Article pubs.acs.org/EF
Exploiting Metal Oxide Nanoparticle Selectivity in Asphaltenes for Identification of Pyridyl-Containing Molecules Aaron K. Zimmer, Christopher Becker, and C. Kevin Chambliss* Department of Chemistry and Biochemistry, Baylor University, Waco, Texas 76798, United States S Supporting Information *
ABSTRACT: Extraction efficiencies for a series of model compounds representing heteroatom functional groups believed to be present in asphaltenes were determined in batch extractions with a variety of metal oxide nanoparticles (Fe3O4, TiO2, NiO, Co3O4, and MgO). Extraction efficiencies from toluene solution varied depending upon both the adsorbate and the type of metal oxide used for extraction. However, the adsorbate was found to be the most important factor governing selectivity, which generally followed the trend: benzoic acid ≫ pyridine ≈ phenol > pyrrole > thiophene ≈ diphenylsulfide ≈ benzophenone. An important exception to this trend was that MgO did not appreciably adsorb pyridine. The divergent adsorption behavior of pyridine on NiO (extraction efficiency = 82 ± 1%) and MgO (extraction efficiency = 0 ± 2%) was subsequently exploited to demonstrate a novel approach for profiling pyridine-containing molecules in an authentic asphaltene sample. Specifically, mass spectra of the asphaltene mixture were obtained before and after treatment with NiO or MgO and compared to identify peaks exhibiting reduced intensity after treatment with NiO but no appreciable change in intensity after treatment with MgO. Results of batch extraction studies with model compounds and elemental composition data deduced from accurate mass measurements support that these peaks likely correspond to (or minimally contain) a molecule(s) possessing a pyridyl functional group. containing functional groups, respectively.2,4−8 A typical composition of asphaltenes is as follows: hydrogen/carbon ratio of 1.15 ± 0.5%, oxygen varying from 0.3 to 4.9%, sulfur varying from 0.3 to 10.3%, and nitrogen varying to a somewhat lesser degree (from 0.6 to 3.3% at the extremes).2 Although a variety of mass spectrometry (MS) techniques support an average of 750 ± 200 Da, the molecular weight distribution of asphaltenes remains a subject of debate.9−13 The relatively small magnitude of this proposed mean supports the likelihood of heteroatom compositional diversity between asphaltene constituents in that there may be some molecules that contain nitrogen and not sulfur or oxygen; others may contain sulfur and not nitrogen or oxygen; some may have nitrogen and sulfur but not oxygen; etc.14 Thus, expected differentiation provides a means for discriminative extraction, which the present study uses. The potential for rapid adsorption and catalytic upgrading of asphaltenes has made nanoparticle adsorption a subject of interest in the heavy oil industry.15 It has been previously shown that a variety of metal oxide nanoparticles (Fe3O4, Co3O4, MgO, CaO, NiO, and TiO2) have high capacity and affinity for asphaltene adsorption.16 Specifically, nickel oxide has received increasing attention because of its relatively high affinity for asphaltene adsorption.17 Adsorption has been modeled using both Langmuir and Freundlich isotherms.16,18,19 Furthermore, increases in adsorption affinity have been correlated with the presence of heteroatom substituents on model compounds.20 However, in none of these studies was
1. INTRODUCTION Oil is one of the major contributing sources to modern day energy consumption and is an extremely profitable industry. Over the past decade or so, there was a shift in interest within the oil industry from light to heavy crude oil.1 This shift in interest was due to an increasing demand for oil products that surpassed the ability of the industry to produce them from light crude oils alone. Accordingly, the heavier fraction of oil has become more important to research. Asphaltenes are one of four fractions of crude oil having a boiling point greater than 540 °C. The remaining fractions are saturates, aromatics, and resins. Each of these fractions is defined by its solubility characteristics, and the distinguishing characteristic of asphaltenes is that they are soluble in toluene but insoluble in nheptane.2 Asphaltenes are the heaviest and most polar fraction of crude oil and will be seen in greater quantities in heavy oils compared to light oils. Asphaltenes are also responsible for difficulties in petroleum processing, upgrading, and transportation.3 Numerous techniques exist for processing the heavier fraction of crude oil, but these methods tend to include high pressures and temperatures that lead to thermal cracking, which yields a relatively unprofitable byproduct called “coke”.2 Asphaltenes are suspected to be the primary compounds responsible for “coking”, and western hemisphere refineries would benefit from alternative methods that minimize the production of “coke” in favor of a more lucrative product. Such advances would arguably require detailed knowledge of molecular structures present in asphaltenes. Accordingly, obtaining knowledge of the constituents of this fraction is of significant interest and an important first step in forming future industrial strategies that deal with this fraction of crude oil. The asphaltene fraction is aromatic and polar because of the presence of polynuclear aromatic systems and heteroatom© XXXX American Chemical Society
