Characterization of Heavy Oil by FT-ICR MS Coupled with Various Ionization Techniques

Transcription

1 Journal of the Japan Petroleum Institute, 52, (4), (2009) 159 [Review Paper] Characterization of Heavy Oil by FT-ICR MS Coupled with Various Ionization Techniques Keiko Miyabayashi *, Yasuhide Naito, and Mikio Miyake * School of Materials Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa , JAPAN (Received November 4, 2008) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) has high resolution, so provides a viable method to characterize extremely complex mixtures. The molecular formulas of individual components are determined simply by accurate mass measurement. Here, recent advances in FT-ICR MS application to petroleum derived heavy materials are reviewed after a brief introduction of the features and history of FT-ICR MS. Advantages and limitations of ionization techniques, such as electron ionization (EI), electrospray ionization (ESI), field desorption (FD), and liquid secondary ionization (LSI), connected to FT-ICR MS are evaluated by application to petroleum derived materials. Our improved ionization techniques are also explained to adapt very complex petroleum derived samples, ex., to suppress fragmentation and to accelerate vaporization in EI, and to detect specific compounds selectively in ESI. Characterization procedures to estimate the structural features of components can be based on heteroatom composition, carbon number and Z-value (hydrogen deficiency index, as a measure of degree of aromatic ring condensation), through spectral analysis using the Kendrick mass. Such characterization can be applied to estimate structural changes of components during hydroprocessing. Keywords Structural characterization, Heavy oil, FT-ICR MS, Electrospray ionization, In-beam EI, Liquid secondary ionization 1. Introduction pipes 2). Fragmentation of the ionized sample is the essential problem with the application of EI to petro- Analysis of the components of petroleum derivatives leum related samples. The acquired mass spectra are has relied on fractionation, e.g., distillation or column complicated by fragmentation peaks, so correct assignchromatography. However, the various analytical ment of the parent peaks to the intact components techniques, such as density, distillation characteristics, becomes quite difficult. nuclear magnetic resonance (NMR), or vapor pressure The introduction of the double focusing sector type osmometry, provide only bulk and averaged structural mass spectrometer allowed further investigation of the information even after fractionation because of the characterization of heavy distillate by high resolution extreme complexity of petroleum. Mass spectrometry mass spectrometry. The use of on-line LC/MS comcoupled with two dimensional gas chromatography has bined with low-voltage electron-impact ionization (LVthe potential to identify individual components con- EI) medium resolution mass spectrometry (MRMS) and tained in light fractions of petroleum distillates (gaso- advanced analytical data handling procedures could line and kerosene) 1). Applications of this approach to provide in-depth molecular level characterization of heavy distillate have been unsuccessful, so development high-boiling petroleum and synthetic fuel fractions 3). of new techniques still remains a challenging research Fragmentation was reduced to some extent by using topic. LV-EI, but different soft ionization techniques are desir- The first applications of mass spectrometry to heavy able for petroleum chemistry because of the restrictions oil analysis used low or middle resolution mass spectrom- of sample volatility in EI. Field ionization (FI) and eter coupled with electron ionization (EI). High- field desorption (FD) ionization were candidates to temperature GC (HTGC) was used to analyze a series overcome such defects at that time. Atmospheric resiof hydrocarbons up to C75 in several geochemical sam- dues (AR) were analyzed from a variety of resources by ples, including oils and waxes precipitated in drill stem FI-MS. The AR samples were separated by boiling point and each fraction was further divided by aromatic * To whom correspondence should be addressed. ring size and polarity. These research was the first to * keiko@jaist.ac.jp, miyake@jaist.ac.jp characterize the comprehensive components of heavy

2 160 oil by mass spectrometry 4),5). Development of other soft ionization techniques, such as thermospray ionization (TSP), electrospray ionization (ESI), and atmospheric pressure chemical ionization (APCI), extended the range of target components in heavy oil. Components with boiling range> 565 could be analyzed using on-line LC TSP mass spectrometry 6). TSP selectively ionizes the aromatic hydrocarbons by protonation, but does not ionize saturated hydrocarbons. The facilitate method is based on using LC-TSP/MS to estimate the distribution of molecular weights and group types. Chemical ionization, liquid secondary ionization (fast atom (ion) bombardment), APCI, and ESI were evaluated in both positive and negative ion modes for the determination of the molecular distribution of naphthenic acids (without derivatization) in crude oils 7). Early application of ESI in petroleum analysis was begun with the detection of porphyrins as biomarkers 8). Jet fuel was characterized by ESI coupled with the triple quadrupole mass spectrometer. Therefore, a new range of information can now be obtained about the composition of polar species 9). Such soft ionization techniques, especially ESI, can detect trace amounts of polar components (containing S, N, and O) in petroleum related materials, and so has the potential to detect catalyst poisons or sedimentation species during storage. However, these trace species with multi-heteroatoms result in extremely complex spectra so multiple-stage chromatographic separations are required. Therefore, much higher spectral resolution is desired for advanced analysis of heavy petroleum distillates. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides the highest mass spectral resolution at present. Here, recent advances in the application and effectiveness of FT-ICR MS to characterize heavy petroleum derivatives are reviewed. The advantages of FT-ICR MS, procedures for selective analysis of targeted compounds from very complex spectra, and the latest research topics related to features of ionization procedures coupled with FT-ICR MS are discussed. In particular, our new strategies to detect targeted components efficiently by selection of ionization technique are interpreted. 