Detailed Chemical Composition of Straight-Run Vacuum Gas Oil and

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Detailed Chemical Composition of Straight-Run Vacuum Gas Oil and Its Distillates as a Function of the Atmospheric Equivalent Boiling Point Wei Wang,* Yingrong Liu, Zelong Liu, and Songbai Tian Research Institute of Petroleum Processing, SINOPEC, Beijing 100083, People’s Republic of China S Supporting Information *

ABSTRACT: The boiling point distribution of petroleum samples remarkably affects the refining process and economic evaluation. The chemical composition of petroleum samples also varies with the boiling range, which is even more important for the processing procedure. In this work, a quick and convenient method was developed to build a clear relationship between boiling points and structures of organic compounds. A straight-run vacuum gas oil (VGO) and its narrow distillates were characterized by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The boiling point distribution of the main species in the petroleum samples was obtained by combining the FT-ICR MS data and the predicted boiling points of the compounds. Traditional gas chromatographic simulated distillations were also carried out to calibrate the boiling point distributions based on FT-ICR MS data. The detailed chemical composition of VGO varied as a function of the atmospheric equivalent boiling point (AEBP). Moreover, some composition information on the narrow cuts was calculated by the chemical composition of VGO. The calculated values matched well with the measured values of the narrow cuts by FT-ICR MS. containing compounds, 16−19 nitrogen-containing compounds,16,19−23 and petroleum acids21−25 have been comprehensively characterized in the distillates of different boiling ranges. Through these works, the composition of petroleum samples has been associated with the boiling points. It should be noted that the information obtained by FT-ICR MS strongly depends upon the applied ionization technique, because samples may exhibit different ionization efficiencies and response behaviors under various ionization sources.26−28 For example, saturated hydrocarbons can be effectively ionized by an atmospheric pressure chemical ionization (APCI) technique,29 but the ionization efficiency is much lower in the atmospheric pressure photoionization (APPI) source.30 To predict the properties of complex petroleum mixtures from molecular structures, a series of methods has been developed. Kinney reported an empirical formula to describe the relationship between the boiling points and the molecular structures of organic compounds, and the relationship was validated in the carbon number range of C1−C19.31 Quann et al. developed the structure-oriented lumping (SOL) method and obtained the boiling points of hydrocarbons and petroleum acids.32,33 In combination with the MS data, the distribution of these species with boiling points was acquired and the predicted results were consistent with the experimental measurements. Horton et al. also built a molecular-level kinetic model and predicted the boiling point distribution of the pyrolysis product by this model.34,35 The prediction methods by Quann et al. and Horton et al. are impactful in describing the reactions and properties of the complex petroleum samples, but the procedures are relatively complicated, which may hinder the

1. INTRODUCTION The boiling point distribution is a basic property for designing the processing procedure and predicting the economic value of petroleum samples. Physical distillation procedures1,2 or gas chromatographic simulated distillations3−5 are widely applied to obtain the boiling point distribution of crude oil and its distillation fractions. The boiling point profiles of sulfur and nitrogen elements in petroleum samples have also been measured by gas chromatography coupled with sulfur and nitrogen chemiluminescence detectors (GC−SCD and GC− NCD).6,7 However, these traditional methods cannot provide the detailed chemical composition of petroleum samples across the boiling ranges, which is of critical importance for the refining process. Mass spectrometry (MS) is a powerful tool to provide the detailed chemical composition of crude oil and its fractions. Boduszynski et al. obtained the molecular characterization of crude oils by field ionization and field desorption mass spectrometry (FI/FD MS) and found that the molecular weight, hydrogen deficiency, and heteroatom concentration increased as a function of the atmospheric equivalent boiling points (AEBPs) of crude oils.8−11 Roussis et al. measured the distributions of hydrocarbon compound types across the boiling range for crude oils by coupling the gas chromatographic simulated distillation with quadrupole MS.12 Chen et al. developed a method to predict the molecular weight of middle distillates with the variation of boiling point using GC−FI MS.13 As a result of the ultrahigh mass resolution of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS),14,15 more detailed analysis of petroleum samples can be achieved, including the distribution of heteroatom class, double bond equivalence (DBE), and carbon number. Then, the compositional variations of aromatic hydrocarbons,16−18 sulfur© 2016 American Chemical Society

Received: November 30, 2015 Revised: January 22, 2016 Published: January 26, 2016 968