Received: April 10, 2013 Revised: July 1, 2013
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the corresponding nanoparticle. The vials were shaken at 100 rpm for 30 min at 21 °C. Subsequently, a 10 μL aliquot of solution was taken from each vial and diluted with 1 mL of toluene prior to MS analysis. “Blanks” consisted of toluene alone, toluene treated with NiO, and toluene treated with MgO (100 nm). Plastic was avoided in these experiments, and glass vials were rinsed with toluene prior to use. We note that two independent extractions could likely be replaced by a single extraction using 3 mL of the initial asphaltene solution and 0.060 g of nanoparticle. 2.6. HPLC Analysis. A Dionex HPLC system, consisting of a GS50 Gradient Pump, AS autosampler, LC30 chromatography oven, and a Dionex UVD170U (UV detector) was used for analysis of benzoic acid, pyridine, pyrrole, thiophene, and phenol. A total of 10 μL of each sample, dissolved in toluene, was injected onto an Aqua Sep C-18 analytical column (ES Industries, 25 cm × 4.6 mm, catalog number 155221-AQS), and analytes were separated at 40 °C using the following binary gradient: 60% H2O/40% acetonitrile (MeCN) held for 5 min, ramped to 90% MeCN over 1 min, held at 90% for 3 min, ramped back to initial composition over 1.5 min, and held until a return to baseline was achieved. The flow rate was held constant at 1 mL/min. Analytes were monitored at the following wavelengths: pyridine (255 nm), pyrrole (220 nm), thiophene (220 nm), benzoic acid (220 nm), and phenol (275 nm). Analytes were quantitated via external calibration, using standards prepared in toluene. 2.7. GC−MS Analysis. Thermo Electron Corporation DSQII GC−MS, equipped with an AI3000 autoinjector, was used for analysis of benzophenone and diphenylsulfide. A total of 0.1 μL of each sample was injected onto an Agilent DB-5MS column (25 m × 0.250 mm, 0.25 μm) with a split ratio of 100:1 (split flow rate = 150 mL/min) and an inlet temperature of 250 °C. The column oven was held at 35 °C for 10 min and then ramped to 260 °C at a rate of 25 °C/min. Carrier gas (He) flow was held constant at 1.5 mL/min throughout the run. The transfer line temperature was held constant at 280 °C. The MS ion source was held at 250 °C and operated in positive mode with detector gain = 3.00 × 105. However, the MS detector was turned off for the first 2.5 min of each chromatographic run, so that the signal for the toluene peak would not be recorded. 2.8. Orbitrap MS Instrumentation. All asphaltene samples were diluted with toluene prior to analysis. Asphaltene concentrations in analyzed samples were on the order of 50 μg/mL (on the basis of the prepared concentration before extraction). Each sample was directly infused into a LTQ Orbitrap mass spectrometer (Thermo Scientific, Waltham, MA) at a flow rate of 25 μL/min. Infused samples were ionized using an atmospheric pressure photo- and chemical ionization (APPI/APCI) source operated in dual APPI/APCI mode. Although the source was operated in a mixed ionization mode to maximize opportunities for sample ionization, we note that we could not observe a significant difference between spectra with and without the APPI lamp turned on. The positive-ion spectra in this paper were obtained with the following instrument settings: vapor temperature, 300 °C; sheath gas flow rate, 50; auxiliary gas flow rate, 5; sweep gas flow rate, 5; discharge current, 5 μA; discharge voltage, 4.05; capillary temperature, 300 °C; capillary voltage, 43 V; and tube lens, 110 V. Full-scan, profile mass spectra were obtained over the m/z range of 300−1500 by collecting 50 scans with 1 microscan and a maximum ion injection time of 400 ms. The mass analyzer was operated in highresolution mode (R = m/Δm = 30 000 at m/z 400). The exact mass of the observed asphaltene ion signal was obtained by locking onto 9,10diphenylanthracene at m/z 330.1408 spiked into a non-extracted asphaltene sample. Data were analyzed and processed using the Thermo Xcalibur Qual Browser software (version 2.1).
