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Characterization of asphaltenes precipitated at different solvent power conditions using Atmospheric Pressure Photoionization (APPI), and Laser Desorption Ionization (LDI) coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) Matthias Witt, Markus Godejohann, Sven Oltmanns, Michael E. Moir, and Estrella Rogel Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b02634 • Publication Date (Web): 12 Dec 2017 Downloaded from http://pubs.acs.org on December 12, 2017
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Characterization of asphaltenes precipitated at different solvent power conditions using Atmospheric Pressure Photoionization (APPI), and Laser Desorption Ionization (LDI) coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) Matthias Witt,1 Markus Godejohann,2 Sven Oltmanns,3 Michael Moir,4 Estrella Rogel4 1 2
Bruker Daltonik GmbH, Bremen, Germany.
Bruker BioSpin GmbH, Rheinstetten, Germany. 3
4
Bruker Optik GmbH, Bremen, Germany.
Chevron Energy Technology Company, Richmond, CA 94801, USA. ABSTRACT
In the present work, asphaltenes obtained using different n-heptane to crude oil ratios (HCOR) were analyzed using Atmospheric Pressure Photoionization (APPI), and Laser Desorption Ionization (LDI) coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS). The main objective was to improve the understanding of the components of the crude oil that precipitate under different solvent power conditions.
Analysis of the
compositional distribution of the asphaltenes reveals that the decrease in solvent power produces an increase in DBE and the number of heteroatoms per molecule while the carbon number remains almost unaltered. This finding seems to indicate that one of the main drivers for precipitation is aromaticity as the heptane/crude oil ratio (HCOR) increases and consequently, the solvent power decreases. Both, APPI and LDI FT-ICR MS produce average values that describe the general tendencies obtained using other techniques. Additionally, APPI FT-ICR MS closely match bulk data of the most aromatic asphaltenes obtained in this study.
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INTRODUCTION In 1905, Richardson coined the words “maltenes” and “asphaltenes” with the caution that these names should not lead persons to believe that they belong to definite compounds.1 More than 100 years later, petroleum chemists are still struggling, although in a different way, with these concepts. Asphaltenes are defined as a solubility class: insoluble in n-heptane and soluble in toluene. However, asphaltenes are just a part of an incredibly complex fluid containing thousands of different molecules and which of these molecules precipitate in heptane depends on many factors. In fact, changes in temperature,2-3 solvent/crude oil ratio,4-5 contact time,5 and washing of the filter cake4,6
produce different “asphaltenes” from the same crude oil. Most of the
time, the effect of these variables in molecular distributions has been examined regarding average properties of the asphaltenes.2,4 Detailed examination of the asphaltenes has revealed that this solubility class contains numerous molecules that cannot strictly be considered asphaltenes as they are soluble in n-heptane.7,8 Recently, sequential asphaltene extraction has been carried out to try to expel as much as possible of this soluble material from precipitated asphaltenes.8 All these results raise again the question of which is the best method to extract asphaltenes. However, an even more important subject is the understanding of how the precipitated material varies with solvent power. Besides the direct application to the development of better extraction procedures, understanding the nature of the precipitated material can have a great impact on the development of deposition models and the handling of asphaltenic deposits. For instance, solvent power or the ability of a solvent to completely or partially dissolve a solute, plays an important role when different hydrocarbons are injected downhole to improve crude oil recovery.9,10 In solvent injection processes such as Vapex or N2 ACS Paragon Plus Environment
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solv,11,12 the selection of the solvent is key as plugging risk, emulsion formation and improved recovery should be balanced to optimize operations. In a recent study,14 it was found that the precipitated material varies significantly: at low solvent/crude oil ratios, the precipitated material is composed mainly by maltenes or heptanesolubles, while at higher ratios, it becomes dominated by asphaltenes or higher aromaticity components of the crude oil. This study, as well as previous ones,2,4,5 demonstrated that the characteristics of the precipitated material change significantly depending on the solvent/sample ratio. In the present work, a detailed examination of the molecular distributions of asphaltenes precipitated at different solvent conditions is carried