Energy & Fuels 1995,9, 760-764
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Determination of Bitumen Molecular Weight Distributions Using 2s2Cf Plasma Desorption Mass Spectrometry John W. Larsen" and Shang Li Department of Chemistry, 6 East Packer Avenue, Lehigh University, Bethlehem, Pennsylvania 1801 5 Received December 7, 1994@
Molecular weight distributions of Green River, Rundle, and Athabasca bitumens and two Athabasca bitumen products were measured using 252Cfplasma desorption mass spectrometry (PDMS). All samples showed continuous molecular weight distributions up to about 3000 amu except Rundle bitumen. Its PDMS spectrum displayed a trimodal molecular weight distribution. Number average molecular weights calculated from PDMS spectra were compared to those obtained by vapor pressure osmometry (VPO) in toluene or THF. Average molecular weights measured by the two methods agreed well for the three bitumens and did not agree well for the bitumen residues. The PDMS measured molecular weight distributions of Athabasca bitumen samples were compared with molecular weight distributions measured by a combination of gel permeation chromatography (GPC) and VPO. The molecular weight distributions agreed reasonably well a t high mass but differed significantly at low mass. 252Cfplasma desorption mass spectrometry may be a useful rapid technique for determining bitumen molecular weight distributions.
Introduction Bitumens are the soluble portion of organic matter in oil shales. Their composition and the concentration of individual components have been used to evaluate both the extent of kerogen maturation and to charaderize the chemistry of kerogen maturati~n.'-~The subject of this paper is the measurement of bitumen molecular weight distributions. Knowledge of bitumen molecular weight distributions can be used in three very different ways. It is of great value in following the industrial processing of bitumens. Most studies of bitumen molecular weights have been connected with Second, the physical properties and behavior of source rocks and petroleum reservoirs are sensitive to bitumen molecular weight distributions and such information is useful in reservoir modelinga8 There is a third, largely ignored, use for such data. The amount and molecular weight distribution of a bitumen are functions of the chemistry by ~ which it is f ~ r m e d .Measuring the amount and molecular weight distribution of bitumens may provide @Abstractpublished in Advance ACS Abstracts, August 1, 1995. (1)Tissot, B.P.;Welte, D. H. Petroleum Formation and Occurrence; Springer-Verlag: New York, 1978. (2)Robinson, W. E. in Oil Shale, Yen, T. F.; Chilingarian, G. V., Eds.; Elsevier Sci. Pub. Co.: Amsterdam, 1976. (3)Gallegos, E. J.In Oil Shale, Yen, T. F., Chilingarian, G. V., Eds., Elsevier Sci. Pub. Co.: Amsterdam, 1976. (4)Vandenbroucke, M. In Kerogen, Durnad, B., Ed., Editons Technip: Paris, 1980. ( 5 ) Champagne, P. J.; Emmanuel, M.; Ternan, M. Fuel 1986,64, 423-425. (6)Brule, B. J. Liq. Chromatogr. 1979,2 (2),165-192. (7)Barrett, D.;Sambi, T.; Sergeant, G.D.; Fuel, 1990,69, 267269. ( 8 ) Huang, S. H.; Radosz, M. Fluid Phase Equilib. 1991,66, 2340. (9)Flory, P.J. Principle of Polymer Chemistry; Cornel1 University Press, Ithaca, NY,1953.
