraction. Finally, the fractions were rotary-evaporated to dryness and then weighed. To have a correct mass balance, the volatile part of the original sample was also determined using rotavap vapor at 26 mbar and 30 °C. The obtained mass balance and recovery is presented in Table 1.

and 0 < DBE < 40. A molecular formula was considered only if the corresponding 13C peak was also found. Radical cations and quasimolecular ions were distinguished and indicated separately (X, X[H], respectively). The calculated molecular formulas were sorted into compound classes based on their denoted Kendrick mass defects and their double bond equivalence (DBE) distribution.16 The obtained mass lists were transferred into Excel and Origin for data evaluation and preparation of the figures shown. Because of unknown response factors for each individual component, the class lists are based on the number of assigned elemental compositions rather than the summary of the intensities.



RESULTS AND DISCUSSION Bulk Property Comparison. Figure 1 shows the result of the SARA fractionation procedure. The heavy crude oil

Table 1. Calculated Weight Distribution within the Different Fractions fractions

wt %

volatiles saturates aromatics resins asphaltenes ∑

8.67 39.84 26.6 7.74 9.9 92.75

FT-ICR MS Analysis. Mass analysis was performed on a 12 T linear quadrupole ion-trap (LTQ) FT-ICR MS (Thermo Fisher, Bremen, Germany). The spectra were collected in positive mode using a laboratory-built APLI source16 and spectral stitching13,24,25 with a mass range of 100−1000. For the APLI measurements, pulsed laser radiation (50 Hz, 8 mJ) was obtained from a KrF* excimer laser (ATL Lasertechnik GmbH, Wermelskirchen, Germany) radiating at a wavelength of 248 nm. The sample was injected through the APCI nebulizer (Thermo Fisher, Bremen, Germany), and the generated cloud was ionized with the unfocused laser beam positioned between the MS orifice and the ion source exit. Typical APLI(+) conditions were a sample infusion flow rate of 20 μL/min, a nebulizing temperature of 240 °C, a sheath gas flow of 16 (arbitrary unit), and an auxiliary gas flow of 5 (arbitrary unit). The different fractions were diluted in toluene to a final concentration of 100 ppm. Because of the low concentration, no multimers were observed; hence, in-source fragmentation was not applied.7 Data Analysis. The data were collected and processed with the LTQ FT Ultra 2.5.5 (Thermo Fisher, Bremen, Germany) data acquisition system. The mass spectra were externally calibrated and resulted in a mass accuracy lower than 1 ppm. The peak lists were converted to molecular formulas by Composer (Sierra Analytics, Modesto, CA). The following chemical constraints were applied: number of H unlimited, 0 < C < 100, 0 < O < 3, 0 < N < 3, 0 < S < 3,

Figure 1. Picture of all fractions obtained from the SARA procedure.

exhibited an extremely high viscosity and non-Newtonian flow behavior. The asphaltene fraction can be described as black−gray dry flecks, which, upon removal from the crude oil, completely changed the viscosity of the maltenes fraction, resulting in a less viscous brownish fluid. The saturates fraction was observed as a bright green liquid with the lowest viscosity. The aromatics showed similar properties to the maltenes. The resins fraction was a sticky, dark brown matter. The sum of the weight percentage of the individual fractions was around 93%, representing a very good yield considering the numerous steps of the SARA procedure. The obtained maltenes, saturates, aromatics, resins, asphaltenes, and the original crude oil were measured with APLI−MS, and the obtained broadband and expanded views of mass spectra are shown in Figure 2. The maltenes, saturates, and aromatics showed almost identical distribution compared to the original crude oil sample, 3482

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Figure 2. APLI−FT-ICR mass spectra of the nonfractionated crude oil (top), asphaltenes, maltenes, saturates, aromatics, and resins in positive ionization mode for the mass range of 150−1000 Da (left column) and the corresponding enlarged section at 346 Da (right column) with the assigned molecular formulas.