out using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS). Over the last few years, the development of FT-ICR MS has enabled the characterization of the compositional distributions of crude oils and petroleum-related materials15-23 giving the capability to identify compositional differences that might be undetectable using other techniques. However, FT-ICR MS results for these complex mixtures should be analyzed with some caution. Crude oils are very complex with a wide variety of different species, and detection of molecules depends on the applied ionization technique17,24. For the same reason, quantification in these complex systems cannot be accomplished. As mentioned before, in the present work, we used FT-ICR MS to examine the variations of the compositional distributions in precipitates obtained at different heptane/crude oil ratios (HCOR). Specifically, we will look for variations in the composition as a function of the solvent power (heptane/crude oil ratio) using two different ionization methods: atmospheric pressure photoionization (APPI) and laser desorption ionization (LDI). APPI in positive ion mode can efficiently ionize polycyclic aromatic compounds including those with heteroatoms.25-26 On the
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other hand, LDI has been successfully used to study crude oils and their heavy components because aromatic ring structures can efficiently absorb photons in the UV wave length of the laser.27 In the case of asphaltenes, there is evidence of a qualitative agreement between the molecular information provided by these MS techniques and the data obtained using more conventional analytical methods such as fluorescence, FTIR, etc.19,28 In this work, we cover a wide range of precipitation ratios from HCOR=1 to HCOR=100. In particular, we are interested in the precipitation at high solvent power since it resembles the initial conditions of asphaltene precipitation. This condition also corresponds to the flocculation onset determined by titration to evaluate the tendency towards precipitation of asphaltenes from crude oils. Our main goal is to get a better understanding of the components of the crude oil that precipitate under different solvent conditions. Additionally, we attempt to correlate the molecular distributions observed with the solubility behavior and other properties previously determined for the same set of samples.14
EXPERIMENTAL SECTION Materials. n-Heptane was used to induce asphaltene precipitation at room temperature. Different n-heptane/sample ratios from 1 to 100 were used. Flocculation onset experiments using n-heptane as precipitant agent indicated that precipitation starts at an n-heptane/crude oil ratio (HCOR) of 1.5. Blends prepared with an HCOR of 1 did not show precipitation at least during the first twelve hours. Solutions are prepared by mixing 10 mL of sample with the corresponding volume of nheptane and shaking vigorously for 10 min in a shaker. After blending, the solutions are kept at room temperature at static conditions for 24 hours. Blends were filtered using a Teflon 4 ACS Paragon Plus Environment
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membrane filter with an average pore size of 0.2 microns so that particles could be recovered and analyzed. Filtered cakes were collected without any washing. They were dried under nitrogen atmosphere and analyzed. Elemental analysis of the samples is shown in Table 1. FT-ICR MS Analysis. The samples were analyzed using a solariX 2XR FT-ICR mass spectrometer (Bruker Daltonik GmbH, Bremen, Germany) equipped with a 7 T refrigerated actively shielded superconducting magnet (Bruker Biospin, Wissembourg, France) and the ParacellTM analyzer cell. The spectra were acquired in 2 omega mode. This is equivalent to quadrupole phase detection.29 The Apollo II Dual ESI/MALDI ion source was used. Samples were analyzed using positive ion mode for both ionization methods, APPI and LDI. The transient length of the mass spectrometric measurements was 2.9 seconds. Half sine apodization was applied, and spectra were processed in absorption mode resulting in a resolving power of 1,300,000 at m/z 400. The spectra were externally calibrated with NaTFA clusters in electrospray ionization in positive ion mode. Spectra were single point calibrated during acquisition with a known mass (lock mass calibration). The final spectrum was additionally internally calibrated in DataAnalysis 4.4 (Bruker Daltonics) with the homologous N1 series for LDI and hydrocarbon series for APPI using quadratic calibration. All RMS mass errors of the internal calibration were below 150 ppb. The RMS mass errors of the calculated molecular formulas of all compound classes for the LDI and APPI measurements was in average 167 ppb and 150 ppb, respectively. Samples were prepared by diluting them 1:20 in toluene as stock solution. The stock solution was diluted 1:1000 in 10/90 CH3OH/toluene for final spray solution (50 ppm). This solution was directly injected to the APPI source with a syringe pump at a flow rate of 50 µL/min. The ion accumulation time was 10 ms, and 300 single scans were added for final mass spectrum. The 5 ACS Paragon Plus Environment