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Figure 1. AEBPs of aromatic hydrocarbons with different carbon numbers and DBEs. The boiling points of n-paraffins were also listed as a reference. 2.2. MS Analysis. VGO and the distillate fractions were dissolved in toluene and diluted to 0.5 mg/mL. The prepared samples were introduced through a fused-silica capillary at a rate of 360 μL/h by a syringe pump (Hamilton Corp.). Analyses were conducted on a 9.4 T Bruker Apex FT-ICR MS. APPI+ was used as the ionization source. Nitrogen served as the drying gas and nebulizing gas. The drying gas flow rate was set at 4.0 L/min at the temperature of 200 °C. The nebulizing gas flow rate was set at 1.0 L/min, and the APPI temperature was 400 °C. The skimmer voltage was set to 30.0 V. The m/z range was from 200 to 800 for VGO and F2−F8, and the m/z range was from 100 to 800 for F1. The data size was 4 M, and the time-domain data sets were 256 scans. 2.3. Mass Calibration and Data Analysis. The APPI FT-ICR MS spectra were externally calibrated by Tuning Mix (Agilent Corp.). The molecular ions were dominant in APPI FT-ICR MS spectra. The peaks of the molecular ions with a relative abundance greater than six standard deviations of baseline root-mean-square (rms) noise (6σ) were chosen for the data analysis. Chemical formulas of the peaks (CcHhNnOoSs) were calculated according to the m/z values within ±1 ppm.

application to the boiling point distribution of petroleum samples. In the current work, the model by Kinney was improved to suit the carbon number range of C10−C50. Then, the boiling points of organic compounds with given DBE (3−23) and carbon number (C10−C50) were predicted and evaluated by comparing the predicted boiling points to some reported boiling points. Moreover, a straight-run vacuum gas oil (VGO) and its eight distillation fractions were characterized by positive atmospheric pressure photoionization (APPI+) FT-ICR MS. The boiling point distributions of the main species ionized by APPI+ were obtained by combining the FT-ICR MS data and the predicted boiling points. This method was further validated by comparing to the gas chromatographic simulated distillation results. Some of the chemical compositions of the eight distillation fractions were also predicted by the composition of the unfractionated VGO. The predicted values were generally consistent with the experimental results.

3. RESULTS AND DISCUSSION 3.1. Improved Prediction Method of the AEBP. The complexity of petroleum molecules has been widely reported.26,36 The tremendous number of isomers makes it almost impossible to measure or distinguish all of the compounds in petroleum. However, the prediction of the boiling point for a certain compound requires an unambiguous structure of the compound. It has been reported that the aromatic ring structures in VGO samples are mainly monoaromatic type.37 The structure of the side chain is much more complicated as a result of the position, number, and

2. EXPERIMENTAL SECTION 2.1. Sample Preparation. A straight-run VGO was distilled into eight narrow cuts F1 [initial boiling point (IBP)−350 °C], F2 (350− 380 °C), F3 (380−410 °C), F4 (410−440 °C), F5 (440−470 °C), F6 (470−500 °C), F7 (500−530 °C), and F8 (>530 °C). The total samples of VGO and its distillates were measured by APPI FT-ICR MS. The aromatic fractions of VGO and the distillate fractions F1−F8 were separated according to ASTM D2549. The aromatic fractions of VGO and F1−F7 were measured by gas chromatographic simulated distillation with ASTM D2887, while the aromatic fraction of F8 was measured by ASTM D6352. 969

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(S1 and S2 species) according to the APPI method. When the boiling range rises up from F1 to F8, the relative abundance of HC species significantly reduces, while the relative abundance of S2 species increases. The relative abundance of S1 species varies a little in the boiling range and decreases slightly in the high boiling fractions F7 and F8. 3.3. Boiling Point Distribution of VGO and Its Distillation Fractions. The DBE versus carbon number distribution of aromatic hydrocarbons (HC) in VGO is illustrated in Figure 3. The size of the bubble indicates the

isomerization of the substituent alkyl groups. However, the boiling points of most isomers are close to the n-alkyl side chain with the same carbon number.38 In this work, the aromatic molecules in the straight-run VGO are presumed to be mainly in the form of a monoaromatic structure and n-alkyl side chain. It has been reported before that the AEBPs of organic compounds have a good relationship with the boiling point number, which is a parameter connected with the structure of the molecule.31 In this work, the relationship is improved in the form of empirical formula 1, and it is better for the carbon number range of C10−C50. A more detailed discussion of the relationship between the AEBP and boiling point number can be found in Figures S1−S3 of the Supporting Information Tb = 263.97 ln(Nb) − 726.93