Figure 3. Number of assigned formulas found in the different fractions and the bulk crude oil.

occupying the same mass range of m/z 150−900, with a maxima around m/z 350. The asphaltene and resin fractions covered a lower and narrower mass range. An expanded segment (ranging over 0.3 Da) was also selected to observe the changes in the distribution within a nominal mass. All six spectra exhibit an average mass resolving power of 810 000 at m/z 346. The enlarged section immediately reveals two interesting aspects of the SARA fractionation. First, a significant increase in the number of the assigned peaks was observed. Only 11 individual molecules could be assigned over the selected 0.3 Da mass window when the bulk

crude oil was analyzed. However, following fractionation, an additional seven molecules were assigned when data from the corresponding mass window of the different fractions were compiled. Second, distribution changes and similarities in the composition can be depicted. The enlarged view of the bulk and maltenes fractions shows identical spectra, while the saturate and asphaltene fractions showed the largest differences. The saturates emphasize the upper mass range, while the asphaltenes show higher response in the lower mass range. This phenomenon could be due to the number of H atoms in the 3483

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molecule and its positive mass defect. Asphaltenes are known to contain condensed aromatic structures, where the H/C ratio is significantly lower than in the constituents in the saturated fraction. An increased number of H (saturation) increased the observed mass defects and resulted in higher values when the constituents of the saturated fractions were investigated. The overall numbers of assigned molecular formulas from the different fractions are summarized in Figure 3. Only signals with a magnitude above a threshold of 3× the standard deviation of the baseline noise (3σ) were processed. The outcome shows that APLI−MS delivered fewer constituents for crude oil (7884) than for the maltenes (8765) and saturates (8905). Alone, this observation suggests a significant increase in peak assignment when SARA fractionation is used. The presented data are filtered for similarities in molecular formulas and theoretical masses to deduct information on the exact increase of the assigned molecules and to understand which components are present in the fractions or are maybe discriminated within the original crude oil. This will be discussed later. Class and DBE Distribution. The distribution of constituents can be observed when the peaks are sorted into compound classes based on their denoted mass defects (Figure 4). The classes can be easily visualized on the basis

Figure 5. DBE distribution of the individual compound classes. Scaled in the third axis according to the number of assigned molecules.

heteroatom-containing classes, such as Nn, Oo, and Ss. The contribution of the most dominant compound class types within each fraction were also calculated on the basis of the assigned number of molecules and presented in Table 2. The analysis of the bulk crude oil showed a pronounced presence of the pure hydrocarbon and N1 compound classes with a DBE range of 5−30. The S1 class also contributed significantly (approximately with 16%) to the complete number of assigned peaks in the crude oil; however, the observed DBE range was more restricted than for the N1 class and does not exceed 25. The maltenes showed minor differences in comparison to the bulk material, except for the significant increase in the OS class. As maltenes were divided into further subclasses, such as aromatics, saturates, and resins, changes in the distribution were still observed. The N1 class was distributed over the three subclasses; however, the N2 class appeared only in the resins. This may indicate that the constituents of the N2 class are highly polar compared to those species that have only one N in their structure. Furthermore, the resins fraction incorporated the highest amount of heteroatom content and only about 7% of pure hydrocarbons. Besides the OS class, no S-containing compound classes were detected in this fraction. The sulfur content of the maltenes was divided between the aromatics and saturates. While the analysis of the maltenes fraction delivered only a 2.6% of S 2 contribution, a further separation of the sample into saturates

Figure 4. Population-based compound classes within the assigned formulas.

of the number of assigned peaks. This population-based distribution eliminates differences caused by the signal intensities derived from differences in ionization efficiency. The corresponding DBEs were also investigated and plotted in Figure 5. A total of 15 different compound classes were considered as a frame to visualize the differences. The compounds were observed in either radical or quasi-molecular ion form. The most dominant classes were the pure hydrocarbons and the 3484