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stock solution was applied on a stainless steel target for the LDI measurements. LDI spectra were acquired using 50 – 150 laser shots for each scan using a low laser power of 4.5 % with minimum laser focus to reduce fragmentation of labile species during ionization. 300 scans were added for the final mass spectrum. Internal mass calibration, spectral interpretation, and export of mass lists were performed using DataAnalysis 4.4 (Bruker Daltonics). The analysis of the data including calculation of molecular formulas and relative abundances of compound classes were performed using PetroOrg 10.0 (Florida State University). Elemental composition assignment was based on Kendrick mass defect sorting. A maximum mass error of 0.5 ppm and a maximum number of heteroatoms of N=3, O=3, and S=3 were allowed for molecular formula calculation. Doublebond- equivalents (DBE) were calculated using the standard equation.30 The isotopic peaks (13C, 34
S, etc.) were calculated in the algorithm of the PetroOrg software. Protonated species and
radical cations compound classes were calculated separately in the PetroOrg software. Weighted average intensities were calculated using both protonated species and radical cations. FT-IR Analysis. The samples were analyzed with a ALPHA FT-IR spectrometer (Bruker Optics, Ettlingen, Germany) using a single reflection ATR module and a ZnSe crystal. Samples were measured between 600 cm-1 and 4000 cm-1 with a resolution of 4 cm-1 in ATR mode (attenuated total reflection). 1
H-NMR Analysis. The samples were analyzed with an Advance III HD NMR 600 MHz
spectrometer equipped with a 5 mm BBO cryo probe (Bruker Biospin, Rheinstetten, Germany). Samples were measured in 5 mm NMR tubes after dissolution in CDCl3. Proton spectra were recorded by accumulation of 32 free induction decays collected into 262144 complex data points
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with a sweep width of 59523.809 Hz setting the offset to 3706.05 Hz. The relaxation delay was set to 10 s. Prior to Fourier transformation, the FID was multiplied with an exponential function leading to a line broadening of 0.3 Hz. No zero filling was applied. Spectra were referenced to the CDCl3 signal at 7.2 ppm. Integration of the aromatic and aliphatic regions was done with AMIX (Bruker Biospin, Rheinstetten, Germany). The integral range for the aliphatic region was set between 4.3 and 0.2 ppm. The integral range for the aromatic region was set between 9.4 and 6.2 ppm. The area of the chloroform-d1 signal was finally subtracted from the area of the aromatic protons.
RESULTS AND DISCUSSION
Class Distributions. Class distribution plots for asphaltenes obtained at different HCOR (nheptane/crude oil ratios) are shown in Figure 1 based on weighted average intensities considering radical cations as well as protonated species generated by positive LDI and positive APPI. In this plot, HC classes, as well as classes containing one heteroatom become less abundant as HCOR increases. The opposite happens for most classes containing two or more heteroatoms. These plots indicate that molecules with many heteroatoms preferentially incorporated themselves in the aggregates that precipitate at lower solvent power (high heptane content-high HCOR).
This enrichment in heteroatoms is associated to larger aromaticities as will be
discussed in the next section. Average relative intensities for classes containing different numbers of heteroatoms as a function of the concentration of n-heptane can be found in the Supporting Information (SI). It is important to point out that the amount of precipitate collected
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increases as the solvent power decreases (higher HCOR) indicating that some species that precipitate at high solvent power do not precipitate as more n-heptane is added.14 DBE and Carbon number. Figure 2 shows a comparison of the DBE distributions (calculated based on weighted relative abundances using positive APPI) as a function of HCOR. The distributions shift to the right as this ratio increases indicating that asphaltenes become more aromatic as the solvent power decreases. The average DBE increases from 11.6 (HCOR=1) to 15.3 (HCOR=100). Increase in DBE as solvent power decreases are also observed using positive LDI (see SI). Using this technique, the average DBE moves from 16.6 to 23.3. These tendencies agree with the decrease in H/C molar ratio shown in Table 1. In contrast, carbon number distributions do not show a clear tendency using positive APPI (Figure 3). In fact, average carbon number differences do not exceed 1.5 indicating that carbon numbers do not change significantly with solvent power. LDI results indicate slightly