Application Note # FTMS-46 solarix XR: Analysis of Complex Mixtures

Application Note # FTMS-46 solarix XR: Analysis of Complex Mixtures Introduction Natural organic matter (NOM) as well as crude oil and crude oil fractions are very complex mixtures of organic compounds consisting of various elemental compositions and chemical structures. These mixtures can vary extremely depending on their origin and complexity. Natural organic matter consists mainly of oxygen containing compounds. However, also nitrogen and sulfur are presented in low amounts in NOM. Therefore, high dynamic range and mass accuracy is needed to detect and identify these compounds. Beside the roughly 9% of hydrocarbon compounds in crude oil, the remaining polar mainly polar compounds are of major interest which are mainly in the resin and asphaltene fractions. These compounds contain different amount of sulfur, nitrogen and oxygen which results in an extremely complex mixture difficult to analyze. Due to the complexity of oil, chromatography can be used to separate compound classes. However, separation of compounds by liquid chromatography is only of limited use. Therefore, mass spectrometers providing extremely high resolving power and mass accuracy like Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers are needed to analysis these samples [1-2]. Authors Dr. Matthias Witt Bruker Daltonik GmbH, Bremen, Germany Keywords Instrumentation and Software Complex Mixture solarix XR Petroleomics DataAnalysis 4. Crude Oil ESI Source NOM APPI II Source FTMS Composer

Still, for FTMS the resolving power is limited by a) analyzer pressure, b) peak coalencense effects and c) non-perfect trapping potential resulting in a de-phasing of the ion cyclotron motion. The solarix XR has been developed to be able to study these kind of mixtures using only a 7T magnet. The non-perfect trapping has been overcome by the develop-ment of a new cell with parabolic trapping potentials, called dynamically harmonized analyzer cell (Fig. 1) [3-5]. It has been shown that extremely high resolving power of more than 2.. can be achieved with this new analyzer cell, however, these measurements were performed with a limited using quadrupole isolation. Nevertheless, very high resolving power of 8. at m/z have been achieved in magnitude mode in full broad band detection of very complex mixtures like crude oil and NOM without any quadrupole isolation using a solarix XR system. Even higher mass resolution of more than 1.2. can be achieved of complex mixtures using the absorption mode processing (AMP) [6]. NOM as well as oil samples have been used to test the performance of the new solarix XR FTMS system with the new dynamically harmonized analyzer cell. Suwannee river fulvic acid (SRFA) as a NOM standard has been measured by electrospray ionization. The mixture consists mainly of oxygen containing compounds with different number of carboxyl, carbonyl and hydroxyl functional groups. However, due to the origin of the sample sodium is present in the sample. ICR paracell Therefore, sodium adducts beside protonated species are detected resulting in more than 5 mass peaks in the spectrum. Different crude oil samples and bitumen as well as a residual fuel oil have been measured by APPI to test the performance of the new FT-ICR system concerning sample complexity. The APPI spectra in positive ion mode are extremely rich in content of peaks due to the formation of radical cations and protonated species. Hence, these spectra represent one of the most complex ones of small molecule mixtures. The spectra have been mainly analyzed concerning achieved mass resolving power and mass accuracy. Additionally, CASI measurements of complex mixtures have been carried out to compare CASI and full broad band results. Experimental Sample preparation The NOM standard SRFA has been purchased by the International Humic Substance Society (IHSS order No. 2S11). SRFA has been measured without any further purification. 2 µg ml -1 solution of SRFA in 5% methanol/5% water was directly sprayed into the electrospray ion source using a syringe pump. One residual fuel oil purchased from TCI (TCI order number S25) as well as two crude oils and one bitumen sample kindly provided by the company SINOPEC, China, were analyzed. Solutions of the oils were prepared without any further purification. 1 mg of the oil were dissolved in 2 µl dichloromethane. These sample stock solutions were diluted 1:5 with 5% methanol, 5% toluene for atmospheric pressure photoionization (APPI) measurements. Mass analysis Mass spectra were acquired with a Bruker solarix XR Fourier transform mass spectrometer (Bruker Daltonik GmbH, Bremen, Germany) equipped with a 7T refrigerated actively shielded superconducting magnet (Bruker Biospin, Wissembourg, France) and the new dynamically harmonized analyzer cell. The samples were ionized in positive ion mode using ESI and APPI (Bruker Daltonik GmbH, Bremen, Germany). Figure 1: New dynamically harmonized analyzer cell with parabolic trapping plates. Sample solutions were continuously infused using a syringe pump. A flow rate of 12 µl h -1 and 6 µl h -1 were used for ESI and APPI, respectively. The size of the acquired data sets was 8 MW resulting in a resolving power of 8 at m/z. The detection mass range was set to m/z 15. scans were acquired for each mass spectrum. A sine apodization was performed before Fourier transformation.