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Table 2. Contribution in Percentage of the Seven Most Abundant Compound Classes in Crude Oil, Asphaltenes, Maltenes, Saturates, Aromatics, and Resins compound class

crude (%)

asphaltenes (%)

maltenes (%)

saturates (%)

aromatics (%)

resins (%)

HC N N2 O O2 S S2

17.7 18.4 6.1 10.1 8.3 15.8 0

17.7 21.6 6.1 11.6 7.6 10.4 0

16.1 15.7 5.3 9.4 7.6 14.7 2.6

16.4 9.1 0 12.3 10.5 20.2 10.2

15.2 24.0 0 8.8 6.6 12.6 8.6

6.9 21.5 16.9 9.2 3.7 0 0

Figure 6. Aromaticity distribution within the different fractions. The individual constituents were truncated (with the bin size of 0.05 DBE/C unit), and their aromaticity (DBE/C) distributions were shown for all assigned molecules. The distributions are represented as single block bar plots with the corresponding number of assigned molecules, with the mean values denoted as bar charts.

slightly decreased average aromaticity. As expected, the precipitated asphaltenes fraction showed a rather pronounced aromaticity, with a highest mean of 0.52.7,28 The first fraction of the maltenes, the saturates, denoted the lowest average aromaticity with a rather pronounced appearance at the lower end of the DBE/C scale. This confirmed the original description of the saturates fraction, which comprises the aliphatic and alicyclic portions of the crude oil. Surprisingly, the aromatic fraction showed lower aromaticity than the asphaltenes and even lower than the resins. The resins, also known as the precursors and peptizing agents for the asphaltenes, showed very similar distribution and average aromaticity in comparison to the asphaltenes.4 However, the resins fraction showed a completely different compound class distribution from that of the asphaltenes (Figure 4). To visualize the potential effect of ion suppression during ionization, the unique constituents found exclusively in their corresponding fractions were calculated. The outcome of the six samples was compared and presented in Figure 7. The fractionation caused the biggest impact on the yield of the unique assigned peaks in the case of the resins. A total of 1271 new molecules were found of the 5289 (Figures 3 and 7) assigned constituents when fractionation occurred. The other major difference was observed in the saturates fraction. After the precipitation and fractionation, 4451 unique formulas were assigned, delivering almost a 60% increase of assigned molecules. The comparison clearly demonstrates that more

and aromatics resulted in higher S2 proportions. A total of 930 of 8905 and 536 of 6212 species were assigned as S2 in the saturates and aromatics fractions, respectively, while only 227 of 8765 were assigned for the maltenes. This indicates that the S2 species are less polar compounds with lower ionization efficiency based on the fact that these species were not present in the mass spectrum of the bulk crude oil sample and showed a negligible contribution in the maltenes. The S2 content can be further subdivided on the basis of aromaticity (Figure 5). As expected, saturates tend to comprise the less aromatic portions (5−15 DBE) and the aromatics fraction contains the S2 content with higher aromaticity (15−25 DBE). Aromaticity and Condensed Aromatic Structures. A DBE normalized to the number of carbons (DBE/C) delivers information about the corresponding aromaticity. This method was successfully demonstrated to follow the in situ degradation of charcoal in soils and the description of black carbon content in the environment.26,27 For the individual compounds, the DBE/C values were calculated, and to visualize the distribution of aromaticity, the results were truncated with 0.05 DBE/C and plotted in Figure 6. The box chart type of distribution has been highlighted to show the mean values of aromaticity of the different fractions. The bulk crude oil showed a broad and centered aromaticity distribution over the range of 0.1−0.9, with a mean value of 0.45. The maltenes fraction was found to produce an almost identical distribution over the same DBE/C range with a 3485