larger carbon differences, an increase in almost 3 carbons from HCOR=1 to 100 (see SI). Analysis of individual classes shows similar tendencies (SI). All classes show a significant increase in average DBE as the solvent power decreases while carbon numbers show slight variations. Therefore, the aromaticity increases significantly. Figure 4 compares the distributions of aromaticity according to weighted relative abundances using APPI. Aromaticity was calculated as DBE/(C+N).31 As shown in Figure 4, distributions shift to larger values as the HCOR increases. Aromaticity was also evaluated using IR and 1H-NMR spectroscopy. The comparison of the IR spectra (SI) indicates that the signals corresponding to aromatic moieties increase significantly as HCOR increases. If the extinction coefficients of the aromatic and aliphatic C-H 8 ACS Paragon Plus Environment
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groups do not vary much among the asphaltene samples, the ratio of the bands 1600 cm-1 and 2920 cm-1 can be considered a measure of the aromaticity. These results agree with 1H-NMR measurements using the ratio of aliphatic proton (4.3 and 0.2 ppm) to aromatic proton (9.4 and 6.2 ppm) for detection of aromaticity in the sample. These ratios are shown in Figure 5 in comparison to the average values calculated based on relative abundances (positive ion-mode APPI). Another calculation indicates, as expected that the number of heteroatoms per molecule increases as the amount of heptane increases and the solvent power decreases. Figure 6 presents a plot of the average number of heteroatoms per molecule as a function of the percentage of nheptane volume used to extract the asphaltenes. We found that the average number of heteroatoms correlates with the average DBE as shown in the insert plot of Figure 6 using both ionization techniques. In contrast, correlations with average carbon numbers are poor as shown in the Supporting Information. The correlation between DBE and heteroatom content poses a problem to decouple the effect of heteroatoms and the effect of large polyaromatic rings regarding precipitation tendencies indicating that most heteroatoms in asphaltenes are associated with aromatic rings. It can be assumed that there might be some bias in the use of these ionization techniques since they both target aromatic structures. However, it is important to notice that correlations shown in Figure 6 for both techniques yield the same slope indicating a strong relationship between the growth of the polyaromatic ring and the increase in the number of heteroatoms. On the other hand, some heteroatoms such as nitrogen are, in fact, associated mainly with aromatic structures.32 This is not the case for sulfur.33,34 Detailed evaluation of the species that are observed in some of the precipitated asphaltenes but not in others can help to evaluate changes in the compositional distribution that led to the 9 ACS Paragon Plus Environment
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increase of aromaticity and DBE as the solvent power decreases. For instance, Figure 7 shows a comparison of the compositional distribution of the molecules that are unique to the asphaltenes obtained at HCOR=1 and HCOR=100 using APPI in positive ion mode. We found that around 26 % of the species identified corresponding at HCOR=1 are not present at HCOR=100. On the other hand, 33 % of the species at HCOR=100 are not found at HCOR=1. These unique species represent those molecules that are solubilized when the solvent power decreases from HCOR=1 to 100 in comparison with those that precipitated under the same conditions. In this figure, DBE distributions show that the molecules that are solubilized from the filter cake when solvent power decreases are those with lower DBE while the ones that precipitated are those with higher DBE. Calculation of the average DBE of these molecules indicates that the ones that are uniquely observed in the filter cake obtained at HCOR=1 have an average DBE of 13.0, while the ones that are uniquely observed at HCOR=100 have an average of 25.2. The insert plots in Figure 8 also shows the C distributions for both sets of molecules. Regarding changes in carbon number, the unique molecules at low solvent power are slightly smaller (average C: 45.5) that the unique ones at high solvent power (47.5). However, this last set of molecules shows a wider distribution, maybe the product of many trapped molecules. We also found that the average number of heteroatoms increases from 2.03 to 2.40 when both sets of molecules are compared. The distribution of heteroatoms is also shown in Figure 7. Equivalent results were found when LDI is used. An increase in average DBE from 17.3 to 30.0 with no significant differences in carbon number and an average number of heteroatoms that increases from 1.49 to 2.67 was observed by LDI. Differences in molecular species in the precipitated asphaltenes are also observed when we compare compositional distributions at high solvent power. For example, a comparison of 10 ACS Paragon Plus Environment