2. Advantages of FT-ICR MS for Petroleum Analysis FT-ICR MS measures the cyclotron frequency of rotating ions in a homogeneous magnetic field, resulting in ultra-high resolution and highly accurate mass measurements with errors of less than 1 ppm 10). Therefore, components in petroleum samples can be determined without the need for prior separation. The ESI FT ICR mass spectrum of Arabian heavy vacuum gas oil Fig. 1 Positive ESI FT-ICR Mass Spectrum of AH-VGO Acquired FID was processed at different data points (a) 1 M points, (b) 512 k points, (c) 128 k points, (d) 64 k points, and (e) 32 k points. Peak resolution at m/z is denoted in the right side of the spectra. Fig. 2 Mass-scale Expanded Segments at m/z 251 of the AH-VGO Mass Spectrum Shown in Fig. 1 (AH-VGO) is shown in Fig. 1 as a typical example. The sample was not fractionated by chromatography. Over a thousand peaks were resolved and identified by a single acquisition procedure. The characterization method will be discussed in detail later. Figure 2 shows the mass-scale expanded segment at m/z 251. To demonstrate the high resolution requirement for petroleum analysis, the acquired free induced decay (FID) was processed at different data points. The number of baseline resolved peaks increased with higher resolution (resolution value is shown in the figure). The spectra shown in Fig. 2-(d) and 2-(e), which are comparable to those obtained by commercially available TOF mass spectrometry, do not have adequate resolution for petroleum analysis, since the observed single peak of No. 3 in Fig. 2-(e) consists of several different peaks (i.e., different compounds) from No. 4 to 12 in Fig. 2-(a), which correspond to the resolution of FT-ICR MS. Such peak coalescence in Fig. 2-(e) causes problems in the determination of peak position (mass value), lead-

3 161 ing to incorrect assignment of components in the petroleum distillate. Thus, characterization of individual components in the petroleum distillate requires high resolution. FT-ICR MS provides the highest mass resolution now available (Fig. 2-(a)) and is one of the most effective methods to analyze heavy petroleum materials. 3. Application of In-beam EI FT-ICR MS for AR, VGO, and Vacuum Residue (VR) EI is conventionally used ionization technique, which is usually coupled with gas chromatography, and is applied for characterizing gasoline, kerosene and gas oil. EI is effective for generating ions of a wide range of compounds that vaporize by heating, including both aliphatic and aromatic hydrocarbons with or without hetero atoms (sulfur, oxygen and/or nitrogen). EI FT ICR MS with 3 T superconducting magnet (SCM) was used to analyze a crude oil fraction 11) and a virgin vacuum gas oil 12). There was difficulty in acquiring high-resolution mass spectra over the full mass range due to the resolution at the relatively low magnetic field strength in both cases, and small segments of the mass range had to be collected at a time. The resolution of FT-ICR MS was improved by increasing the magnetic field to 5.6 T SCM in the compositional analysis of raw diesel fuel 13). Different boiling cuts of VGO were characterized by 7 T SCM with low voltage EI to suppress fragmentation and demonstrated an increase in the observed mass range up to m/z 500 depending on the boiling temperature of the VGO cut 14). Heavy distillate is believed to contain much higher molecular weight species than m/z 500 4). Detailed characterization of much heavier petroleum distillate is anticipated in the petroleum, plant and catalyst industries for effective utilization of heavy oil. However, the vaporization points of those molecules are generally higher than their pyrolysis points, so analyte molecules are decomposed faster than vaporized by the increasing temperature on the sample probe in conventional EI 17). Consequently, the mass spectra are complicated by fragmentary or decomposed ion peaks, especially in petroleum analysis. In particular, VR contains high boiling fractions in which many constituents are unionizable and undetectable by conventional EI-MS. Inbeam electron ionization (in-beam EI) 15) and desorption electron ionization (desorption EI or DEI) 16) are approaches to analyze such nonvolatile and thermally unstable molecules using a conventional EI source. The sample on Pt wire or Re filament attached to the sample probe is placed close to the electron beam to cause ionization immediately after vaporization. As advanced EI techniques, application of in-beam EI to VR is shown below. Unfortunately, effective ionization by in-beam EI, firstly applied to un-fractionated Arabian heavy vacuum residue (AH-VR), was unsuccessful 18), presumably because the boiling point of the VR sample (above 565 ) is far higher than the maximum operating probe temperature (~350 ). Considering the pressure of the ionization source (~10-8 bar, 1 bar=10 5 Pa), some of the components in AH-VR can be vaporized and detected since the component with boiling point of 565 can be vaporized below 350 at ~10-8 bar based on the temperature-pressure nomograph. Increase of the vaporization temperature of components by complexation with co-existing compounds may be one possible reason. Van der Waals interactions between highlydeveloped aromatic hydrocarbons and hydrogen bonding or other types of polar interaction further increase the vaporization temperatures of individual components. In fact, recent heavy oil (asphaltene and bitumen) measurements by mass spectrometry have revealed a tendency to aggregation of these heavy oils 19),20). In-beam EI FT-ICR MS has been successfully applied to the saturate fraction of AH-VR, with reduced molecular interaction, as described below Effect of Ionization Energy and Probe Temperature on In-beam EI FT-ICR Mass Spectra Electron beams at 70 ev are conventionally adopted to irradiate the vaporized sample for EI since this energy can ionize most organic molecules with the maximum ionization efficiency 21). High electron energy facilitates the ionization of a range of components and increases the signal intensity of the acquired mass spectra. However, high electron energy accelerates the fragmentation of ionized molecules, resulting in complicated spectra, especially