0887-0624l9512509-0760$09.00/0
insight into the kerogen maturation process, especially if such information is combined with studies of kerogen cross-link densities.1° We wish to combine knowledge of bitumen molecular weight distributions with kerogen cross-link densities to create a model of the polymerization or depolymerizationwhich occurs during kerogen maturation. To this end, we seek a reliable method for determining bitumen molecular weight distributions. The most frequently used technique for studying bitumen molecular weight distributions is gel permeation chromatography (GPC). A careful study of the application of GPC to bitumens revealed that there are no adequate calibration standards, a common occurrence when applying this technique t o complex heavy hydrocarbon mixtures and kerogen p r o d u ~ t s . ~ J ' JA~ laborious solution to the calibration problem exists and has been used: separate the bitumen into fractions by preparative GPC and measure the molecular weight of each fraction by vapor pressure osmometry (VPO).5 In addition to being labor intensive, there are problems due to the inefficiency of the GPC separation and the breadth and symmetry of the molecular weight distributions of the individual fractions. We believe that GPC molecular weight distributions do not meet our needs. Besides GPC and GPCNPO, few other techniques have been used for determining bitumen molecular weight distributions. Ternan and co-workers compared molecular weight measurements obtained by three techniques: W O ,freezing point depression (FPD), and gas chromatography-mass spectrometry (GC-MSL5 For 10 fractions separated by preparative GPC, VPO,and FPD (10)Larsen, J. W.; Li, S. Energy Fuels 1994,8, 932-936. (11) Bartle, K D; Mulligan, M. J.; Taylor, N.; Martin, T. G.; Snape, C. E. Fuel 1964,63,1556-1560. (12)Mulligan, M. J.; Thomas, K. M.; Tytko, A. P. Fuel 1987,66, 1472-1480.
0 1995 American Chemical Society
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Bitumen Molecular Weight Distributions results generally agreed well. They analyzed three low molecular weight fractions using GC-MS; the data verified the molecular weight measurements by VPO. Huang and Radosz combined GPC and gas chromatography simulated distillation to obtain bitumen molecular weight distributions.* Distributions obtained by the two techniques are substantially different. Payzant and co-workers applied field-ionization mass spectrometry (FIMS) to determine bitumen molecular weight di~tributi0ns.l~ They were able to evaluate the effect of biodegradation on a series of Alberta bitumens by examining molecular weight distributions of the hydrocarbon-substituted aromatic, sulfur-containing aromatic, thiourea adduct, and thiourea nonadduct fractions from these bitumens. Compared to low-voltage electron-impact mass spectrometry (EIMS), FIMS generated more reliable molecular weight distributions because it responded with approximately equal sensitivity t o almost all classes of compounds. McKay and coworkers used VPO and FIMS to characterize Green River bitumen.14-16 A detailed comparison of their results and ours is presented in the Result and Discussion section of this paper. Having had some success in using 252Cfplasma desorption mass spectrometry to measure molecular weight distributions of coal hydrogenation products, we decided to explore its application t o bitumens.17 The technique uses 252Cffission fragments to volatilize and ionize materials deposited on an aluminized Mylar disk.l* For most molecules, this process results in little fragmentation for heteroatomic ions, but hydrocarbons have a greater tendency to fragment. Their fragmentation is much less in conventional electron ionization mass spectrometry. l9 A time-of-flight mass spectrometer is used, so the accessible molecular weight range exceeds 20 000 amu. This paper contains our results for three bitumens and two bitumen products.
Results and Discussion Molecular weight distributions of Green River, Rundle, and Athabasca bitumens and two Athabasca bitumen derivatives were obtained using 252Cf plasma desorption time-of-flight mass spectrometry (Bio Ion 20 mass spectrometer). Number and weight average molecular weights of these samples were calculated from the PDMS spectra after subtracting the background signals from the aluminized Mylar disk which supports the sample monolayer. The results are compared to those obtained by VPO (see Table 1). Figure 1 shows the PDMS spectra of an aluminized Mylar disk. The background spectrum reaches the (13)Payzant, J. D.; Rubinstein, I.; Hogg, A. M.; Straus, 0.P. Geochim. Cosmochim. Acta 1979,43, 1187-1193. (14) McKay, J.F.; Chong, S.-L.;Gardner, G. W. Liq.Fuels Technol. 1983, 1,259'287. (15) McKay, J. F.; Chong, S.-L. Liq.Fuels Technol. 1983, 1, 289324. (16) McKay, J. F.; Blanche, M. S. Liq. Fuels Technol 1986,3, 489521. (17) Larsen, J. W.; Lapucha, A. R.; Wemett, P. C.; Anderson, W. R. Energy Fuels 1994,8, 258-265. (18) (a)Macfarlane,R. D.; Torgerson, D. F. Science 1976,191,920925. (b) Macfarlane, R. D. Anal. Chem. 1983,55, 1246A. (19) (a)Zingaro, R. A.; Macfarlane, R. D.; Garcia, J.M., 111;Vindiola, A. G.;Zoeller, J. H., Jr. Prepr. Pap.-Am. Chem. Soc., Diu. Fuel Chem. 1984,29 ( 5 ) , 22-30. (b) Zingaro, R. A.; Vindiola, A. G.; Zoeller, J. H., Jr. Int. J.Mass Spectrom. Ion Phys. 1983,53,349-352. (c) Zoeller, J. H., Jr.; Zingaro, R. A.; Macfarlane, R. D. Int. J . Mass Spectrom. Ion Phys. 1987, 77, 21-30.