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asphaltenes obtained at HCOR =1 and HCOR =1.5 shows that around 20 % of the detected species at HCOR=1 are not observed when HCOR is 1.5 (APPI). As in the previous comparison, the average DBE of the molecules that might get solubilized is lower than the average DBE of those that appear to be precipitated (12.6 vs. 18.5). In contrast, average C values do not change (48.1 vs. 48.6). On the other hand, the comparison between HCOR=10 and HCOR=100 does not show significant differences between both sets of molecules in average DBE values (19.9 vs. 19.3) or average carbon number (46.0 vs. 48.0). Figures showing the compositional distribution of these species and DBE distributions can be found in the Supporting Information. According to these results, the more soluble molecules precipitate at low ratios and then, as the solvent power decreases, they re-dissolve while molecules that are more aromatic precipitate. This exchange seems to be contrary to the common belief that the first molecules to precipitate when the precipitation is just beginning at high solvent power are the less soluble. In fact, it is well accepted that aromaticity is one of the primary drivers of the low solubility of the asphaltenes. So, it might be expected that at high solvent power, the first molecules to precipitate are those that are the more aromatic and, therefore, the less soluble. This behavior has not been observed when different ratios of solvent are used to precipitate asphaltenes.14 At high solvent power (low HCOR), a significant portion of the molecules that precipitate cannot be considered as asphaltenes, and it has been shown that they are not the least soluble as expected.14 In fact, several studies have pointed out that plentiful of molecules present in the crude oil co-precipitate with asphaltenes and remain in the precipitated material even after significant soxhlet extraction procedures.7,8 Studies have shown7,35 that some of the molecules that co-precipitated with asphaltenes, i.e. resins, interact mainly by the stacking of the aromatic regions with London dispersion forces dominating the aggregation.36 The trapping of other molecules inside 11 ACS Paragon Plus Environment
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asphaltene nano-structures is also supported by extensive research aimed to use these trapped molecules as biomarkers.37-38 In particular, these trapped molecules can preserve original geochemical information in comparison to free counterparts in crude oil that go under thermal alteration and biodegradation processes.39 This behavior indicates that some of these molecules have been associated to asphaltenes for geological periods, but they are not considered asphaltenes regarding their solubility. Initially, the crude oil contains nano-aggregates that might include some trapped molecules such as biomarkers. The biomarkers could also be dissolved but are near the point of insolubility. The addition of a solvent such as n-heptane decreases the solvent power and the formation of disordered larger aggregates starts, and more molecules are trapped in the incipient formation of these larger aggregates. In these aggregates, formed in local environments, a variety of molecules of different kinds are present. At low HCOR, as mentioned before, there is the expectation that the least soluble molecules should precipitate, a phenomenon that we did not observe. Instead, the precipitate contains a large proportion of heptane soluble molecules or maltenes as found in a previous study14 and confirmed by the present work. A plausible explanation for the absence of the least soluble molecules in the initially formed precipitate is that the highly aromatic molecules are present in very stable nano-aggregates that do not agglomerate when the solvent power is still high. For instance, it has been shown that dimers of carboxylic acids have a significant different solubility parameter than the monomer. For example, acetic acid as a dimer has a solubility parameter 30 % smaller than the monomer.40 This explains why acetic acid is soluble in water as well as in heptane. On the other hand, molecular dynamic simulations used to calculate solubility parameter of asphaltenes also showed that the solubility parameter of asphaltene aggregates decreases with the increase in the aggregation number.41 Thus, the 12 ACS Paragon Plus Environment