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for each individual fraction (Figure 8). The application of the DBE/C ≥ 0.7 value is rather restrictive, and although it eliminates a significant amount of potential polycondensated structures, we investigated this section of the complete data sets. Approximately 7.5% of the assigned structures fulfilled the applied criteria in the case of the bulk crude oil. The asphaltene fraction, as expected, denoted a significantly higher, 13% (628 of 4928), CARS proportion followed by the resins fraction with 12%.5 Surprisingly, the saturates fraction, with the lowest expected aromaticity, delivered 170 potential candidates for condensed structures. However, this was only 2% of the assigned structures within the saturates fraction. The compound class distributions within the CARS components were also calculated and compared to the complete sample (see Figure 4 and Table 2). The role of pure hydrocarbons in the condensed aromatic structures was significantly higher (on average with an increase of 10%) than in the complete sample, especially in the cases of the saturates (increased from 16 to 44%) and the resins. The N contribution remained almost identical when the CARS components are compared to the complete sample. These results suggest that most of the condensed aromatic structures are pure hydrocarbons with limited heteroatom content. Furthermore, the majority of the condensed structures with heteroatom content are restricted to a single heteroatom. These results are in good agreement with earlier findings, especially when structures containing sulfur as the heteroatom were investigated within the SARA fractions.20

Figure 7. DBE distribution of the unique assigned molecules within the different fractions.

information can be obtained combining the results from the SARA fractions than from the crude oil alone, as observed especially in Figure 7, where the unique compound assignments are summarized. On the basis of these findings, we concluded that a “sample-simplification step”, such as the SARA fractionation, aids in the understanding of the selected heavy crude oil sample because the matrix effect can be reduced significantly if a fractionation step is included in the method. However, the data that are shown in Figure 7 raise some questions about the efficiency of this separation procedure. First, the differences between the bulk sample and the maltenes were almost negligible. It seems that the precipitated asphaltenes show pronounced similarities with the bulk material and the maltenes, as seen in detail in Figures 4 and 5. These results may suggest a possible co-precipitation of the smaller constituents with the larger asphaltene-type molecules, despite using Soxhlet extraction for sample preparation. The relatively low amount of unique molecules in the asphaltenes and an expected high average DBE value support this theory.6,7 These co-precipitated constituents suppress the asphaltenes because their ionization efficiencies tend to be higher. A DBE/C value of 0.7 serves as a criterion for identifying species with condensed aromatic ring structures (CARS),27 and an absolute upper limit of 0.9 was used as the boundary of hydrocarbon compositional space.29 A DBE/C ≥ 0.7 value can only be reached by a polycyclic aromatic structure; therefore, molecules within this range must contain one or more aromatic cores.28 Considering this fact, we calculated the number of assigned formulas that must contain a condensed aromatic core



CONCLUSION In this work, APLI−FT-ICR MS was applied using a heavy crude oil to investigate the results of SARA fractionation. APLI coupled to ultrahigh-resolution MS was found to be a very effective technique for characterizing compositional changes on a molecular level induced by the fractionation procedure. The properties of the different fractions, such as aromaticity, could be followed and differentiated using this ionization method. The highly aromatic character of the asphaltene fraction was also confirmed. Once the unique constituents of each fraction were selected, a significant increase in the number of the assigned molecules was found when compared to results obtained from the bulk crude oil. Furthermore, it was also shown that the saturated constituents, with low aromaticity, probably have relatively low ionization efficiencies, because this fraction delivered the highest amount of unique peaks. Overall, it can be stated that SARA fractionation and APLI combined with high-resolution MS can increase the depth of data analysis and provide a better understanding of crude oil analysis.