(1)

where Tb is the AEBP of the organic compound (°C) and Nb is the boiling point number of the molecule. The value of the boiling point number is determined by the aromatic ring structures and side chains of the molecules. For the compounds containing a monoaromatic structure and nalkyl side chain, there exists a relationship described in empirical formula 239 Nb,n = Nb,0 + 0.8n + 1.0 × 2n

Figure 3. DBE versus carbon number distribution of aromatic hydrocarbons in VGO. The compounds in the boiling range of 390− 400, 490−500, and 590−600 °C are labeled with different colors.

(2)

relative abundance of the compounds. The boiling point of each compound with the determined DBE and carbon number can be found in Figure 1. The relative abundance of the compounds in the same boiling point range is summed up to represent the distillation yield of the narrow boiling range. The temperature interval of the boiling point is 10 °C, and three boiling point ranges (390−400, 490−500, and 590−600 °C) are labeled in Figure 3 as an illustration. The same processes are also applied to S1 and S2 species in VGO as well as these main species in all distillation fractions. The boiling point distributions of HC, S1, and S2 species in VGO and its fractions are shown in panels a−c of Figure 4. By combination of the boiling point distributions of each species, the boiling point distribution of the whole oils is obtained and illustrated in Figure 4d. The gas chromatographic simulated distillation is a classic method to provide the boiling point distribution of the whole oils. It has been reported that the saturated hydrocarbons in petroleum samples cannot be effectively ionized by the APPI source.17,30 The APPI spectra of pyrene and hexadecahydropyrene at the same concentration also indicate the low ionization efficiency of naphthenes compared to aromatic hydrocarbons (shown in Figure S6 of the Supporting Information). As a result, the APPI FT-ICR MS data mainly reflect the composition of aromatic fractions of VGO and its distillates. The boiling point distributions of the aromatic fractions measured by gas chromatographic simulated distillations are shown in Figure 5. It is found that the total boiling point distribution calculated by FT-ICR MS data (Figure 4d) is shifted to the high boiling direction for about 50 °C. The reason may be due to the mass discrimination in FT-ICR MS caused by the time-of-flight effects and gated trapping.40,41 To counteract the mass discrimination, the curves obtained by FT-ICR MS data have to be shifted to the low boiling direction for 50 °C. Then, the boiling point distribution of VGO and its fractions obtained by gas chromatographic simulated distillations and FT-ICR MS data are compared in Figure 6. Generally, the results of the two methods match quite well with each other. For VGO with a wide boiling range, the

where Nb,n is the boiling point number of the molecule with a n-alkyl side chain, Nb,0 is the boiling point number of the monoaromatic ring without any side chains, and n is the carbon number of the side chain. As a result, the relationship between the AEBP of the compounds with and without n-alkyl side chains can be derived by empirical formulas 1 and 2 Tb,n = 263.97 ln(e(Tb,0+ 726.93)/263.97 + 2.8n) − 726.93

(3)

where Tb,n is the AEBP of the compound with a n-alkyl side chain (°C), Tb,0 is the AEBP of the compound without any side chains (°C), and n is the carbon number of the side chain. Generally, the AEBP of most monoaromatic compounds without any side chains can be easily obtained from databases, such as National Institute of Standards and Technology (NIST) Chemistry and SciFinder Scholar. The AEBPs of the monoaromatic hydrocarbons with different carbon numbers and DBEs are shown in Figure 1. The calculated data of AEBP by formula 3 is consistent with the reported data. The calculated AEBPs of monoaromatic S1 and S2 species can be found in Figures S4 and S5 of the Supporting Information. 3.2. Heteroatom Class Distribution of VGO and Its Distillation Fractions. The heteroatom class compositions for VGO and its distillation fractions are shown in Figure 2. The most abundant species in these samples are aromatic hydrocarbons (HC species) and sulfur-containing compounds

Figure 2. Relative abundance of heteroatom class distribution of VGO and its distillates. 970

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Figure 4. Boiling point distributions of main species in VGO and its distillates: (a) HC species, (b) S1 species, (c) S2 species, and (d) sum of HC, S1, and S2 species.