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aggregation of the asphaltenes helps the solubilization of this fraction. These small nanoaggregates are composed of the most aromatic molecules and are probably indigenous to the crude oil, so we postulate that the destabilization of these aggregates requires a significant lower solvent power than if the molecules were in the form of monomers. Experimental evidence obtained using small angle neutron scattering (SANS) indicates the presence of two types of asphaltene aggregates. One assigned to soluble asphaltenes and another corresponding to insoluble asphaltenes.42 Only at low solvent power or high HCOR, these asphaltenes become insoluble.42 At low HCOR, the kinetics of the formation of large aggregates is slow as demonstrated by the increase in the time to detect microscopic particles as the amount of added heptane decreases.41 The slow kinetics has been attributed to the high viscosity of crude oil/n-heptane blends at low n-heptane concentrations. As more n-heptane is added, the aggregation process is accelerated and more material is incorporated in aggregates that precipitate. The amount of precipitate increases as the amount of heptane increases even after washing the precipitated material with n-heptane43 or without washing.14 In this process, as more heptane is added, it can be hypothesized that an exchange of components takes place where some of the components non-covalently bound in the aggregates go back into solution while new components are incorporated in the aggregates. The changes observed in the molecular composition support this hypothesis. In general, it is observed that the less aromatic molecules go back into solution, while the most aromatic ones are incorporated into the large aggregates that settle out of solution. Comparison of Average Properties. Figure 8 shows the comparison of the molar H/C ratio calculated based on weighted abundances using both ionization techniques and the values shown in Table 1. From this plot, H/C molar ratios obtained from APPI and LDI followed similar 13 ACS Paragon Plus Environment
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tendencies to those determined by elemental analysis. However, those obtained using APPI are closer than the LDI ratios to the values determined by direct elemental analysis. Similar results have been reported before,19 indicating that LDI tends to be more selective towards highly aromatic compounds than APPI and, therefore, the H/C ratios are smaller. We also evaluate the average solubility parameter of the samples using a methodology described before.44 The concept of solubility parameter plays a relevant role as a measure of the intermolecular interactions in a pure fluid. It is defined as the root square of the cohesive density energy or cohesive energy per unit of volume: δ =(-U/V)0.5
(1)
Where U is the energy associated with the net attractive interactions of the material, V is the volume. The solubility parameter is an important concept that is currently used in many industries as a predictor of mixing ability and it has been used frequently in the description of asphaltene solubility.45-47 For asphaltenes, the solubility parameter cannot be determined directly as asphaltenes are non-distillable materials. However, there is equation called the “third-rule” that relates density with solubility parameter for hydrocarbons.49 In a previous work, it was proved that this rule could be used for asphaltenes.44 In the same study, it was also found that asphaltene density correlates rather well with hydrogen content. Therefore, it is possible to calculate the solubility parameter of the asphaltene molecules based on hydrogen content. Figure 9 shows a comparison of the solubility parameter values obtained using elemental analysis and APPI and LDI results. In this comparison, LDI overestimated the solubility parameter of the asphaltenes, although it yields the right tendency. As stated before, this 14 ACS Paragon Plus Environment
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ionization technique seems to be selective towards highly aromatic compounds. On the other hand, APPI produces remarkably close values to those calculated using elemental analysis composition for the most aromatic samples (HCOR=5 to 100), suggesting that APPI is one of the best ionization techniques to study asphaltenes. CONCLUSIONS Analysis of asphaltenes precipitated at different n-heptane/crude oil ratios indicates an increase in DBE and heteroatom content as the amount of added heptane increases. In contrast, carbon numbers show small changes. Both, APPI and LDI FT-ICR MS can be used to produce average values that describe the general tendencies obtained using other techniques. Specifically, the results support the idea that APPI FT-ICR MS can be particularly useful to study asphaltenes that are highly aromatic since the distributions obtained produce average values that closely match bulk data in the most aromatic asphaltenes obtained in this study.
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45. Lian, H.; Lin, J. R.; Yen T. F. Fuel 1994, 1, 423-428. 46. Wang, X.; Xu, Z.; Zhao, S.; Xu, C.; Chung, K. H. Energy Fuels 2008, 23, 386-391. 47. Mutelet, F.; Ekulu, G.; Solimando, R.; Rogalski, M. Energy Fuels 2004, 18, 667-673. 48. Redelius, P.; Soenen, H. Fuel 2015, 140, 34-43. 49. Panuganti, S. R.; Vargas, F. M.; Chapman, W. G. Ind. Eng. Chem. Res. 2013, 52, 80098020.