Mass calibration The mass spectra were calibrated externally with arginine clusters in positive ion mode using a linear calibration. A 1 µg ml -1 solution of arginine in 5% methanol was used to generate the clusters. To improve the mass accuracy the spectra were recalibrated internally with a known homologous series. Molecular formula calculation The mass formula calculation of the SRFA spectrum was done in DataAnalysis 4. (Bruker Daltonik GmbH, Bremen, Germany) using a maximum formula of C n H h O 3 Na, electron configurations even and a mass tolerance of.5 ppm. The calculation of molecular formulae of the oil samples was done in DataAnalysis 4. using a maximum formula of C n H h N 3 O 3 S 3 and electron configurations odd and even due to the formation and detection of radical cations and protonated species. The mass tolerance was set to.5 ppm. Compound classes were calculated with the Composer software (Sierra Analytics, Modesto, CA, USA. Results and Discussion The performance of the solarix XR system has been demonstrated by measurement of different very complex samples. The mass spectrum of SRFA measured in positive ion mode using electrospray ionization is shown in Figure 2. The mass spectrum has more than 5 mass peaks. More than 27 molecular formulae containing only carbon, hydrogen, oxygen and maximum of one sodium could be calculated with a root mean square (RMS) mass error less than 5. The mass error plot is shown in Figure 3. A residual fuel oil was measured to show the performance of the solarix XR for the petroleomics applications. The mass error plot of the ESI spectrum of the residual fuel oil is shown in Figure 4. Mainly compound class N and NO have been detected resulting in low number of peaks detected by electrospray ionization. Roughly molecular formulae have been calculated with a RMS error of 65. An even low RMS error of only 13 could be achieved of the compound class N1 considering only mass peaks above with a relative abundance of more than 1%. Mass error plot of ESI spectrum 35 25 2 15 5-51 - 46-41 - 36-31 - 26-21 - 16-11 - 6 Figure 3: Mass error plot of ESI spectrum of SRFA in positive ion mode. 2765 peaks were considered for the calculation ( 13 C peaks were excluded). A RMS mass error of only 49 was calculated. Mass error plot of ESI spectrum 45-1 avg. Deviation: RMS error: 49 2765 peaks considered for calculation 4 9 14 19 24 avg. Deviation: 2 RMS error: 65 2958 peaks considered for calculation 29 34 39 44 49 35 Broad band electrospray spectrum Resolving power: 8. (at m/z (at) m/z ) NOM standard NOM complex mixture standard Suwannee river fulvic acid Suwannee river fulvic acid 25 2 15 5-5 -46-42 -38-34 - -26-22 -18-14 - -6-2 2 6 14 18 22 26 34 38 42 46 5 Figure 4: Mass error plot of ESI spectrum of a residual fuel oil in positive ion mode. Nearly peaks were considered for the calculation ( 13 C peaks were excluded). A RMS mass error of only 65 was calculated. 2 5 6 m/z Figure 2: Broad band electrospray spectrum of Suwannee river fulvic acid from the IHSS measured in positive ion mode. More than 5 mass peaks could be detected.

More challenging samples are crude oils with high amount of sulfur when analyzed by APPI. These samples are extremely complex and APPI can detect sulfur containing compound with one, two or even three sulfur atoms. Additionally, radical cations as well as protonated species are formed resulting in spectra with much more peaks than detected by ESI. Two crude oil and a bitumen sample have been analyzed by APPI in positive ion mode. The APPI spectra are shown in Figure 5. Broad band APPI spectra Crude oil, low sulfur Crude oil, medium sulfur Bitumen, high sulfur 2 5 6 7 8 9 m/z The average mass is shifting to higher mass with increase of the sulfur content. However, also the complexity is increasing resulting in a higher mass error. The error plots of the three samples are shown in Figure 6. The number of unambiguously assigned molecular formulae is increasing from roughly 5 to nearly 8 with the amount of sulfur in the complex sample. The RMS mass error shows the expected trend with an increase from 12 to 139 based on the complexity of the sample. The difference of the RMS mass error of peaks with a relative abundance of more than 1% is even more significant. The error increases from 2 to 4 with higher sulfur content in crude oil and nearly doubles for the extremely complex bitumen sample. Nevertheless, a resolving power of 8. at m/z could still be achieved even of the most complex bitumen sample. The mass spectra of extremely complex mixtures can be further improved by CASI (continuous accumulation of selected ions). Ions only of a limited mass range (typically Da isolation mass window) are selected with a quadrupole. These selected ions are accumulated in the storage cell for detection. The dynamic range of the mass spectrum can be improved with this technique. Also mass errors are lowered due to the reduced number of detected peaks compared to the broad mass spectrum. The mass error plots of the broad band and CASI measurements are shown in Figure 7. Figure 5: Broad band APPI spectra of two crude oil and one bitumen sample with different amount of sulfur in positive ion mode. Mass error plots a) Low sulfur containing sample (crude oil) b) Medium sulfur containing sample (crude oil) abs. avg. Deviation: 2, RMS error: 12 abs. avg. Deviation: 22, RMS error: 13 553 considered for calculation 6518 considered for calculation 45 35 25 2 15 5-5 - 44-38 - 32-26 - 2-14 - 8-2 4 16 22 28 34 46 RMS error: 2 (peaks > 1%) 45 RMS error: 4 (peaks > 1%) 35 25 2 15 5 35 25 2 15 5-5 - 44-38 - 32-26 - 2-14 - 8-2 4 16 22 28 34 46-5 -44-38 - 32-26 - 2-14 -8-2 4 16 22 28 34 46 c) High sulfur containing sample (bitumen) abs. avg. Deviation: 51, RMS error: 139 7939 considered for calculation RMS error: 75 (peaks > 1%) Figure 6: Mass error plots of a) crude oil with low amount of sulfur, b) crude oil with medium amount of sulfur and c) bitumen with high amount of sulfur. Complexity of mass spectra increases with amount of sulfur resulting in a) detection of more mass peaks for error calculation and b) increase of mass error.