for petroleum samples. GC/MS with EI is applicable to the characterization of light distillate but is not suitable for heavy distillate because of the difficulty of sample vaporization in the injection region of the GC. Irradiation with lower electron energy is the first approach to suppress molecular fragmentation during in-beam EI FT-ICR MS measurement 18). The mass spectra of the saturate fraction of AH-VR (AH-VR-Sa) were measured at various ionization energies with fixed probe temperature of 200. No peaks were detected with the ionization energy below 30 ev. However, almost 600 distinguishable peaks originating from the components of AH-VR-Sa were observed up to around m/z 400 with electron energy of ev as shown in Fig. 3. These spectra had a bimodal distribution with mode m/z values at around 150 and 300. The peak intensities increased over the whole detected range with increased ionization energy. Relative peak intensities below m/z 200 increased with higher ionization energy from 30 to 50 ev. On the other hand, relative peak intensities over m/z 250 decreased with higher ionization energy. The tendency observed for low m/z may reflect the enhanced

4 162 Fig. 3 In-beam EI FT-ICR Mass Spectra of AH-VR-Sa Acquired at Various Ionization Energies; (a) 30, (b) 40, (c) 50, and (d) 70 ev Peak intensity of VR was doubled to clarify the spectral distribution change. Fig. 5 In-beam EI FT-ICR Mass Spectra of AR, VGO, and VR Fig. 4 Segmented Mass Spectrometric Profiles of In-beam EI FT ICR Mass Spectra of AH-VR-Sa Acquired at Various Probe Temperatures degree of fragmentation at higher ionization energy. The effects of probe temperature on the mass spectra of AH-VR-Sa were examined to identify suitable conditions 18). The segmented mass spectra obtained using various probe temperatures from 150 to 350 at the fixed ionization energy of 30 ev are shown in Fig. 4. Increased probe temperature resulted in decreased relative intensity at less than m/z 400, and the detectable peak range extended to higher m/z values up to m/z 700 at 350. Characterization of the heavy ends, such as vacuum residue or asphaltene, requires high probe temperatures to vaporize high molecular weight species, but the probe temperature should also chosen to prevent thermal decomposition of the small molecules which are also contained in heavy oil Components Detected by In-beam EI FT-ICR Mass Spectra Figure 5 shows the in-beam EI FT-ICR mass spectra of the saturate fractions of AR, VGO and VR (heptane soluble fraction) of Kuwait heavy oil acquired at ionization energy of 16 ev and probe temperature of 300. The mass spectra of AR and VGO contained peaks up to m/z 500. The mass range of VGO was similar to that found using conventional EI 14). The upper mass limit of VR extended over m / z 700 in Fig. 5. Therefore, in-beam EI has the potential to characterize much heavier petroleum distillate. Table 1 shows the estimated molecular formulas based on the peaks detected in the in-beam EI FT-ICR mass spectra of AR, VGO, and VR. The peaks with odd masses were fragment ions derived from larger species, since EI often yields [M] + ions of odd-electron species in the positive ion mode. The molecular formulas were determined based on the accurate mass values for all the peaks observed in the whole mass range shown in Fig. 5. The detected compounds (classes) were hydrocarbons and one sulfur-containing compound. No fragment peaks of sulfur containing compounds were detected, so the sulfur atom may be located within an aromatic ring but not in a side chain 22). Figure 6 summarizes the compound (type) distributions in each compound class. Although only saturate fractions of AR, VGO and VR were measured, the obtained carbon number distributions reflect the preparation conditions of the samples. Carbon number of the hydrocarbons ranged to 35 in VGO and to 51 in VR mass spectra. Compounds with up to five aromatic rings (Z-value=-30) were detected in VGO and VR. Benzothiophenes (Z-value=-10) were observed in both VGO and VR, and dibenzothiophenes (Z-value= -16) were observed only in VGO. Dibenzothiophene derivatives were not detected in VR, in accord with our previous AH-VR measurements by in-beam EI 18). Since VGO and VR are vacuum distillation fractions of AR, the distribution of the compounds derived from AR should be equivalent to superpositioning of both VGO and VR. The distribution of VGO shows lower major Z-value (Z=-16) than AR (Z=-10) in Fig. 6. The mechanism of this observation remains unclear, but the ionization energy of the compounds may be involved,

5 163 Molecular formula Table 1 Estimated Molecular Formulas for the Peaks Observed in the Saturate Fractions of AR, VGO, and VR Formula mass [u] Z a) Meas. mass [u] (difference [mu]) AR VGO VR [C 22 H 34 S] (0.8) (1.1) [C 24 H 42 ] (1.3) (1.0) (1.6) [C 25 H 31 ] (1.7) (0.0) [C CH 42 ] (1.9) [C 24 H 43 ] (-0.2) (1.1) [C 25 H 32 ] (1.1) (0.4) [C 24 H 44 ] (0.1) (0.0) [C CH 32 ] (2.0) [C 24 H 45 ] (0.1) (0.2) (0.9) [C 23 H 26 S] (1.3) [C 26 H 34 ] (1.5) (1.1) [C 24 H 46 ] (0.0) (0.1) (0.4) a) Hydrogen deficiency index: [C nh 2n+ZS s] +. Fig. 6 Carbon Number and Z-value Distribution of Hydrocarbons and S-containing Compounds Detected in the In-beam EI FT-ICR Mass Spectra of AR, VGO, and VR as the ionization energy of dibenzothiophenes is lower than that of benzothiophenes. The concentration of dibenzothiophenes exceeded the detection limit of inbeam EI FT-ICR MS in VGO by chromatographic separation, although the amount of dibenzothiophenes is lower than that of benzothiophenes. 4. Application of ESI FT-ICR MS ESI has been preferentially applied for biological materials with large molecular weights since ESI is effective to ionize molecules with polar functional groups, which tend to protonate, without causing fragmentation. Petroleum largely consists of nonpolar hydrocarbons, so ESI has not been considered suitable. The high sensitivity of ESI has a significant advantage for the analysis of the minor polar compounds with heteroatoms present in petroleum, which cause significant deactivation of catalysts during upgrading 23). We have succeeded in applying ESI FT-ICR MS to the characterization of Arabian mix vacuum residue (AM VR) 24). Since then, over 20 further reports have appeared 11),25)~46). Currently, ESI-MS is the most powerful analytical tool for the characterization of the polar components in petroleum.