Table 1. Number and Weight Average Molecular Weights (Da) Determined Using VPO and PDMS VPO PDMS samde M, M, M, M, Green River Rundle, toluene soluble Rundle, toluene insoluble Athabasca Athabasca, +525 fraction Athabasca, +525 unimodal catalyst
720 f 71" 400 f 21" 596b 103W 1244c
1246b 1152c 2014c
609 462 551 620 733 726
1092 831 988 1076 1259 1253
Standard deviation calculated from the result of linear regression. Calculated from VPO results of 11 fractions.s Calculated from VPO results of 5 fractions.18 I X 10001
0
2
I
m/z
3
4
5 ( X 10001
Figure 1. PDMS spectrum of an aluminized Mylar disk background.
Table 2. Elemental Analyses of Kerogen,=Amount of Bitumen Extracted,* and Amount of Kerogen' in Green River and Rundle Oil Shales sample
% C
H
%
% ash
Rundle Oil Shale Green River Oil Shale
55.1 73.3
8.0 9.4
20.1 5.2
%
%
bitumenb kerogenc 4.7 6.1
22.7 26.5
a Galbraith Laboratories. Soxhlet extraction with toluene. By weight, % of starting shale.
baseline between 500 and 1000 amu. The intense peaks a t low mass are due to aluminum oxide cluster ions. This background must be subtracted from the sample spectrum in order to calculate the average molecular weight. The number and weight average molecular weights listed in Table 1were calculated after subtraction of the background spectrum. Because of errors resulting from the subtraction of large background peaks, the spectra were truncated a t 78 amu and lower molecular weight peaks were discarded. A detailed discussion of our data treatment can be found in ref 17. Green River and Rundle bitumens were isolated by HCl/HF demineralization of the raw oil shales followed by Soxhlet extraction (toluene) of the demineralized kerogens.1° Demineralizations were carried out for 48 h at 55-65 "C. Table 2 contains the elemental analyses of these two kerogens, the amount of bitumen extracted, and the amount of kerogen isolated. The toluene extract from Rundle kerogen separated into two fractions a t room temperature: toluene-soluble and toluene-insoluble. Toluene was removed from the toluene-soluble fraction by using a rotary evaporator followed by vacuum drying. The dried sample was dissolved in THF at room temperature for PDMS and VPO experiments.
Larsen and Li
762 Energy & Fuels, Vol. 9,No. 5, 1995 I X 1001
IX 1001
I
10
8
6 In
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Y
CI C
3 c
" 0
u
4
2
0
2
1
m/z
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4
5
Figure 2. PDMS spectrum of Green River bitumen raw data
(upper line) and the smoothed spectrum with the Mylar disk background subtracted (lower line). Table 3. Reported Number and Weight Average Molecular Weights of Green River Bitumen Measured by VPO and FIMS w~ FIMS FIMS (calculated) isolation technique Mn Mn Mw M, Mw pyridine extractiona CH30H/H20 400 "C" COfl20 400 "Cb a
1150 452 521
721
934
747 1050 1010
0
IX 10001
1
2
3
4
m/z
5
IX 10001
Figure 3. PDMS spectrum of toluene-soluble fraction of
Rundle bitumen raw data (upper line) and the smoothed spectrum with the Mylar disk background subtracted (lower line). IX 1001
943 1230 1180
*
From ref 16. From ref 14.