Mass error plots of bitumen sample a) Broad band, masses m/z 38-48 abs. avg. Deviation: 18, RMS error: 99 265 considered for calculation b) Broad band, masses m/z 38-48 abs. avg. Deviation: 4, RMS error: 67 386 considered for calculation 16 14 12 8 6 4 2-5 -45 - -35 - -25-2 -15 - -5 35 RMS error: 46 (peaks > 1%) RMS error: 2 (peaks > 1%) RMS RMS error: error: 426 (peaks (peaks > 1%) > 1%) 5 15 2 25 35 45 5 25 13 C peaks considered 13 C peaks considered 2 Peaks > 1% considered Peaks > 1% considered 15 5-5 -46-42 -38-34 - -26-22 -18-14 - -6-2 2 6 14 18 22 26 34 38 42 46 5 Figure 7: Mass error plots of bitumen sample with high amount of sulfur considering masses between m/z 38 and m/z 48 of a) broad band and b) CASI measurement. RMS mass error is further reduced from 99 to 67 using CASI instead of broad band detection. The mass error is further reduced from 99 to 67 considering only peaks between m/z 38 and m/z 48 using CASI instead of broad band mass detection. Only unambiguously assigned mass peaks with a relative abundance of more than 1% have been considered for the error plot calculation to compare similar peaks in the mass spectrum. Therefore, the number of peaks used for the error plots increases only by about 2% and the improvement in the dynamic range is not really visible here. The effect of improved dynamic range by CASI is shown in Figure 8. Peaks not visible in broad band have been observed by CASI marked with the red arrows. Therefore, this technique can be used to detect very low abundant species in extremely complex mixtures not detectable in broad band mode. Zoom in of CASI spectrum broad band.18555.18891.18215 CASI.18555.18893.18217.2546.229.2136.175.18.185.19.195.2.25.21 m/z Figure 8: Zoom in of a) broad band and b) CASI spectrum to show the improvement of dynamic range using CASI. Peaks marked with arrows could only be detected with the CASI technique.

Bruker Daltonics is continually improving its products and reserves the right to change specifications without notice. Bruker Daltonics 11-212, FTMS-46, #7442 Conclusion Complex mixtures like NOM and crude oil have been successfully analyzed on the molecular level with the new solarix 7T XR system. Signal transients of more than 6 seconds could be achieved resulting in a resolving power of about 8. at m/z in magnitude mode. RMS mass errors of less than 5 could be obtained for SRFA. Low RMS mass errors below 15 were observed for extremely complex mixtures like crude oil and bitumen. A resolving power of 8. could be achieved for very complex APPI spectra of these samples in broad band detection mode. Acknowledgments The author would like to thank Dr. Maowen Li from the company SINOPEC, China, for providing the crude oil and bitumen samples. Many thanks to Roland Jertz, Jochen Friedrich and Claudia Kriete from Bruker Daltonik GmbH (Bremen) for their support during sample measurements and generating mass error plots. References [1] Marshall, A. G.; Rodgers, R. P. Acc. Chem. Res. 24, 37, 59-59 [2] Purcell, J. M.; Hendrickson, C. L.; Rodgers, R. P.; Marshall, A. G. Anal. Chem. 26, 78, 596-5912 [3] Boldin, I.A., Nikolaev, E.N. Rapid Commun. Mass Spectrom. 211, 25, 122-126 [4] Nikolaev, E.N., Boldin, I.A., Jertz, R., Baykut, G. A. J. Am. Soc. Mass Spectrom. 211, 22, 1125-1133 [5] Nikolaev, E.N., Jertz, R., Grigoryev, A., Baykut, G. A. Anal. Chem. 212, 84, 2275-2283 [6] Qi, Y., Witt, M., Jertz, R. Baykut, G., Barrow, M.P., Nikolaev, E.N., O Connor, P.B. Rapid Commun. Mass Spectrom. 212, 26, 221-226 For research use only. Not for use in diagnostic procedures. Bruker Daltonik GmbH Bremen Germany Phone +49 ()421-225- Fax +49 ()421-225-13 sales@bdal.de www.bruker.com/ms Bruker Daltonics Inc. Billerica, MA USA Phone +1 (978) 663-366 Fax +1 (978) 667-5993 ms-sales@bdal.com Fremont, CA USA Phone +1 (51) 683-4 Fax +1 (51) 49-6586 ms-sales@bdal.com