there precise indication of which specific heteroatom functional group(s) was responsible for observed adsorption. This work reveals which of the heteroatom functional groups expected to be present in asphaltenes adsorb onto metal oxide nanoparticles. This was achieved by observing relative differences in extraction efficiencies of model compounds containing a single functional group onto a variety of metal oxide nanoparticles. Initial extraction studies revealed an extreme difference in affinity of pyridine for NiO relative to MgO that was subsequently exploited to evaluate the distribution of potential pyridyl-containing constituents in the mass spectrum of an asphaltene sample. This proof-of-concept example demonstrates a novel approach to reducing spectral complexity in mass spectral characterizations of asphaltenes and may be useful in future efforts to elucidate the structure of authentic asphaltene constituents.
2. EXPERIMENTAL SECTION 2.1. Materials. Nanoparticles, NiO (100 nm average particle size), TiO2 (30−40 nm), Fe3O4 (20−30 nm), Co3O4 (50−80 nm), MgO (100 nm), and MgO (20 nm), were obtained from Nanostructured & Amorphous Material, Inc., Houston, TX (additional details on the nanoparticles used in this study are available in Table S1 of the Supporting Information). Unless specified, all chemicals were reagentgrade (assayed at >98% purity) or best-available-grade, obtained from commercial venders and used as received. Water for high-performance liquid chromatography (HPLC) eluent was deionized to 18 MΩ using a Barnstead NANOpure Diamond ultraviolet (UV) water purification system. Ultra-Resi analyzed-grade toluene for MS was obtained from J.T. Baker. To obtain the asphaltene sample used in this work, a San Andro region crude oil was homogenized with n-heptane (1:40 oil/ heptane ratio) and refrigerated in the dark over 6 h (∼4 °C). Asphaltenes were collected from the chilled solution on a fine-grade glass frit by vacuum filtration. The asphaltene sample was stored at room temperature in a capped scintillation vial prior to use. 2.2. Extraction Studies: Model Compound Adsorption. In a typical experiment, a 10 mM solution of a model compound (benzoic acid, pyridine, pyrrole, thiophene, phenol, benzophenone, or diphenylsulfide) was prepared in toluene. A total of 5.00 mL of this solution was then added to 1.000 g of a given nanoparticle in a glass scintillation vial. The vial was vortexed for 15 min and then centrifuged at 3000 rpm for 5 min. A portion of solution was transferred to an autosampler vial for analysis. All experiments were performed in triplicate. Benzophenone and diphenylsulfide were analyzed by gas chromatography−mass spectrometry (GC−MS), and all other analytes were analyzed by HPLC. 2.3. Adsorption Kinetics. A 10 mM solution of model compound (benzoic acid, pyridine, or phenol) was prepared in toluene. A total of 5.000 mL was added to a sample of a given nanoparticle and then vortexed. The vortex time for each vial was different: 0.083, 0.25, 0.5, 1, 2.5, 5, 10, and 15 min. Immediately after being vortexed, the vial was centrifuged at 3000 rpm for 30 s. A portion of solution was then removed from the vial and taken for HPLC analysis. 2.4. Competitive Adsorption. A solution containing 10 mM benzoic acid, 10 mM phenol, and 10 mM pyridine was prepared in toluene. A total of 5.000 mL of solution was then added to a given nanoparticle [1.000 g of NiO, 0.100 g of NiO, or 0.200 g of MgO (100 nm)] in triplicate. The vial was vortexed for 15 min and then centrifuged at 3000 rpm for 5 min. A portion of solution was taken for HPLC analysis. 2.5. Asphaltene Adsorption. Two 0.003 g portions of asphaltene were independently dissolved in 3 mL of toluene. Prior to the addition of nanoparticles, 10 μL of each solution was subsampled and diluted with 1 mL of toluene to serve as an asphaltene control (no extraction). Afterward, 0.030 g of MgO (100 nm) was added to one vial of asphaltene, and 0.030 g of NiO was added to the other. These samples were shaken at 100 rpm for 30 min at 21 °C. After shaking, 1 mL of solution from each vial was taken and added to an additional 0.010 g of