The other fraction precipitated from toluene solution. We failed to find a good room temperature solvent for it, and redissolved it in toluene at 80 "C for PDMS analysis. Figure 2 presents the molecular weight distribution of Green River bitumen. The top noisy curve is the raw data. The lower line is the same data after subtracting the aluminized Mylar background spectrum and smoothing. The spectrum shows a continuous molecular weight distribution up to about 3000 amu. The number average molecular weight of this bitumen measured by VPO agrees well with that calculated from its PDMS spectrum (Table 1). A thorough study of Green River bitumen including VPO and FIMS molecular weight data has been published by McKay.14-16 Recognizing that his samples and ours may be significantly different if isolated from different places in the Green River formation, we will still proceed with a comparison of our results. The comparison may reveal more about sample variability in the Green River formation than the different techniques used. The relevant data are contained in Table 3. The isolation procedures used, including the extraction solvent, were also different and this will result in some differences in the bitumen samples analyzed. Mckay's FIMS results for the pyridine extract of Green River oil shale agree reasonably well with o u r PDMS data for the toluene extract of the demineralized material (Tables 1-3) and both are consistent with our VPO number average molecular weight. The VPO average molecular weight measured by McKay is significantly higher. A comparison of the intensity vs m / z plots (Figure 3, ref 16, with Figure 2 this paper) reveals significantly different shapes. McKay also published FIMS spectra and VPO results on bitumen isolated by supercritical extraction.14-16We calculated M , and M , from his mass spectra by evenly
0
1
2
3
m/z
4
5 IX 10001
Figure 4. PDMS spectrum of toluene-insoluble fraction of
Rundle bitumen raw data and the smoothed spectrum with the Mylar disk background subtracted (lower line). dividing the mass range between 200 and 2000 into 19 areas. The intensity of each was measured and M,, and M , calculated in the usual way. The results are given in Table 3. There is no similarity between McKafs VPO and FIMS data and no similarity with ours. Rundle bitumen behaves differently from Green River bitumen. Figures 3 and 4 display molecular weight distributions of the toluene-soluble and toluene-insoluble fractions of Rundle bitumen. A comparison of the PDMS curves reveals that the toluene-soluble Rundle bitumen has less high molecular weight material than Green River bitumen. The number average molecular weight calculated from this spectrum agrees with the VPO result. We could not use VPO to determine the number average molecular weight of the toluene-insoluble fraction because we were unable to find a suitable solvent. Characterization of this sample will be also difficult using GPC and other analytical techniques requiring dissolution. The PDMS method used here is uniquely effective with samples having limited solubility. This sample was dissolved in toluene a t 80 "C, deposited on the aluminized Mylar disk, and run normally. Figure 3 reveals a trimodal molecular weight distribution with peaks a t about 400,900, and 1300 m / z . This trimodal distribution of Rundle bitumen differs from a previously reported bimodal distribution.' PDMS is providing
Bitumen Molecular Weight Distributions
Energy & Fuels, Vol. 9,No. 5, 1995 763
I X 1001
(X 1001
0
I
2
m/z
3
4
Figure 5. PDMS spectrum of Athabasca bitumen raw data and the smoothed spectrum with the Mylar disk background subtracted (lower line).