the compounds distributing in a certain boiling range of VGO behave with a similar distribution of the carbon number and DBE to the corresponding narrow distillates of F1−F8. It is noted that the compounds in the narrow cuts are more complicated than expected, and some compounds with boiling points out of the distillation range are observed in the narrow cuts. The reason may be that the distillation process cannot separate the petroleum samples exactly as a result of the formation of azeotropes. This phenomenon is also supported by the gas chromatographic simulated distillation results (Figure 5), because the actual boiling ranges of the narrow cuts are always wider than the distillation temperature ranges. Furthermore, the boiling point distribution of the compounds in VGO can be used to predict some chemical compositions of the narrow cuts. The average carbon number and DBE of the aromatic hydrocarbons are considered as a function of the AEBP, as shown in Figure 8. The calculated values are obtained from the FT-ICR MS data and boiling point distribution of VGO, while the measured values are determined by the FT-ICR MS data of the narrow cuts F1−F8. The calculated carbon number is basically consistent with the measured values, while the calculated DBE has a tendency similar to the measured values. However, the measured value of the heaviest fraction F8 is quite different from the calculated carbon number and DBE. The reason may be that more compounds with high carbon number and low DBEs are detected in F8 than in VGO. The absence of these compounds in VGO may be due to the matrix effects and/or ionization suppression.42 The boiling point distributions of S1 and S2 species in VGO are also obtained as the HC species. The relative abundance of HC, S1, and S2 species of the narrow cuts can then be calculated according to the data of VGO, as shown in Figure 9. The calculated values reveal that the relative abundance of HC species reduces, while the relative abundance of S2 species increases, with the rise of the boiling point, which matches

Figure 5. Boiling point distributions of the aromatic fractions of VGO and its distillates measured by gas chromatographic simulated distillations.

distillation yield according to the FT-ICR MS result is underestimated in the low boiling range (350−450 °C) and high boiling range (>540 °C) while a little overrated in the middle boiling range (450−540 °C). The distillation yields of F7 and F8 calculated by FT-ICR MS are visibly lower than the gas chromatographic simulated distillation results in the high boiling range, because the unconsidered species (such as N1 and N1S1) are more abundant in these fractions. Nevertheless, the distillation behaviors of VGO and its fractions described by the FT-ICR MS data are mainly consistent with the traditional gas chromatographic simulated distillation results. 3.4. Boiling Point Distribution of the Compounds in VGO and Its Distillation Fractions. The boiling point distributions of HC species in VGO and its distillation fractions are shown in Figure 7. The boiling points of the compounds with a given DBE and carbon number have been calibrated according to the gas chromatographic simulated distillation results. The carbon number and DBE of HC species increase to a higher direction with the rising boiling range, which is consistent with former reports.16−18 For compounds in the same narrow boiling range, the increase of DBE is generally accompanied by the decline of the carbon number. Moreover, 971

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Figure 6. Boiling point distributions of VGO and its distillates measured by gas chromatographic simulated distillations and calculated from FT-ICR MS data.

Figure 7. DBE versus carbon number distribution of aromatic hydrocarbons in VGO and its distillates labeled with different boiling ranges.

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Figure 8. Correlation of the (a) average carbon number and (b) average DBE with the boiling points. The calculated value is based on the composition of VGO, while the measured value is obtained from the composition of each narrow distillate.

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Figure 9. Relative abundance of HC, S1, and S2 species in the distillates. The calculated value is based on the composition of VGO, while the measured value is obtained from the composition of each narrow distillate.

C1−C19 (Figure S1), relationship between the boiling point (°C) and boilng point number in the carbon number range of C10−C49 (Figure S2), boiling point of alkyl benzenes with carbon number from C10 to C50 (Figure S3), AEBP of S1 species with different carbon numbers and DBEs (Figure S4), AEBP of S2 species with different carbon numbers and DBEs (Figure S5), and APPI FT-ICR MS spectra of pyrene and hexadecahydropyrene at the same concentration of 0.1 mg/mL (Figure S6) (PDF)

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

quite well with the measured values of the narrow cuts by APPI FT-ICR MS.

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ACKNOWLEDGMENTS This work was supported by the Major State Basic Research Development Program of China (973 Program, 2012CB224801).