3. RESULTS AND DISCUSSION 3.1. Justification of Model Compounds. Adsorption of asphaltenes onto metal oxide nanoparticles has been attributed to heteroatom functional groups within the asphaltenes.16 Nitrogen in the asphaltene fraction is expected to be within the aromatic ring systems in pyridinic and pyrrolic forms. This assumption is supported by thermal studies that have shown B
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Table 1. Extraction Efficiency of Metal Oxide Nanoparticles toward Model Organic Compounds Dissolved in Toluenea Fe3O4 TiO2 NiO Co3O4 MgO_20 nm MgO_100 nm
pyridine (%)
benzoic acid (%)
± ± ± ± ± ±
>99c 86 ± 6 >99 80 ± 5 >99 >99
43 32 82 49 4 0
1b 1 1 1 1 2
phenol (%) 51 30 68 50 84 16
± ± ± ± ± ±
pyrrole (%)
1 1 1 2 1 3
16 14 18 34 19 15
± ± ± ± ± ±
thiophene (%)
1 3 1 1 6 2
5 3 4 5 3 4
± ± ± ± ± ±
diphenylsulfide (%)
1 2 2 1 3 2
12 4 3 1 7 3
± ± ± ± ± ±
benzophenone (%)
3 3 3 3 3 2
5 1 6 3 2 2
± ± ± ± ± ±
2 2 2 2 2 2
a Extraction experiments were conducted using a 5 mL volume of 10 mM analyte and 1.000 g of nanoparticle. bExtraction efficiency was calculated as [(prepared concentration − measured concentration)/prepared concentration] × 100%. Error is expressed as the coefficient of variance for three replicate extractions. cThe >99% extraction efficiency indicates that any analyte remaining after extraction was present below the instrumental limit of detection.
Table 2. Extraction Efficiencies Resulting from Competitive versus Non-competitive Adsorption of Select Model Compounds onto Nickel Oxide and Magnesium Oxide Nanoparticlesa non-competitive extraction efficiencies NiO NiO MgO_100 nm
competitive extraction efficiencies
nanoparticle weight (g)
pyridine (%)
benzoic acid (%)
phenol (%)
pyridine (%)
benzoic acid (%)
phenol (%)
1.000 0.100 0.200
82 ± 1b 21 ± 3 3±4
>99c 67 ± 1 86 ± 2
68 ± 1 9±1 8±3
81 ± 2 12 ± 3 2±4
>99 77 ± 1 52 ± 3
54 ± 3 5±3 2±3
a
aNanoparticle weight was varied to leave a measurable amount of benzoic acid in solution at the end of experiments using 99% extraction efficiency indicates that any analyte remaining after extraction was present below the instrumental limit of detection.
that only 1% of nitrogen is lost upon heating.2 In addition, in 1993, Mitra-Kirtley et al. concluded that a larger portion of nitrogen is likely present in the pyrrolic form rather than the pyridinic form.21 In contrast, oxygen is expected to be found primarily in carboxylic acid, phenolic, and ketone functional groups rather than in heteroaromatic ring systems of the asphaltenes.2,22−28 Sulfur is present in a variety of thiophenederived structures.2,22,29−34 Other forms of sulfur expected to exist in asphaltenes include sulfides, such as alkyl−alkyl sulfides, alkyl−aryl sulfides, and aryl−aryl sulfides.2,31 With this information, pyridine, pyrrole, thiophene, phenol, diphenylsulfide, benzophenone, and benzoic acid were selected as model compounds. These molecules are aromatic, consisting of a low hydrogen/carbon ratio, and they have heteroatom functional groups that are expected to exist in asphaltene molecules. 3.2. Extraction Efficiencies. It has been shown that asphaltenes adsorb very quickly onto the same metal oxide nanoparticles used in this study.16 Thus, a similar fast adsorption of analytes used in this study was expected. The adsorption rates were appraised by monitoring extraction efficiencies for vortex times varying from 5 s to 15 min. In all test cases using 1.000 g of nanoparticle, equilibrium appeared to be reached in 2.5 min of vortex time. Regardless, a 15 min vortex time was used in all adsorption experiments involving model compounds. To test how well the different functional groups adsorb onto various metal oxide nanoparticles, a 10 mM solution of each analyte was contacted with a given nanoparticle type. After equilibration, the concentration of analyte remaining in solution was measured and used to calculate extraction efficiency (Table 1). Inspection of data in Table 1 shows that benzoic acid, pyridine, and phenol were strongly adsorbed (>20% extraction efficiency) by most tested metal oxides. In contrast, benzophenone, diphenylsulfide, and thiophene showed relatively weak adsorption. Adsorption of pyrrole was generally