information which does not appear in the gel permeation chromatogram. The trimodal distribution could be due to the origin of the deposit, its maturation chemistry, or some combination of the two. Comparing average molecular weights measured in two independent ways is a minimal test of a technique for measuring molecular weight distributions. While disagreement is conclusive, agreement does not demonstrate the correctness of the distribution. The most reliable bitumen molecular weight distribution was published by Ternan and co-workers a t CANMET, who provided us with samples characterized using their published t e ~ h n i q u e . ~ ~ ~ ~ Dr. Ternan kindly sent us three samples: an Athabasca bitumen closely similar in molecular weight distribution to that p ~ b l i s h e da, ~f 5 2 5 "C boiling point fraction of Athabasca bitumen, and a f 5 2 5 "C boiling point fraction from a hydrocracked bitumen. The last two fractions have been described.21122Their PDMS molecular weight distributions are shown in Figures 5-7. While of similar overall shape, the distributions are different. The PDMS molecular weight distributions are compared with the published molecular weight distributions in Figures 8-10. The Mylar disk background was subtracted from the PDMS spectra. Then, the sample spectra were smoothed using Statgraphics to make the comparison easier. The bars are the relative mass intensity measured by W O of fractions separated by preparative gel permeation chromatography. For Athabasca bitumen (Figure 81,the two techniques agree well for masses greater than 300 and are in serious disagreement below 300. As expected, this leads to a lower reported number average molecular weight using PDMS. The f 5 2 5 "C boiling fraction molecular weight distribution is shown in Figure 9. The general s h a p e of the distribution above 600 amu is the same for both techniques, but PDMS shows much more low molecular weight material than does GPCNPO. The same is true for the +525 "C hydrocracked fraction (Figure 10). ( 2 0 ) Furimsky, E.; Champagne, P. J. Fuel Process. Technol. 1982, 6. 269-275. (21) Ternan, M.; Rahimi, P. M.; Clugston, D. M. Energy Fuels 1994,
8. 518-530. (22) Ternan, M., personal communication.
0
5
IX 10001
1
3
2
5
4
m/z
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Figure 6. PDMS spectrum of f 5 2 5 "C residue from Athabasca bitumen with raw data (upper line) and the smoothed spectrum with the Mylar disk background subtracted (lower line). I X 100)
1
0
2
3
5 I X 10001
4
m/z
Figure 7. PDMS spectrum of +525 "C residue from unimodal catalyst raw data (upper line) and the smoothed spectrum with the Mylar disk background subtracted (lower line). 500
'
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~
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~
,
~
~
~
~
,
"
'
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% ool 0
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1000
2000
3000
4000
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Figure 8. Comparison of the smoothed PDMS spectrum (Mylar disk background subtracted) with GPCNPO molecular weight distribution of Athabasca bitumen.
There is a systematic difference between the PDMS and the GPCNPO results. PDMS "sees" more low molecular weight materials than GPCNPO does. The three possible explanations are (1)the PDMS is making the low molecular weight ions by fragmenting large structures, or (2) the small molecules are associating in the THF solvent used for the VPO measurements, or (3) the PDMS technique has a bias toward low mass
~
,
'
Larsen and Li
764 Energy & Fuels, Vol. 9, No. 5, 1995
low mass. It seems to be reliable at high mass and can certainly be used in a comparative way. PDMS shows promise as a routine tool for measuring bitumen molecular weight distributions. More work is necessary to resolve the discrepancy between PDMS and GPCNPO at low molecular weight.
t L
400
c M
200
-
-
100
-
-
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d
0
r
. ,
0 0
1000
3000
2000
,
,
,
, , 4000
,
,
, ,
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Figure 9. Comparison of the smoothed PDMS spectrum (Mylar disk background subtracted) with the GPCNPO molecular weight distribution of the +525 "C residue from Athabasca bitumen.
I 3 0 0 1 1 h [I/ - I 400
L
W . , I
Y
" W a
J
---
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Figure 10. Comparison of the smoothed PDMS spectrum (Mylar disk background subtracted) with the GPCNPO molecular weight distribution of the +525 "C residue from unimodal catalyst.