4. CONCLUSION In this work, the relationship between the AEBP of organic compounds with and without n-alkyl side chains was established. Then, the boiling point of the organic compound with a given DBE and carbon number was calculated by the improved empirical formula. The predicted boiling points matched well with the reported boiling points in the carbon number range of C10−C50. The boiling point distributions of VGO and its distillate fractions were acquired on the basis of the FT-ICR MS data and the predicted boiling points. In comparison to the traditional gas chromatographic simulated distillation results, the calculated boiling point distribution curves shifted to the high boiling range for around 50 °C as a result of the mass discrimination of FT-ICR MS. The boiling point distributions of the main species in VGO and its distillate fractions were also discussed after calibrating the temperature by gas chromatographic simulated distillation. The results revealed that the detailed boiling point distribution of the compounds in VGO was able to predict some chemical compositions of the narrow cuts.

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NOMENCLATURE AEBP = atmospheric equivalent boiling point VGO = vacuum gas oil FT-ICR MS = Fourier transform ion cyclotron resonance mass spectrometry REFERENCES

(1) ASTM International. ASTM Standard D1160-15. In Standard Test Method for Distillation of Petroleum Products at Reduced Pressure; ASTM International: West Conshohocken, PA, 2015; DOI: 10.1520/ D1160-15. (2) ASTM International. ASTM Standard D2892-15. In Standard Test Method for Distillation of Crude Petroleum (15-Theoretical Plate Column); ASTM International: West Conshohocken, PA, 2015; DOI: 10.1520/D2892-15. (3) ASTM International. ASTM Standard D2887-15. In Standard Test Method for Boiling Range Distribution of Petroleum Fractions by Gas Chromatography; ASTM International: West Conshohocken, PA, 2015; DOI: 10.1520/D2887-15. (4) ASTM International. ASTM Standard D6352-15. In Standard Test Method for Boiling Range Distribution of Petroleum Distillates in Boiling Range from 174 to 700 °C by Gas Chromatography; ASTM International: West Conshohocken, PA, 2015; DOI: 10.1520/D635215. (5) ASTM International. ASTM Standard D7500-15. In Standard Test Method for Determination of Boiling Range Distribution of Distillates and Lubricating Base OilsIn Boiling Range from 100 to 735 °C by Gas

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.energyfuels.5b02803. AEBP (Tb) and boiling point number (Nb) of n-paraffins (Table S1), relationship between the boiling point (°C) and boiling point number in the carbon number range of 973