6 Characterization of Vacuum Residues from Different Geological Sources The structural characteristics of the components of five vacuum residues from different geological sources (Taching (TC-VR), Sumatra light (SL-VR), Iranian heavy (IH-VR), AM-VR, and Murban vacuum residues (MB-VR)) were investigated by ESI FT-ICR MS without chromatographic pre-separation (Fig. 7) 33). The mass spectra showed differences in both average molecular weight and detection range depending on the origin (Table 2). Figure 8 shows the expanded spectra of VRs in the ranges of 468<m/z<474 and 624<m/z< 630. Three series of patterns in peak intensities are usually observed for petroleum spectra: the isotopic peak pattern ( 12 C _13 C: u), every additional ring or double bond in the loss of two hydrogen atoms (2H: u), and every additional methylene in the side chains (CH2: u). The isotopic peak and the ring or double bond difference patterns were observed in Fig. 8. The peak intensity pattern depended on the geological source. These peak patterns and accurate masses were used to estimate the molecular formulas as mentioned above (Table 3). All observed peaks in Fig. 8 were assigned to N-containing compounds or NS-containing compounds. Homologue analysis for all estimated molecular formulas showed both analogies and peculiarities in the components of the five vacuum residues. Every observed compound was sorted by hydrogen deficiency index (Z-value: [CnH2n+ZNmSs +H] + ) and carbon number (only TC-VR are shown in Fig. 9). The center of distribution for the Z-values depended on the origin and the maximum value decreased as follows: TC-VR (-17)>SL-VR (-19)>IH-VR (-21) AM-VR (-21)>MB-VR (-25). TC-VR Fig. 7 Positive ESI FT-ICR Mass Spectra of Five Vacuum Residues from Different Geological Sources; (a) TC-VR, (b) SL-VR, (c) IH-VR, (d) AM-VR, and (e) MB-VR Table 2 Detected Peak Range, Number Average Molecular Weight and Observed Carbon Numbers Obtained from the ESI Mass Spectrum of Each Vacuum Residue Sample Detected range Number average MW Range of detected carbon number TC-VR 340<m/z< SL-VR 320<m/z< MB-VR 320<m/z< IH-VR 300<m/z< AM-VR 300<m/z< The spectral patterns are consistent in peak position but have different peak intensity for (a) TC-VR, (b) SL-VR, (c) IH-VR, (d) AM-VR, and (e) MB-VR. Fig. 8 Expanded View of the Full Mass Range Mass Spectra of Fig. 7 Showing Peak Patterns due to 13 C and 2H Meas. mass [u] Table 3 Estimated Molecular Formulas for the Peaks Observed in Fig. 8-(a) Molecular formula Formula mass [u] (difference [mu]) Z a) % of peak intensity against monoisotopic peak [C 34 H 45 N+H] (1.2) [C CH 45 N+H] (1.4) [C 34 H 47 N+H] (0.5) [C CH 47 N+H] (1.2) [C 34 H 49 N+H] (1.5) [C CH 49 N+H] (0.2) [C 45 H 69 N+H] (1.4) [C CH 69 N+H] (1.0) [C 45 H 71 N+H] (0.2) [C CH 71 N+H] (1.0) [C 45 H 73 N+H] (1.0) [C CH 73 N+H] (1.0) a) Hydrogen deficiency index: [C nh 2n+ZN+H] +.

7 165 contained low absolute Z-values compared to the other VRs from the Middle East. The results obtained by ESI FT-ICR MS agreed well with the reported findings of highly condensed aromatic compounds in Middle East VR compared to Chinese VR 47) Characterization of Feed and Hydroprocessed Oil Molecular formulas of the components in feed and catalytically processed deasphalted oils were characterized by ESI FT-ICR MS 45). The processed oil samples were prepared over a zeolite catalyst at three reaction temperatures (370, 380, and 390 ) ( Fig. 10). Molecular formulas for the detected peaks were calculated using peak pattern and accurate mass, as well as vacuum residues from different geological sources (Table 4). N-containing compounds were detected as the predominant species together with minor amounts of NS-containing compounds in every sample. The compound types of the detected species in processed deasphalted oil decreased as the reaction temperature increased. The type distribution was investigated for N-containing compounds. The Z-value distribution of the peaks assigned to [C56H112-ZN+H] + was convergent in its compounds with Z=-25 with increasing reaction temperature (Fig. 11). Probable structures with Z=-25 are shown in Fig. 12. Although structural isomers cannot be distinguished by mass spectrometry alone, aromatic ring size calculated from Z-value and side chain length can provide a reference index of catalyst refractory components. Therefore, ESI FT-ICR analyses may allow evaluation of chemical Fig. 9 Distribution Map of Carbon Number and Z-value for [C nh 2n+ZN+H] + Observed in the TC-VR Mass Spectrum Fig. 10 ESI FT-ICR Mass Spectra of Feed and Processed Oils; (a) feed oil, (b) processed at 370, (c) processed at 380, (d) processed at 390 Table 4 Estimated Molecular Formulas for the Peaks Detected in Feed and Processed Oil Mass Spectra Feed Processed oil-370 Processed oil-380 Processed oil-390 Meas. mass [u] Meas. mass [u] Meas. mass [u] Meas. mass [u] (difference [u]) (difference [u]) (difference [u]) (difference [u]) Molecular formula Formula mass [u] [C 56 H 69 N+H] (-0.003) [C 55 H 81 N+H] (-0.006) [C 54 H 93 N+H] (-0.007) [C 56 H 71 N+H] (-0.001) [C 55 H 83 N+H] (-0.004) (0.011) (0.010) [C 56 H 73 N+H] (0.000) (-0.005) [C 55 H 85 N+H] (0.005) (0.001) (-0.002) (0.001) [C 56 H 75 N+H] (0.010) [C 55 H 87 N+H] (0.009) [C 56 H 77 N+H] (0.006) (0.007) [C 55 H 89 N+H] (0.004) (0.005) (-0.003) a) Hydrogen deficiency index: [C nh 2n+ZN mo os s+h] +. Z a)