materials. Molecular association is a notorious problem in heavy hydrocarbon chemistry including VPO, and its occurrence here would not be surprising. We do not anticipate a large amount of fragmentation in the PDMS experiments, but suitable model polymers of known molecular weight distribution are not available and this point is difficult to check. Fragmentation has not been a problem in our other studies,17 but significant fragmentation of hydrocarbons has been reported.lg The technique is not differentially sensitive to aliphatic and aromatic compounds below 1500 amu. Finally, there may be an instrumental bias toward low mass. Microchannel plate detectors have a significant m / z dependence up to -1000 m l z after which it remains con~ t a n t It . ~is~more sensitive to low mass ions. In spite of this, polymer average molecular weights measured by GPC, GC, NMR, and time-of-flight mass spectrometry using microchannel plate detectors were all in agreement.24 This bias may not be a problem. Also, the sputtering and/or ionization efficiency may be higher at low mass than that at high mass. There is ample reason t o suspect the reliability of the PDMS data at (23) Brunelle, A.; Della-Negra, S.; Depauw, U.; Le Beyec, Y.; Baptista, G. B. Proc. 39th ASMS Conf. Mass Spectrom. Allied Top. 1991, 1733-1734. (24) Bletsos, I. V.; Hercules, D. M.; van Leyen, D.; Hagenhoff, B.; Niehuis, E.; Benninghoven, A. Anal. Chem. 1991, 63, 1953-1960.
Experimental Section Bitumens. Green River and Rundle oil shales (20-100 mesh) were demineralized for 48 h using H C M F proced ~ r e . Following ~ ~ , ~ ~the demineralizations, the kerogens were Soxhlet-extracted with toluene until there was no color observable in the solutions. The amount of bitumen was determined by removing toluene in a rotary evaporator followed by vacuum drying a t 105 "C. Demineralizations and Soxhlet extractions were performed under dry Nz atmospheres. Athabasca bitumen and its two products were supplied by Dr. Marten Ternan of Canada Center for Mineral and Energy Technology (CANMET). Plasma Desorption Mass Spectrometry. Bio Ion 20 252Cfplasma desorption time-of-flight mass spectrometry was used for determining molecular weight distributions. Aluminized Mylar disks obtained from Applied Biosystems Inc. were used as the sample supports. Bitumen solutions were prepared to concentrations of ca. 10 mg/mL. Sample disks for PDMS determination were coated by dropping 20-40 p L of bitumen solutions on aluminized Mylar disks followed by blowing with dry Nz. We selected positive 10 kV acceleration voltage and 1 nslchannel time resolution as the working conditions and collected lo6 primary ion events for each spectrum. H+ and Na+ were used as the calibration standards. Calibration was checked using Porcine insulin of molecular weight 5778 amu. The measured molecular weight was 5790 amu, within instrument specifications of the actual. Previously developed software (CFINT) is capable of transferring the data from the Bio Ion 20 PDP-11 computer to a PC and of subtracting the Mylar disk background. We replotted the spectra and calculated the average molecular weights using Statgraphics and Quattro Pro. A detailed description of sample disk preparation, PDMS technique, and data treatment has been previously r e ~ 0 r t e d . l ~ Vapor Pressure Osmometry. A Knauer Dampfdruck osmometer was used for determining the number average molecular weight of Green River bitumen and toluene-soluble fraction of Rundle bitumen. Benzil was used as the calibration standard. The molecular weight of 2500 amu polystyrene standard from Polysciences, Inc. was determined as a reliability check. The measured molecular weight was 2265 i 184. For Green River bitumen, M , was calculated by using seven measurements (1.26, 1.86, 2.99, 4.21, 4.86, 7.13, 9.62 mg/g) in toluene at 48 "C; for the toluene-soluble fraction of Rundle bitumen, M , was calculated using six measurements (1.88, 3.34, 4.06, 5.63, 7.60, 10.5 mg/g) in THF at 45 "C. The principle and procedures of VPO are described in ref 27.
Acknowledgment. We thank Dr. Michael Siskin for providing Green River and Rundle oil shales, Dr. Marten Ternan for sending Athabasca samples, and Dr. Patrick Wernett for writing the CFINT program. Acknowledgment is made to the donors of the Petroleum Research Fund, administered by the American Chemical Society, for partial support of this research. EF9402210 (25) Durand, B.; Nicaise, G. In Kerogen; Durnad, B., Ed.; Editions Technip: Paris, 1980. (26) Saxby, J. D. In Oil Shale; Yen, T. F., Chilingarian, G. V., Eds.; Elsevier Sci. Pub. Co.: Amsterdam, 1976. (27) Larsen, J. W.; Choudhury, P. J. Org. Chem. 1979, 44 (161, 2856-2859.