Figure 8. Bar chart represents the obtained number of molecules with condensed aromatic structures. The corresponding compound class distribution (in percentage) for each ionization technique is shown in the pie charts, color-coded on the basis of the classes. 3486

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using atmospheric pressure laser ionization and Fourier transform ion cyclotron resonance mass spectrometry (APLI FT-ICR MS). Analyst 2008, 133 (7), 867−869. (17) Fan, T. G.; Buckley, J. S. Rapid and accurate SARA analysis of medium gravity crude oils. Energy Fuels 2002, 16 (6), 1571−1575. (18) Fuhr, B.; Scott, K.; Dettman, H.; Salmon, S. Fractionation of bitumen by distillation, SARA analysis and gel permeation chromatography. Abstr. Pap. Am. Chem. Soc. 2005, 229, U607−U607. (19) Kharrat, A. M.; Zacharia, J.; Cherian, V. J.; Anyatonwu, A. Issues with comparing SARA methodologies. Energy Fuels 2007, 21 (6), 3618−3621. (20) Cho, Y.; Kim, Y. H.; Kim, S. Planar limit-assisted structural interpretation of saturates/aromatics/resins/asphaltenes fractionated crude oil compounds observed by Fourier transform ion cyclotron resonance mass spectrometry. Anal. Chem. 2011, 83 (15), 6068−6073. (21) Woods, J.; Kung, J.; Kingston, D.; Kotlyar, L.; Sparks, B.; McCracken, T. Canadian crudes: A comparative study of SARA fractions from a modified HPLC separation technique. Oil Gas Sci. Technol. 2008, 63 (1), 151−163. (22) Constapel, M.; Schellentrager, M.; Schmitz, O. J.; Gab, S.; Brockmann, K. J.; Giese, R.; Benter, T. Atmospheric-pressure laser ionization: A novel ionization method for liquid chromatography/mass spectrometry. Rapid Commun. Mass Spectrom. 2005, 19 (3), 326−336. (23) Vazquez, D.; Mansoori, G. A. Identification and measurement of petroleum precipitates. J. Pet. Sci. Eng. 2000, 26 (1−4), 49−55. (24) Southam, A. D.; Payne, T. G.; Cooper, H. J.; Arvanitis, T. N.; Viant, M. R. Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray Fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method. Anal. Chem. 2007, 79 (12), 4595−4602. (25) Weber, R. J. M.; Southam, A. D.; Sommer, U.; Viant, M. R. Characterization of isotopic abundance measurements in high resolution FT-ICR and orbitrap mass spectra for improved confidence of metabolite identification. Anal. Chem. 2011, 83 (10), 3737−3743. (26) Hockaday, W. C.; Grannas, A. M.; Kim, S.; Hatcher, P. G. Direct molecular evidence for the degradation and mobility of black carbon in soils from ultrahigh-resolution mass spectral analysis of dissolved organic matter from a fire-impacted forest soil. Org. Geochem. 2006, 37 (4), 501−510. (27) Hockaday, W. C.; Grannas, A. M.; Kim, S.; Hatcher, P. G. The transformation and mobility of charcoal in a fire-impacted watershed. Geochim. Cosmochim. Acta 2007, 71 (14), 3432−3445. (28) Sabbah, H.; Morrow, A. L.; Pomerantz, A. E.; Zare, R. N. Evidence for island structures as the dominant architecture of asphaltenes. Energy Fuels 2011, 25 (4), 1597−1604. (29) Hsu, C. S.; Lobodin, V. V.; Rodgers, R. P.; McKenna, A. M.; Marshall, A. G. Compositional boundaries for fossil hydrocarbons. Energy Fuels 2011, 25 (5), 2174−2178.

AUTHOR INFORMATION

Corresponding Author

*Telephone: +49-0-208-306-2230. Fax: +49-0-208-306-2982. E-mail: [email protected]. Notes

The authors declare no competing financial interest.



