Characterization of Basic Nitrogen Species in Coker Gas Oils by Positive-Ion Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
Bibliographic record
Abstract
Six coker gas oils (CGOs) and three basic fractions extracted from one of the CGOs by 0.1, 0.4, and 1 M HCl hydrochloric acid were characterized by positive-ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) and compared to those analyzed by gas chromatography mass spectrometry (GC-MS). The ultra high mass resolving power and high mass accuracy of FT-ICR MS allow the assignment of a unique elemental composition to each peak in the mass spectrum. Basic nitrogen species were characterized by class, type, and carbon number. The mass spectra of the CGOs at the 200−500 Da mass range were similar, but the distribution of double bond equivalence (DBE) versus carbon number were different. Among the N, N 2, NO, and NS that were identified in CGOs, the N class nitrogen species were dominant. The results showed that hydrotreating reduced the relative abundance of all class species, except for the N class species. This suggests that some N class species are refractory to hydrotreating. The molecular weight of nitrogen species in the acid-extracted basic nitrogen fraction of CGO was lower than that of its parent CGO. The N 3, NO 2, and N 2 O class species were clearly identified and concentrated in the basic nitrogen fraction, but were not detected in their parent CGO. The N class species with ring plus DBE value of 4−16 in the basic nitrogen fraction were also identified by GC-MS analysis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".