8 166 Insets show the expanded view around m/z 585. Fig. 11 Z-value Distributions for Peaks Assigned to [C 56 H 112-ZN+H] + ; species observed in the ESI FT-ICR mass spectra of feed and processed deasphalted oil Fig. 12 Assumed Chemical Structures with Estimated Molecular Formulas of Z=-25 Observed in the ESI FT-ICR Mass Spectra in Fig. 10 reactions occurring during upgrading. As stated previously in this section, ESI is extremely sensitive to polar components in petroleum. The feed oil contains over 2000 ppm nitrogen, whereas the deasphalted oil processed at 390 contains only 110 ppm nitrogen. Characterization of petroleum distillate by ESI FT-ICR MS has the advantages of obtaining both the molecular formula of each polar component and detecting trace amounts Detection of Polyaromatic Hydrocarbons by ESI FT-ICR MS As explained above, most polar constituents in petroleum materials can be characterized by ESI, and hydrocarbons and sulfur-containing compounds can be characterized by EI FT-ICR MS. However, completely fragment-free mass spectra are still difficult to acquire for hydrocarbons and sulfur-containing compounds by EI even at low ionization energy 14),18). Application of ESI, which is known for soft ionization, to nonpolar compounds has been studied by complexation with cations or electron subtraction from the molecular ions. Transition metal ions used for complexation with polyaromatic hydrocarbons have several isotopes, such Fig. 13 ESI FT-ICR Mass Spectra of AM-VR in Methanol/ chloroform (a) and Methanol/chloroform/TFA (b) as 107 Ag and 109 Ag. Isotopes reflected peak intensity pattern observed from the aromatic fraction of vacuum residues but isotopic peaks complicate the spectra for elemental analysis 48). The viability of ESI MS without transition metal adduction for the analysis of polycyclic aromatic hydrocarbons was investigated 49). Aromatic hydrocarbons were ionized as radical cations in the ESI solvent (methylene chloride) containing trifluoroacetic acid (TFA), 2,3-dichloro-5,6-dicyano-pbenzoquinone (DDQ), or antimony pentafluoride 50). By modifying this method, AM-VR were measured by ESI with addition of TFA (Fig. 13-(b)). Figure 13-(a) shows the ESI FT-ICR mass spectrum of AM-VR using methanol/chloroform for comparison. Both mass spectra show single-mode distribution but the mode value of the distribution in methanol/chloroform/tfa has shifted toward higher m/z of 800 compared to that in methanol/chloroform. The detected species in Fig. 13-(a) were polar compounds as stated above. Addition of TFA made possible the detection of new species which cannot be detected by using methanol/ chloroform as a solvent. Molecular formulas for m/z= , , and were determined in a similar way for the peaks with even masses (Table 5). The peaks with odd masses were assigned to protonated or sodium-ion attached hydrocarbons without heteroatoms. The observed spectral distribution shift also suggested that the detected species were hydrocarbons, since the hydrocarbon fraction showed higher molecular weight than the heteroatom fraction with the same Atmospheric Equivalent Boiling Point (AEBP) 5). The results of the peak analysis of all odd masses observed in the range of 570<m/z<670 in Fig. 13-(b) are summarized in Fig. 14. Hydrocarbons with carbon numbers from 41 to 49 were detected, and the Z values ranged from -54 to -8, which corresponded to 1-10 aromatic rings. Several maxima with different Z values were observed for each carbon number as shown in Fig. 14; i.e., the distribution of Z value of hydrocarbons was broader. The profile also suggests that compounds with a wide variety of aromatic structures were present. The possibility of hydrocarbon detection by

