Analysis of Hydrocarbon Compositional Changes during Oxidative Desulfurization of Bitumen-Derived Gas Oil
Bibliographic record
Abstract
Sulfur compounds in bitumen-derived gas oil undergo selective oxidation using a titanium-derived catalyst, resulting in the formation of sulfones and sulfoxide species. Using caustic solution, the sulfones and sulfoxide species are then chemically converted to hydrocarbon compounds by replacing C–S fragments with C–H fragments. In this study, we provide detailed chemical and structural hydrocarbon-type information for the hydrocarbon streams. The results presented in this paper consist of data obtained using elemental analysis, saturate–aromatic–resin–asphaltene (SARA) separation, and comprehensive two-dimensional gas chromatography (GC × GC) with both flame ionization/sulfur chemiluminescence detectors (FID/SCD) and time-of-flight mass spectrometry detector (TOFMS). These techniques were used to track elemental composition, the speciation of sulfur-containing hydrocarbons, and their respective oxidized and desulfurized counterparts in three bitumen-derived gas oil samples. Based on the compositional data presented in this study, 87.5% of the sulfur compounds were converted to sulfone/sulfoxides compared to the original gas oil feed, followed by 72.5% of the sulfone/sulfoxide conversion to sulfur-free hydrocarbons, resulting in a 63% reduction of the sulfur originally present in the sample. This work is the first known attempt to identify the broad range of species appearing during the oxidative desulfurization (ODS) process of bitumen-derived gas oil feed with the use of GC × GC-TOFMS/SCD/FID techniques. The comprehensive characterization results of SARA fractions provide evidence of the existence of species from two consecutive stages of ODS reactions, oxidation, and desulfurization, which is beneficial to further technology and process development.
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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 | 0.001 |
| 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".