found to be of intermediate strength, although trending toward the weaker end of the two extremes. These data are consistent with previous observations suggesting that the presence of oxygen and nitrogen in the structure of asphaltenes is important in dictating adsorption dynamics.20 However, the present experiment further supports that adsorption onto these metal oxides is, in general, most strongly favored by oxygen present in the carboxylic and/or phenolic (or alcohol) functional groups and by pyridinic forms of nitrogen. With respect to nitrogen, Co3O4 and MgO appear to be possible exceptions to the noted trend. Extraction efficiencies for pyrrole were highest when Co3O4 was used as the sorbent (putting it on a similar level with pyridine when adsorbed by Co3O4), and pyridine showed extremely weak adsorption onto MgO. The most siginificant difference in extraction efficiencies observed for a single compound on two metal oxides occurred for pyridine. Extraction efficiency was essentially negligible when MgO was the sorbent, but >80% of pyridine was extracted from toluene by NiO. This observed adsorption selectivity lead to a rational hypothesis for identification of pyridyl-containing molecules in asphaltenes via sequential extractions. Subsequent experiments were designed to confirm that selective adsorption should be expected in a competitive extraction experiment and to demonstrate selective removal of pyridyl-containing molecules from the asphaltene mixture. 3.3. Competitive Adsorption. Because the asphaltene fraction of crude oil is composed of all heteroatom functionalities investigated here, it was important to examine the effect of a competitive environment on adsorption trends. Competitive adsorption was investigated using NiO and MgO nanoparticles for analytes exhibiting greater than 20% extraction efficiency in Table 1 (i.e., pyridine, benzoic acid, and phenol). Table 2 displays extraction efficiencies observed under conditions of competitive adsorption alongside results for corresponding solo-adsorption experiments. Note that the C
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Figure 1. Mass spectra of an asphaltene sample (A) prior to extraction, (B) after two extractions with NiO, (C) toluene blank before acquiring sample data, and (D) toluene blank after acquiring sample data.
NiO could have a cooperative effect on benzoic acid adsorption (e.g., via intermolecular interactions between these molecules). However, it must also be appreciated that standard deviations reported in Table 2 represent intraday precision (i.e., triplicate experiments performed and analyzed on the same day). An evaluation of interday precision would undoubtedly result in larger standard deviations, perhaps to such an extent that the observed 10% difference between benzoic acid extraction efficiencies was no longer statistically relevant. Overall, data in Table 2 support that important trends observed in solo-adsorption studies were conserved when competing analytes were present in solution. That is, benzoic acid was efficiently removed by both NiO and MgO, and measurable adsorption of pyridine was observed with NiO but not MgO. Extraction behavior of phenol was generally similar to that observed for pyridine, but competition resulted in minimal and negligible adsorption of phenol onto NiO and MgO, respectively, when the mass of the nanoparticle was substantially less than 1.000 g. 3.4. Asphaltene Adsorption. A subsequent experiment was designed to evaluate whether comparison of mass spectra of an asphaltene sample, before and after independent treatments with MgO and NiO, could be useful in identifying asphaltene constituents that contain one or more pyridyl functionalities. On the basis of results of adsorption experiments with model compounds, one would expect MgO and NiO to both adsorb asphaltene constituents that contain a carboxylic acid functional group(s). However, MgO would not be expected to appreciably adsorb pyridyl-containing constituents, provided no other group(s) that interacted strongly with MgO was present in their structure. NiO, on the other hand, would be expected to adsorb such compounds, thus providing a degree of preferential selectivity in compound removal. To test this hypothesis, duplicate asphaltene samples were prepared in toluene. One was treated with MgO, and the other