REFERENCES

(1) Swain, E. J. Sulfur, coke and crude qualityConclusion: United States crude slate continues to get heavier, higher in sulfur. Oil Gas J. 1995, 93 (2), 37−42. (2) McKenna, A. M.; Purcell, J. M.; Rodgers, R. P.; Marshall, A. G. Heavy petroleum composition. 1. Exhaustive compositional analysis of Athabasca bitumen HVGO distillates by Fourier transform ion cyclotron resonance mass spectrometry: A definitive test of the Boduszynski model. Energy Fuels 2010, 24, 2929−2938. (3) Betancourt, S. S.; Ventura, G. T.; Pomerantz, A. E.; Viloria, O.; Dubost, F. X.; Zuo, J.; Monson, G.; Bustamante, D.; Purcell, J. M.; Nelson, R. K.; Rodgers, R. P.; Reddy, C. M.; Marshall, A. G.; Mullins, O. C. Nanoaggregates of asphaltenes in a reservoir crude oil and reservoir connectivity. Energy Fuels 2009, 23, 1178−1188. (4) Hammami, A.; Ratulowski, J. Precipitation and deposit of asphaltene in production systems: A flow assurance overview. In Asphaltenes, Heavy Oils and Petroleomics; Mullins, O. C., Sheu, E., Hammami, A., Marshall, A. G., Eds.; Springer Science: New York, 2007; pp 617−660. (5) Mullins, O. C. Review of the molecular structure and aggregation of asphaltenes and petroleomics. SPE J. 2008, 13 (1), 48−57. (6) Andrews, A. B.; Edwards, J. C.; Pomerantz, A. E.; Mullins, O. C.; Nordlund, D.; Norinaga, K. Comparison of coal-derived and petroleum asphaltenes by 13C nuclear magnetic resonance, DEPT, and XRS. Energy Fuels 2011, 25 (7), 3068−3076. (7) Mullins, O. C. The modified Yen model. Energy Fuels 2010, 24, 2179−2207. (8) Hemmingsen, P. V.; Silset, A.; Hannisdal, A.; Sjoblom, J. Emulsions of heavy crude oils. I: Influence of viscosity, temperature, and dilution. J. Dispersion Sci. Technol. 2005, 26 (5), 615−627. (9) Riveros, L.; Jaimes, B.; Ranaudo, M. A.; Castillo, J.; Chirinos, J. Determination of asphaltene and resin content in Venezuelan crude oils by using fluorescence spectroscopy and partial least squares regression. Energy Fuels 2006, 20 (1), 227−230. (10) Savory, J. J.; Kaiser, N. K.; McKenna, A. M.; Xian, F.; Blakney, G. T.; Rodgers, R. P.; Hendrickson, C. L.; Marshall, A. G. Parts-perbillion Fourier transform ion cyclotron resonance mass measurement accuracy with a “walking” calibration equation. Anal. Chem. 2011, 83 (5), 1732−1736. (11) Hertkorn, N.; Ruecker, C.; Meringer, M.; Gugisch, R.; Frommberger, M.; Perdue, E. M.; Witt, M.; Schmitt-Kopplin, P. High-precision frequency measurements: indispensable tools at the core of the molecular-level analysis of complex systems. Anal. Bioanal. Chem. 2007, 389 (5), 1311−1327. (12) Hsu, C. S.; Hendrickson, C. L.; Rodgers, R. P.; McKenna, A. M.; Marshall, A. G. Petroleomics: Advanced molecular probe for petroleum heavy ends. J. Mass Spectrom. 2011, 46 (4), 337−343. (13) Gaspar, A.; Schrader, W. Expanding the data depth for the analysis of complex crude oil samples by Fourier transform ion cyclotron resonance mass spectrometry using the spectral stitching method. Rapid Commun. Mass Spectrom. 2012, 26 (9), 1047−1052. (14) Klein, G. C.; Angstrom, A.; Rodgers, R. P.; Marshall, A. G. Use of saturates/aromatics/resins/asphaltenes (SARA) fractionation to determine matrix effects in crude oil analysis by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Energy Fuels 2006, 20 (2), 668−672. (15) Panda, S. K.; Andersson, J. T.; Schrader, W. Mass-spectrometric analysis of complex volatile and nonvolatile crude oil components: A challenge. Anal. Bioanal. Chem. 2007, 389 (5), 1329−1339. (16) Schrader, W.; Panda, S. K.; Brockmann, K. J.; Benter, T. Characterization of non-polar aromatic hydrocarbons in crude oil 3487

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