9 167 Table 5 Estimated Molecular Formulas and Probable Structures for Observed Peaks with m/z , , and in Fig. 13-(b) Formula mass [u] Meas. mass [u] Molecular formula Z a) Probable structure (difference [mu]) C 44 H (-2.8) -32 +H + C 22 H C 43 H 48 Na (-1.5) -38 +Na + C 15 H C 49 H (-2.4) -38 +H + C 21 H 43 a) Hydrogen deficiency index: [C nh 2n+ZN ms so o+h (or +Na)] +. difficult to acquire because of the difference of ionization efficiency in each compounds. Simultaneous detection of both hydrocarbons and polar components is desirable, and potential ionization techniques are discussed below. 5. Application of Other Ionization Techniques Molecules with the same carbon number, determined by the molecular formulas, are linked with a dashed line; C41 ( ), C42 ( ), C43 ( ), C44 (+), C45 ( ), C46 ( ), C47 ( ), C48 ( ), and C49 ( ). Fig. 14 Relationship of Peak Intensity to Z-value of [C nh 2n+Z+Na] + Detected in Fig. 13-(b) ESI was demonstrated by selecting the appropriate solvent composition (methanol/chloroform/tfa). Detection of hydrocarbons by selecting the solvent composition illustrates the possibility of complete characterization of petroleum distillate by ESI, but spectra which reflect the amounts of the constituents are still Field ionization (FI) and field desorption ionization (FD) have been used for the characterization of crude oil and petroleum distillates, since hydrocarbons and even saturated hydrocarbons can be ionized with no or little fragmentation 51),52). FD ionization coupled with 9.4T FT-ICR MS was applied to VGO, FCC bottoms and coker VGO 53). Although FD is known to undergo soft ionization, substantial fragmentation was observed from paraffin molecules during the external accumulation event. Therefore, focus on the aromatic fraction revealed that FCC bottoms contained larger aromatic rings than VGO and shorter aliphatic chain length. Liquid secondary ionization (LSI) is another option to detect both hydrocarbons and polar components. LSI requires simple sample preparation procedures compared to FD. The sample is just mixed up with matrix compounds (3-nitrobenzylalcohol) and loaded on the probe tip. Ionization capacity of LSI for the constituents of vacuum residue was examined using model compounds; carbazole, acridine, pyrene, and coronene. Similar to the ESI model experiment, the peaks were detected as molecular ions, except for acridine which was detected as protonated, and all peaks were detected

10 168 without fragmentation. The peak intensity of the model compounds were observed in equal intensity in the LSI mass spectrum whether the model compounds contained nitrogen or not. We cannot conclude that all the components responded equally, but clearly LSI has considerable potential to reflect the individual amounts of the components. The FT-ICR mass spectrum of AM VR ionized by LSI is shown in Fig. 15. The mass scale expanded segment of the AM-VR LSI mass spectrum is shown in the Fig. 15 inset. Molecular formulas for the peaks in the expanded segment were calculated from the m/z values and shown in Table 6. Both hydrocarbons and heteroatom-containing compounds were detected simultaneously. The compound classes detected in the AM-VR LSI FT-ICR mass spectrum are summarized in Fig. 16. Hydrocarbons and S-containing compounds were major constituents in AM-VR. Extraction of the sulfur content from mass spectra and comparison of those values with elemental analysis indicated that although the calculated value did not reflect the ionization efficiency of each compound, the two data sets are in reasonable agreement 53). The sulfur content (as weight%) was calculated from the LSI FT ICR mass spectrum. Sulfur content from the mass spectrum (5.0%) was comparable to the findings of the elemental analysis (5.2%) as well as the FD results above. Therefore, LSI FT-ICR MS also has considerable potential for the quantitative analysis of petroleum components. 6. Kendrick Mass for Data Analysis Assignment of the thousands of peaks detected in petroleum FT-ICR mass spectra is extremely laborious and time consuming. To facilitate the characterization of peaks in a very complex spectrum, one useful method is to search for analogous peak groups already identified. Kendrick mass is frequently adopted for analysis of petroleum-related samples 54),55). Components in petroleum contain homologous series; that is compounds with the same constituents of heteroatoms and number of rings (plus double bonds). Kendrick mass is a scale for sorting thousands of acquired m/z values according to these homologues. The Kendrick mass scale takes the mass of CH2 as with no decimal fraction. In the IUPAC mass scale, CH2 corresponds to Kendrick Mass=IUPAC mass (14/ ) When the IUPAC mass is converted to Kendrick mass, these homologous series show identical values of the decimal fraction. Examples of N-containing compounds are shown in Table 7, where all the com- Inset shows mass scale expansion 263<m/z<266. Fig. 15 LSI FT-ICR Mass Spectrum of AM-VR Fig. 16 Compound Class Distribution Detected in the LSI FT-ICR Mass Spectrum of AM-VR Table 6 Estimated Molecular Formulas for the Peaks Observed at 263<m/z<266 in Fig. 15 Meas. mass [u] Molecular formula Formula mass [u] (difference [mu]) [C 18 H 14 S+H] (0.2) [C 20 H 23 ] (0.5) [C 21 H 12 ] (-1.8) [C 19 H 21 N+H] (1.0) [C 18 H 16 S+H] (0.5) [C 20 H 25 ] (0.5) [C 21 H 14 ] (-2.2) -20 a) Hydrogen deficiency index: [C nh 2n+ZN ms s+h] +. Z a)