nanoparticle weight was adjusted in the latter two experiments to leave a measurable amount of benzoic acid in solution at the end of each experiment. When 1.000 g of NiO was used as the sorbent, competition had a negligible effect on observed extraction efficiencies of benzoic acid and pyridine and extraction efficiency observed for phenol was only moderately decreased relative to the corresponding solo-adsorption value. In contrast, when only 0.100 g of NiO was used, competition resulted in extraction efficiencies for pyridine and phenol that were reduced by almost 50%. These observations are consistent with the following interpretation. In the first experiment (1.000 g of NiO), it is likely that an abundance of adsorption sites was available. In this case, even when benzoic acid is exhaustively removed from solution, NiO adsorption sites appear to remain sufficiently abundant to allow for extraction equilibria involving pyridine and phenol to proceed in a manner similar to what would be expected in solo-adsorption studies. When nanoparticle weight was reduced (0.100 g of NiO), however, benzoic acid adsorption, benzoic acid remaining in solution, or both had an appreciable influence on pyridine and phenol adsorption affinities. This scenario likely represents a situation where all three compounds were indeed competing for a limited number of NiO adsorption sites. Minimal removal of phenol was observed under these conditions. Pyridine, on the other hand, was still appreciably extracted, albeit with a lower efficiency than when 1.000 g of NiO was used. When conditions expected to promote competitive adsorption onto MgO were employed (i.e., when 0.200 g of MgO was used as the sorbent), removal of both pyridine and phenol was negligible, while observed extraction efficiency for benzoic acid remained relatively high. Note that a modest increase in benzoic acid adsorption was observed in the competitive adsorption experiment relative to the solo-adsorption experiment when 0.100 g of NiO was used (Table 2). It is possible that pyridine adsorbed on the surface of D
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Figure 2. Mass spectra between m/z 493.26 and 493.39 of an asphaltene sample before and after nanoparticle extraction (by MgO and NiO, left and right, respectively). The red mass indicates removal by NiO only. (A and B) Two different asphaltene samples before extraction, (C) resulting asphaltene sample extracted with only MgO, and (D) resulting asphaltene sample extracted with only NiO.
Figure 3. Mass spectra between m/z 505.23 and 505.39 of an asphaltene sample before and after nanoparticle extraction (by MgO and NiO, left and right, respectively). The blue mass indicates removal by both MgO and NiO. The red mass indicates removal by NiO only. (A and B) Two different asphaltene samples before extraction, (C) resulting asphaltene sample extracted with only MgO, and (D) resulting asphaltene sample extracted with only NiO.
in panels A and B of Figure 1, respectively. These data show a substantial reduction in the intensity of peaks corresponding to asphaltenes (i.e., the approximate Gaussian distribution of ion signals between m/z 300 and 1100) after extraction, suggesting that many asphaltene constituents were adsorbed by the metal oxide. Note that more prevalent peaks at higher abundance in
was treated with NiO. High-resolution mass spectra of the asphaltene samples were obtained before and after extraction and inspected for peaks that behaved in a manner consistent with the aforementioned hypothesis. High-resolution mass spectra of the asphaltene sample before extraction and following two successive treatments with NiO are displayed E
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Figure 4. Mass spectra between m/z 693.00 and 693.80 of an asphaltene sample before and after nanoparticle extraction (by MgO and NiO, left and right, respectively). The blue mass indicates removal by both MgO and NiO. The red mass indicates removal by NiO only. (A and B) Two different asphaltene samples before extraction, (C) resulting asphaltene sample extracted with only MgO, and (D) resulting asphaltene sample extracted with only NiO.