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Energy & Fuels Chromatography; ASTM International: West Conshohocken, PA, 2015; DOI: 10.1520/D7500-15. (6) Ng, S.; Briker, Y.; Zhu, Y.; Gentzis, T.; Ring, Z.; Fairbridge, C.; Ding, F.; Yui, S. Energy Fuels 2000, 14, 945−946. (7) Revellin, N.; Dulot, H.; Lopez-Garcia, C.; Baco, F.; Jose, J. Energy Fuels 2005, 19, 2438−2444. (8) Boduszynski, M. M. Energy Fuels 1987, 1, 2−11. (9) Boduszynski, M. M. Energy Fuels 1988, 2, 597−613. (10) Altgelt, K. H.; Boduszynski, M. M. Energy Fuels 1992, 6, 68−72. (11) Boduszynski, M. M.; Altgelt, K. H. Energy Fuels 1992, 6, 72−76. (12) Roussis, S. G.; Fitzgerald, W. P. Anal. Chem. 2000, 72, 1400− 1409. (13) Chen, J.; Mclean, N.; Hager, D. Energy Fuels 2011, 25, 719−726. (14) Qian, K.; Rodgers, R. P.; Hendrickson, C. L.; Emmett, M. R.; Marshall, A. R. Energy Fuels 2001, 15, 492−498. (15) Qian, K.; Robbins, W. K.; Hughey, C. A.; Cooper, H. J.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2001, 15, 1505−1511. (16) Fu, J.; Kim, S.; Rodgers, R. P.; Hendrickson, C. L.; Marshall, A. G.; Qian, K. Energy Fuels 2006, 20, 661−667. (17) McKenna, A. M.; Purcell, J. M.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2010, 24, 2929−2938. (18) McKenna, A. M.; Blakney, G. T.; Xian, F.; Glaser, P. B.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2010, 24, 2939−2946. (19) Liu, P.; Shi, Q.; Pan, N.; Zhang, Y.; Chung, K. H.; Zhao, S.; Xu, C. Energy Fuels 2011, 25, 3014−3020. (20) Pakarinen, J. M. H.; Teräväinen, M. J.; Pirskanen, A.; Wickström, K.; Vainiotalo, P. Energy Fuels 2007, 21, 3369−3374. (21) Stanford, L. A.; Kim, S.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2006, 20, 1664−1673. (22) Teräväinen, M. J.; Pakarinen, J. M. H.; Wickström, K.; Vainiotalo, P. Energy Fuels 2007, 21, 266−273. (23) Shi, Q.; Zhao, S.; Xu, Z.; Chung, K. H.; Zhang, Y.; Xu, C. Energy Fuels 2010, 24, 4005−4011. (24) Avila, B. M. F.; Vaz, B. G.; Pereira, R.; Gomes, A. O.; Pereira, R. C. L.; Corilo, Y. E.; Simas, R. C.; Nascimento, H. D. L.; Eberlin, M. N.; Azevedo, D. A. Energy Fuels 2012, 26, 5069−5079. (25) Smith, D. F.; Rodgers, R. P.; Rahimi, P.; Teclemariam, A.; Marshall, A. G. Energy Fuels 2009, 23, 314−319. (26) Panda, S. K.; Andersson, J. T.; Schrader, W. Angew. Chem., Int. Ed. 2009, 48, 1788−1791. (27) Gaspar, A.; Zellermann, E.; Lababidi, S.; Reece, J.; Schrader, W. Anal. Chem. 2012, 84, 5257−5267. (28) Ruddy, B. M.; Huettel, M.; Kostka, J. E.; Lobodin, V. V.; Bythell, B. J.; McKenna, A. M.; Aeppli, C.; Reddy, C. M.; Nelson, R. K.; Marshall, A. G.; Rodgers, R. P. Energy Fuels 2014, 28, 4043−4050. (29) Tose, L. V.; Cardoso, F. M.; Fleming, F. P.; Vicente, M. A.; Silva, S. R.; Aquije, G. M.; Vaz, B. G.; Romao, W. Fuel 2015, 153, 346−354. (30) Hourani, N.; Muller, H.; Adam, F. M.; Panda, S. K.; Witt, M.; Al-Hajji, A. A.; Sarathy, S. M. Energy Fuels 2015, 29, 2962−2970. (31) Kinney, C. R. J. Am. Chem. Soc. 1938, 60, 3032−3039. (32) Quann, R. J.; Jaffe, S. B. Ind. Eng. Chem. Res. 1992, 31, 2483− 2497. (33) Qian, K.; Edwards, K. E.; Dechert, G. J.; Jaffe, S. B.; Green, L. A.; Olmstead, W. N. Anal. Chem. 2008, 80, 849−855. (34) Horton, S. R.; Hou, Z.; Moreno, B. M.; Bennett, C. A.; Klein, M. T. Sci. China: Chem. 2013, 56, 840−847. (35) Horton, S. R.; Zhang, L.; Hou, Z.; Bennett, C. A.; Klein, M. T.; Zhao, S. Ind. Eng. Chem. Res. 2015, 54, 4226−4235. (36) Shi, Q.; Hou, D.; Chung, K. H.; Xu, C.; Zhao, S.; Zhang, Y. Energy Fuels 2010, 24, 2545−2553. (37) Qian, K.; Edwards, K. E.; Mennito, A. S.; Freund, H.; Saeger, R. B.; Hickey, K. J.; Francisco, M. A.; Yung, C. Y.; Chawla, B.; Wu, C.; Kushnerick, J. D.; Olmstead, W. N. Anal. Chem. 2012, 84, 4544−4551. (38) Mahe, L.; Courtiade, M.; Dartiguelongue, C.; Ponthus, J.; Souchon, V.; Thiebaut, D. J. Chromatogr. A 2012, 1229, 298−301. (39) Kinney, C. S. Ind. Eng. Chem. 1940, 32, 559−562. (40) Wong, R. L.; Amster, I. J. J. Am. Soc. Mass Spectrom. 2006, 17, 205−212.

(41) Kaiser, N. K.; Skulason, G. E.; Weisbrod, C. R.; Bruce, J. E. J. Am. Soc. Mass Spectrom. 2009, 20, 755−762. (42) Cho, Y.; Na, J. G.; Nho, N. S.; Kim, S. H.; Kim, S. Energy Fuels 2012, 26, 2558−2565.

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