11 169 Table 7 Comparison of the IUPAC and Kendrick Masses of Acridines Molecular formula IUPAC mass Kendrick mass KMD a) Acridine C 13 H 9 N Methylacridine C 14 H 11 N Ethylacridine C 15 H 13 N Propylacridine C 16 H 15 N a) KMD: Kendrick mass deficiency. pounds have the same value of By using the Kendrick mass defect (KMD: the difference between nominal Kendrick mass and Kendrick mass) homologous series can be sorted by compound class (number of heteroatoms) and compound type (number of rings plus double bonds). The series of compounds in Table 7 has the same KMD (126.5) and share the same compound class (N) and type (number of rings plus double bonds=10). Such KMD value (126.5) is specific to these sequence of compounds. The conversion of m/z by KMD processes can be automatically conducted using spreadsheet software, such as Microsoft Excel and macro commands. 7. Conclusions The advantages of FT-ICR MS, and strengths and limitations of various ionization techniques for characterization of components in petroleum samples, were reviewed by application to various petroleum distillates and processed oils. The high resolution of FT-ICR MS provides rapid compositional assessments of complex mixtures since the molecular formulas of components can be calculated simply from accurate mass values. In-beam EI and low voltage EI can characterize hydrocarbons and S-containing compounds without chromatographic separation. These species are major components in petroleum distillates. Compounds with over m/z 500 can also be analyzed by in-beam EI with careful selection of the experimental conditions. ESI can characterize the polar components which are present in trace amounts in petroleum samples and reveal the various compound classes involved even in processed oils. FD and LSI can characterize both hydrocarbons and polar constituents. Various compounds contained in petroleum samples can be analyzed by FT ICR MS coupled with these ionization techniques. Evolution of ionization or detection methods are expected to overcome the above limitations of mass spectrometry for the characterization of petroleum samples by application to FT-ICR MS. The next step for the characterization of petroleum is quantitative analysis and characterization of isomers. FD and LSI can provide semi-quantitative analysis of S-containing compounds. Hyphenated techniques, such as liquid chromatography, and increasing magnetic field strength may overcome this limitation. FT ICR MS can be used in tandem mass spectrometry for isomer analysis, but the amount of ions with certain m/z in the ICR cell is not sufficient to detect the product ion spectrum. Isolation by quadrupole before MS/MS in the ICR cell is one of the potential solutions for isomer analysis 56). MS/MS measurement is not enough for complete characterization of the isomers since about 50 fragment peaks are detected from a single precursor peak. Combination with other characterization techniques including computer simulation may provide more detailed compositional information of petroleum samples. References 1) Pierce, K. M., Wood, L.F., Wright, B. W., Synovec, R. E., Anal. Chem., 77, 7735 (2005). 2) Del Rio, J. C., Philip, R. P., Allen, J., Org. Geochem., 18, 541 (1992). 3) Hsu, C. S., McLean, M. A., Qian, K., Aczel, T., Blum, S. C., Olmstead, W. N., Kaplan, L. H., Robbins, W. K., Schulz, W. W., Energy & Fuels, 5, 395 (1991). 4) Boduszynski, M. M., Energy & Fuels, 1, 2 (1987). 5) Boduszynski, M. M., Energy & Fuels, 2, 597 (1988). 6) Hsu, C. S., Qian, K., Energy & Fuels, 7, 268 (1993). 7) Hsu, C. S., Dechert, G. J., Robbins, W. K., Fukuda, E. K., Energy & Fuels, 14, 217 (2000). 8) Van Berkel, G. J., Quinones, M. A., Quirke, J. M. E., Energy & Fuels, 7, 411 (1993). 9) Zhan, D. L., Fenn, J. B., Int. J. Mass Spectrom., 194, 197 (2000). 10) Gross, J. H., Mass Spectrometry A Text book, Springer, (2004), p ) Guan, S., Marshall, A. G., Scheppele, S. E., Anal. Chem., 68, 46 (1996). 12) Hsu, C. S., Liang, Z., Campana, J. E., Anal. Chem., 66, 850 (1994). 13) Rodgers, R. P., White, F. M., Hendrickson, C. L., Marshall, A. G., Anal. Chem., 70, 4743 (1998). 14) Fu, J., Kim, S., Rodgers, R. P., Hendrickson, C. L., Marshall, A. G., Qian, K., Energy & Fuels, 20, 661 (2006). 15) Tsujimoto, K., Nomura, H., Ohashi, M., Shitsuryoubunnseki, 33, 255 (1985). 16) Peltier, J. M., MacLean, D. B., Szarek, W. A., Rapid Commun. Mass Spectrom., 5, 446 (1991). 17) Daves, G. D. Jr., Acc. Chem. Res., 12, 359 (1979). 18) Miyabayashi, K., Naito, Y., Tsujimoto, K., Miyake, M., Int. J. Mass Spectrom., 221, 93 (2002). 19) Mullins, O. C., Sheu, E. Y., Hammami, A., Marshall, A. G., Asphaltenes, Heavy Oils, and Petroleomics, Springer, New York (2007). 20) Pomerantz, A. E., Hammond, M. R., Morrow, A. L., Mullins, O. C., Zare, R. N., J. Am. Chem. Soc., 130, 7216 (2008).