panels A and B of Figure 1 were also observed in blank spectra of toluene (panels C and D of Figure 1) and may be attributed to the background. Representative mass spectra illustrating selective adsorption of asphaltene constituents by NiO are displayed in Figures 2−4. The intensities of peaks appearing at m/z 493.34, 505.34, and 693.49 in asphaltene spectra prior to treatment with nanoparticles were appreciably reduced following treatment with NiO. In contrast, treatment with MgO had an essentially negligible effect on the relative intensities of peaks appearing at these m/z values. Note that the apparent increase in intensity of the peak at m/z 493.34 in Figure 2C is an artifact of the relative abundance scale. Inspection of raw peak intensities (i.e., counts) revealed that the peaks appearing on either side of the peak in question experienced a modest decrease in intensity after treatment with either metal oxide. In contrast, the difference in observed counts for the peak appearing at m/z 493.34 in panels A and C of Figure 2 was within typical precision limits of the measurement. It is important to point out that none of these peaks was observed in mass spectra of toluene blanks. Thus, these data support that asphaltene sample constituents appearing at m/z 493.34, 505.34, and 693.49 likely contain at least one pyridyl functional group. Of the estimated 6000 m/z peaks evaluated in this study, about 45 were found to exhibit a similar selective reduction in intensity following treatment with NiO relative to MgO. Exact mass measurements were employed to further support the presence of pyridyl functional groups in sample constituents appearing at m/z 493.34, 505.34, and 693.49. Chemical formulas within 25 ppm of the exact mass observed for each peak (i.e., the experimental mass) are reported in Table S2 of the Supporting Information. All formulas within 5 and 25 ppm of the experimental mass were surveyed for the presence of nitrogen. The 5 ppm mass window represents a conservative
mass-accuracy threshold, assuming that each peak corresponds to a single compound. However, the resolving power of MS instrumentation used in this work does not preclude the possibility of multiple compounds appearing as a single peak. For this reason, a 25 ppm window, which essentially spans the baseline width of peaks appearing at m/z 493.34 and 505.34, was also evaluated. Results are summarized in Table 3. In all analyses, the vast majority of possible chemical formulas contained nitrogen. This statistical outcome lends further Table 3. Chemical Formula Analysis of Extracted Asphaltene Ions Showing the Total Possible Molecular Formulas within a Given Mass Error (in ppm)a 5 ppm mass error m/z ratio 493.3359 total with N without N 505.3344 total with N without N 693.4905 total with N without N
25 ppm mass error
number of formulas
percentage of the total (%)
number of formulas
percentage of the total (%)
6 5 1
83.3 16.7
32 29 3
90.6 9.4
8 7 1
87.5 12.5
36 33 3
91.7 8.3
25 22 3
88.0 12. 0
121 110 11
90.9 9.1
a Analysis assumes that m/z values correspond to singly charged (+1) ions. A restriction of double bond equivalence greater than or equal to 4 was imposed, and maximum elemental composition thresholds were as follows: 40 C, 80 H, 10 N, 10 O, and 15 S for m/z 493.34 and 505.34 and 60 C, 120 H, 15 N, 15 O, and 23 S for m/z 693.49.
F
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credence to the hypothesis that compounds selectively removed from asphaltenes by NiO contain one or more pyridyl functional groups. Interestingly, 4 of 5 and 5 of 7 nitrogencontaining chemical formulas identified within the 5 ppm massaccuracy threshold for m/z 493.34 and 505.34, respectively, also contained oxygen. Because the intensity of neither peak was reduced following treatment with MgO, it is unlikely that oxygen is present in the extracted molecule(s) in the form of a carboxyl group. However, definitive conclusions regarding the presence or absence of a carboxyl group may not be drawn based solely on data reported in this paper.
4. CONCLUSION Data presented in this work demonstrated that a comparison of mass spectra of an asphaltene solution, following treatment with NiO and MgO, may be used to identify the m/z ratio of constituents of the complex mixture that contain a pyridyl functional group. The availability of such information has prominent implications in attempts to formulate structural assignments for asphaltene constituents. Additionally, to the extent that sorbents exhibiting selectivity for other functional groups of interest may be identified, the approach presented here serves as an important proof-of-concept example of selective adsorption. In general, selective adsorption of heteroatom-containing functional groups could be used to profile the distribution of a specific heteroatom in a complex mixture. It may also serve to reduce mass spectral complexity and enable elucidation of information that would be difficult to deduce via MS alone by providing a complementary separation. For example, if a compound appearing as a shoulder in complex spectra could be selectively removed, it would result in a more accurate determination of the mass/charge ratio for the compound remaining in solution. Overall, the concept of selective adsorption has exceptional potential, and further work of this nature is merited as it relates to not only asphaltenes but also other complex mixtures.
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ASSOCIATED CONTENT
* Supporting Information S
Nanoparticle information available from the manufacturer (Table S1) and chemical formulas assigned to specific peaks (Table S2). This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*Telephone: 254-710-6849. Fax: 254-710-4272. E-mail: kevin_
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We acknowledge the Baylor University Mass Spectrometry Center for instrument access and experimental support provided during the course of this work.
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REFERENCES
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dx.doi.org/10.1021/ef400643v | Energy Fuels XXXX, XXX, XXX−XXX
