Petroleum Analysis by Atmospheric Pressure Photoionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
Bibliographic record
Abstract
Petroleum and petroleum products are an integral part of today's society. Although petroleum is projected to be the dominant energy source for the next fifty years, the depletion of light sweet crude oil reserves has led to the refinement of heavier feedstocks. Heavier petroleum feedstocks contain higher weight percent sulfur-, nitrogen- and oxygen-containing species. Not only is the combustion of these species harmful to the environment, they can also poison catalytic and hydrotreatment refining equipment. The United States Environmental Protection agency has limited allowable heteroatom weight percents in petroleum products. Moreover, sulfur is the third most abundant element in petroleum and has been regulated to parts-per-million levels and further reduction slated for the year 2010. To meet the more stringent environmental regulations, refineries are facing major challenges. Mass spectrometry has proven to be a valuable tool for the molecular speciation of petroleum. Notably, electrospray ionization Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry has proven invaluable for the speciation of the polar compounds in crude oil. This analysis has added to the understanding of specific refinery problems, e.g., solid deposition and flocculation. However, hydrocarbons and non-polar sulfur species are not accessible by ESI mass spectrometry. Atmospheric Pressure PhotoIonization (APPI) can produce ions from non-polar (and polar) species. Chapter 1 is a brief discussion of basic ICR principles, APPI pathways, instrumentation and data analysis. In Chapter 2, I describe an APPI source coupled to the in house built 9.4 Tesla Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer at the National High Magnetic Field Laboratory (NHMFL) in Tallahassee, Florida. This chapter highlights the complexity of crude oil analysis with an APPI source. The possibility of forming two ion types (protonated compounds and radical molecular ions) from one compound complicates an already complex spectrum. Model compound spectra demonstrate the necessity of ultra-high resolution mass spectrometry to resolve common mass doublets (3.4 mDa, the mass difference between C3 vs. SH4; 4.5 mDa, the mass difference between 12CH and 13C) found in petroleum spectra. Also, this report establishes the highest number of resolved (and assigned elemental formulas) spectral peaks (>12,000 peaks in a single mass spectrum and up to 63 peaks of the same nominal mass) in one mass spectrum.12,000 peaks in a single mass spectrum and up to 63 peaks of the same nominal mass) in one mass spectrum. Although APPI is considered to be a soft ionization technique, the analyte is nebulized and heated before ion formation. On the other hand, ESI is a well established soft ionization process. Therefore, in Chapter 3, I compare ESI and APPI data from the same crude oil and also pyridinic and pyrrolic nitrogen model compounds. The chapter defines instrument parameters which can cause fragmentation (loss of H2) and parameters which do not. ESI and APPI crude oil spectra yield the same elemental species, providing evidence that APPI can produce an ion population without fragmentation. A dopant (proton donor) is advantageous for APPI mass spectrometry because proton transfer reactions are enhanced. For simple mixture analysis, the proton donor is predominantly the dopant. However, for complex mixture analysis (crude oil), the solution matrix can contain species which could also participate in proton transfer reactions. In Chapter 4, I investigate the proton transfer reaction for a Canadian bitumen petroleum in deuterated toluene (C7D8). Nitrogen class compounds are also analyzed in deuterated toluene. The dopant percent contribution to the even-electron ions (protonated and deuterated compounds) of the petroleum is ~5 %. The nitrogen model compounds exhibited a similar trend. Petrochemical analysis commonly employs the saturates-aromatic-resins-asphaltenes (SARA) separation method. In Chapter 5, the sulfur containing compounds of a Middle East crude oil are speciated. The crude oil is additionally fractionated by the SARA method and its fractions are analyzed by APPI FT-ICR mass spectrometry. Molecular species from the whole crude oil and its fractions are compared to ascertain differences and similarities between sulfur species in the fractions. Non-polar sulfur species are not efficiently ionized by ESI. However, derivatization chemistry can methylate polycyclic aromatic sulfur species and form cations in solution with subsequent analysis by ESI mass spectrometry. In Chapter 6, the derivatized and non-derivatized samples of a petroleum vacuum bottom residue (the highest boiling point fraction of petroleum and hence, the most complex heteroatom content) are analyzed by ESI and APPI. Significant differences in the double bond equivalent values (DBE, value equal to the number of rings plus double bonds in the molecular structure calculated from the elemental formula) between the ESI and APPI analyzed sulfur species are identified. Furthermore, this report provides data that probes APPI ionization efficiency. Chapter 7 is a synopsis of the APPI technology applied to petroleum analysis. The chapter also includes a real world application of APPI FT-ICR mass spectrometry. The Institute of Petroleum at France (IFP) is interested in the development of new hydroconversion processes to upgrade vacuum bottom residue to more useful petroleum products. A substantial fraction of vacuum bottom residue is the asphaltenes; the most heteroatom rich fraction in petroleum. The chapter presents molecular speciation from intermediate stages of a hydroconversion process; a first step in hydroconversion catalytic technology improvement. A Ph.D. thesis may also include research outside the scope of the primary dissertation research to achieve a broader understanding of the sciences. Appendix A describes the ongoing construction and adaptation of an ion cluster source to an existing FT-ICR mass spectrometer. The primary investigator is Professor Harry Kroto, Nobel prize laureate for the discovery of fullerenes. Fullerenes are closed cage molecules consisting of 12 pentagonal and several hexagonal rings. Fullerenes with 60 carbon atoms or larger follow the isolated pentagon rule (IPR). Smaller fullerenes ( In appendix B, the reaction products of C60 and hydrogen at high temperature and pressure are resolved and identified. The product species formed at elevated temperature and hydrogen pressure are characterized by APPI FT-ICR mass spectrometry. Only the APPI analysis (and Field Desorption, FD) were accomplished at Florida State University and the first report (of three published reports) is presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".