Self-Association of Organic Acids in Petroleum and Canadian Bitumen Characterized by Low- and High-Resolution Mass Spectrometry
Bibliographic record
Abstract
We examine solution-phase aggregation for a whole crude oil, whole bitumen, and bitumen distillate fractions by negative-ion electrospray ionization [(−) ESI] detected by both high-resolution [Fourier transform ion cyclotron resonance (FT-ICR)] and low-resolution [linear quadrupole ion trap (LTQ)] mass spectrometry (MS). Aggregate formation for both crude oil and bitumens is concentration-dependent. At high concentrations (i.e., >1 mg/mL), the disruption of noncovalent interactions between heteromultimers by low-energy collision-activated dissociation (CAD) yields LTQ dissociation mass spectra with molecular-weight distributions identical to those observed by FT-ICR MS analysis at lower concentrations for purely monomeric species. These materials can exist as aggregates in solution even at high dilution (less than 0.1 mg/mL). We demonstrate the concentration and boiling point dependence for multimerization of polar acidic species in the Athabasca bitumen and bitumen distillates. Interestingly, the lowest boiling distillation cut (375−400 °C) displays the highest aggregation tendency, with dimers at concentrations as low as 0.05 mg/mL. Higher boiling point distillation cuts display a decreased aggregation tendency with an increasing cut point. High-resolution negative-ESI FT-ICR MS of the bitumen distillation fractions reveals the elemental composition, and thus the class, type, and carbon number of the multimeric species. Acidic heteroatomic classes for the distillation cut multimers include O 4, S 1 O 4, O 3, S 1 O 3, N 1 O 2, and N 1 S 1 O 2 . The most abundant multimers for the 375−400 °C distillation cut are O 4 species, whereas the 450−475 °C cut contains N 1 O 2 multimers in the highest relative abundance. Changes in multimer heteroatom content as a function of the monomer composition and distillation cut suggest that aggregation depends upon the chemical functionalities of the monomer species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".