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TABLES Table 1. Elemental analysis of asphaltenes as a function of the heptane to crude oil ratio (HCOR) n-Heptane/Crude Oil
Elemental Analysis
Ratio (HCOR)
C (wt. %)
H(wt. %)
H/C Molar Ratio
1 1.5 2 5 10 100
82.86 83.58 84.08 80.94 81.35 80.33
11.01 10.41 10.00 8.72 8.41 8.04
1.59 1.49 1.43 1.29 1.24 1.20
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FIGURES LIST Figure 1. Class distribution of the asphaltenes obtained at different n-heptane/crude oil ratios using LDI and APPI. Relative intensities were calculated based on weighted intensities. Figure 2. DBE distributions as a function of n-heptane to crude oil ratio (APPI). Distributions calculated based on weighted intensities. Figure 3. Carbon number distributions as a function of n-heptane to crude oil ratio (APPI). Distributions calculated based on weighted intensities. Figure 4. Aromaticities (Fa) distributions as a function of n-heptane to crude oil ratio (APPI). Distributions calculated based on weighted intensities. Figure 5. Comparison of different aromaticity measurements as a function of the amount of n-heptane. FT-IR, APPI FT-ICR-MS and 1H-NMR measurements. Figure 6. Average number of heteroatoms per molecule as a function of the amount of the heptane. Insert shows average number of heteroatoms vs average DBE. Figure 7. Compositional distribution of unique species in the asphaltenes obtained at HCOR=1 and HCOR=100. a) DBE distribution. b) Carbon number distribution and c) Number of heteroatoms per molecule distribution. (APPI) Figure 8. Comparison of H/C molar ratios obtained by weighted intensity average of APPI and LDI signals and values obtained using elemental analysis results. Figure 9. Comparison of solubility parameters obtained by weighted intensity average of APPI and LDI signals and values obtained using elemental analysis results.
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Figure 1. Class distribution of the asphaltenes obtained at different n-heptane/crude oil ratios using LDI and APPI. Relative intensities were calculated based on weighted intensities.
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0.09 1
0.08
1.5 2
0.07
5
Relative Intensity
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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0.06
10 100
0.05 0.04 0.03 0.02 0.01 0 0
5
10
15
20 DBE
25
30
35
40
Figure 2. DBE distributions as a function of n-heptane to crude oil ratio (APPI). Distributions calculated based on weighted intensities.
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0.04 1 1.5 2
0.03
5 10
Intensity
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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100 0.02
0.01
0 0
10
20
30
40 50 Carbon Number
60
70
80
Figure 3. Carbon number distributions as a function of n-heptane to crude oil ratio (APPI). Distributions calculated based on weighted intensities.
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0.04 1 1.5 2
0.03
5
Relative Intensity
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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10 100 0.02
0.01
0.00 0
0.2
0.4
0.6
0.8
1
Aromaticity Figure 4. Aromaticities (Fa) distributions as a function of n-heptane to crude oil ratio (APPI). Distributions calculated based on weighted intensities.
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0.45
25 1600/2920
0.40
Aromaticity (MS) 20
Aromatic proton/aliphatic proton (H NMR)
0.35 0.30
15 0.25 0.20 10 0.15 0.10
5
0.05 0.00
0 40
50
60
70 80 % Vol. n-heptane
90
100
Figure 5. Comparison of different aromaticity measurements as a function of the amount of n-heptane. FT-IR, APPI FT-ICR-MS and 1H-NMR measurements.
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Aromatic proton/aliphatic proton
1600 cm-1/2920 cm-1 - Aromaticity
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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1.90
2.50
1.80 1.70 1.60
Average Heteroatom content/molecule
2.30
Average heteroatom per molecule
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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2.10 1.90 1.70 1.50 1.30 1.10 0.90 0.70 0.50 10
12
14
16
18
20
22
24
26
Average DBE
1.50 1.40 1.30 1.20
APPI 1.10
LDI
1.00 40
50
60
70 % Vol. n-heptane
80
90
100
Figure 6. Average number of heteroatoms per molecule as a function of the amount of the heptane. Insert shows average number of heteroatoms vs average DBE.
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Figure 7. Compositional distribution of unique species in the asphaltenes obtained at HCOR=1 and HCOR=100. a) DBE distribution. b) Carbon number distribution and c) Number of heteroatoms per molecule distribution. (APPI)
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1.70 Elemental Analysis 1.60
APPI
1.50 Molar H/C Ratio
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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LDI
1.40 1.30 1.20 1.10 1.00 0.90 0.80 40
50
60
70 % Vol. n-heptane
80
90
100
Figure 8. Comparison of H/C molar ratios obtained by weighted intensity average of APPI and LDI signals and values obtained using elemental analysis results.
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23.00
Elemental Analysis APPI
22.00
LDI Solubility Parameter
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
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21.00
20.00
19.00
18.00
17.00 40
50
60
70 % Vol. n-heptane
80
90
100
Figure 9. Comparison of solubility parameters obtained by weighted intensity average of APPI and LDI signals and values obtained using elemental analysis results.
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