12 170 21) Mark, T. D., Int. J. Mass Spectrom. Ion. Phys., 45, 125 (1982). 22) Gatesa, B. C., Topsoeb, H., Polyhedron, 16, 3213 (1997). 23) Botchwey, C., Dalai, A. K., Adjaye, J., Energy & Fuels, 17, 1372 (2003). 24) Miyabayashi, K., Suzuki, K., Teranishi, T., Naito, Y., Tsujimoto, K., Miyake, M., Chem. Lett., 172 (2000). 25) Miyabayashi, K., Naito, Y., Miyake, M., Tsujimoto, K., Eur. Mass Spectrom., 6, 251 (2000). 26) Qian, K., Rodgers, R. P., Hendrickson, C. L., Emmett, M. R., Marshall, A. G., Energy & Fuels, 15, 492 (2001). 27) Qian, K., Robbins, W. K., Hughey, C. A., Cooper, H. J., Rodgers, R. P., Marshall, A. G., Energy & Fuels, 15, 1505 (2001). 28) Hughey, C. A., Hendrickson, C. L., Rodgers, R. P., Marshall, A. G., Energy & Fuels, 15, 1186 (2001). 29) Hughey, C. A., Rodgers, R. P., Marshall, A. G., Qian, K., Winston, K., Org. Geochem., 33, 743 (2002). 30) Wu, Z., Jernström, S., Hughey, C. A., Rodgers, R. P., Marshall, A. G., Energy & Fuels, 17, 946 (2003). 31) Barrow, M. P., McDonnell, L. A., Feng, X., Walker, J., Derrick, P. J., Anal. Chem., 75, 860 (2003). 32) Miyabayashi, K., Naito, Y., Tsujimoto, K., Miyake, M., Int. J. Mass Spectrom., 235, 49 (2004). 33) Miyabayashi, K., Naito, Y., Tsujimoto, K., Miyake, M., J. Petrol. Inst., 47, (5), 326 (2004). 34) Miyabayashi, K., Naito, Y., Tsujimoto, K., Miyake, M., ACS Symposium Series. 895; Heavy Hydrocarbon Resources: Characterization, Upgrading, and Utilization, eds. by Nomura, M., Rahimi, P. M., Koseoglu, O. R., Amer. Chem. Soc., Washington DC (2004), p ) Barrow, M. P., Headley, J. V., Peru, K. M., Derrick, P. J., J. Chromatogr., A, 1058, 51 (2004). 36) Hughey, C. A., Rodgers, R. P., Marshall, A. G., Walters, C. C., Qian, K., Mankiewicz, P., Org. Geochem., 35, 863 (2004). 37) Wu, Z., Rodgers, R. P., Marshall, A. G., Strohm, J. J., Song, C., Energy & Fuels, 19, 1072 (2005). 38) Stanford, L. A., Kim, S., Rodgers, R. P., Marshall, A. G., Energy & Fuels, 20, 1664 (2006). 39) Fu, J., Klein, G. C., Smith, D. F., Kim, S., Rodgers, R. P., Hendrickson, C. L., Marshall, A. G., Energy & Fuels, 20, 1235 (2006). 40) Klein, G. C., Angström, A., Rodgers, R. P., Marshall, A. G., Energy & Fuels, 20, 668 (2006). 41) Klein, G. C., Rodgers, R. P., Marshall, A. G., Fuel, 85, 2071 (2006). 42) Klein, G. C., Kim, S., Rodgers, R. P., Marshall, A. G., Yen, A., Asomaning, S., Energy & Fuels, 20, 1965 (2006). 43) Stanford, L. A., Kim, S., Klein, G. C., Smith, D. F., Rodgers, R. P., Marshall, A. G., Environ. Sci. Technol., 41, 2696 (2007). 44) Stanford, L. A., Rodgers, R. P., Marshall, A. G., Czarnecki, J., Wu, X. A., Taylor, S., Energy & Fuels, 21, 973 (2007). 45) Miyabayashi, K., Naito, Y., Yamada, M., Miyake, M., Ushio, M., Fuchigami, J., Kuroda, R., Ida, T., Hayashida, K., Ishihara, H., Fuel Process. Technol., 89, 397 (2008). 46) Schaub, T. M., Hendrickson, C. L., Horning, S., Quinn, J. P., Senko, M. W., Marshall, A. G., Anal. Chem., 80, 3985 (2008). 47) Sonoda, N., Kameoka, H., Yukikougyoukagaku, 2nd ed., Kagaku-Dojin, Kyoto (1994), p ) Roussis, S. G., Proulx, R., Anal. Chem., 74, 1408 (2002). 49) Van Berkel, G. J., Asano, K. G., Anal. Chem., 66, 2096 (1994). 50) Van Berkel, G. J., McLuckey, S. A., Glish, G. L., Anal. Chem., 64, 1586 (1992). 51) Mead, L., Anal. Chem., 29, 13 (1968). 52) Scheppele, S. E., Hsu, C. S., Maririott, T. D., Benson, P. A., Detwiler, K. N., Perreira, N. B., Int. J. Mass Spectrom. Ion Phys., 28, 335 (1978). 53) Schaub, T. M., Rodgers, R. P., Marshall, A. G., Qian, K., Green, L. A., Olmstead, W. M., Energy & Fuels, 19, 1566 (2005). 54) Kendrick, E., Anal. Chem., 35, 2146 (1963). 55) Hughey, C. A., Hendrickson, C. L., Rodgers, R. P., Marshall, A. G., Anal. Chem., 73, 4676 (2001). 56) Schaub, T. M., Jennings, D. W., Kim, S., Rodgers, R. P., Marshall, A. G., Energy & Fuels, 21, 185 (2007).

13 171 要 旨 種々のイオン化法を用いた FT-ICR MS による重質油のキャラクタリゼーション 宮林恵子, 内藤康秀, 三宅幹夫 北陸先端科学技術大学院大学マテリアルサイエンス研究科, 石川県能美市旭台 1-1 超高分解能での測定が可能であるフーリエ変換イオンサイクロトロン共鳴質量分析法 (FT-ICR MS) を用いた重質油成分分析法について概説した FT-ICR MS では得られる質量スペクトルの質量確度の高さゆえ, 精密質量値から簡便に分子式を算定することが可能である 本稿では, 常圧残油 (AR), 減圧軽油 (VGO), 減圧残油 (VR) などの重質油および触媒処理油について,FT-ICR MS と様々なイオン化法との組合せから得られる成分を解析し, それらの特徴について示した AR,VGO,VR を電子イオン化 (EI) で測定した結果, 試料中の主成分である炭化水素や硫黄化合物が観測され, 炭化水素化合物では蒸留分に応じた炭素数や芳香環数の成分分布を得た 温和なイオン化法であるエレクトロスプレーイオン化 (ESI) を用いた場合, 石油中の微量成分である極性成分が選択的に検出され, 採取地の異なる 5 種の減圧残油の分析では, 採取地に依存した減圧残 油窒素化合物成分の組成分布を観測できることを明らかとした また, 処理温度の異なる触媒処理油の ESI FT-ICR MS 測定から処理温度の向上に従い, 特定の不飽和度 (Z=-25) の成分 ([C nh 2n-25 N+H] + ) が選択的に残留することを明らかにし, 本手法が触媒耐性成分の解明に有用であることを示した さらに, フラグメントを排した炭化水素化合物の検出法として, ESI における溶液の酸性度を制御することで, 炭化水素成分が検出できることを示した 液体二次イオン化法では, 炭化水素 硫黄化合物 窒素化合物が観測され, 質量スペクトルから得られる硫黄の成分量は元素分析値に近い値を示し, 定量性の可能性を検討した FT-ICR MS を用いることで, 従来困難であった個々の重質油成分分析の可能性を示すとともに, イオン化法の特長を生かすことで目的とする成分の選択的な分析が可能であることを示した