Thermal Conversion of Athabasca Bitumen under Low- and High-Pressure Conditions: Influence on Cracking, Hydrogen Transfer, and Addition Reactions
Bibliographic record
Abstract
Visbreaking is a mature thermal conversion process for heavy oils, yet the molecular effects of pressure on phase behavior and reaction chemistry of the liquid feed remain poorly understood. While thermal conversion predominantly occurs in the liquid phase, the process operates in a mixed vapor-and-liquid system. In this context, pressure does not directly influence the liquid-phase reaction kinetics but instead modulates vapor–liquid equilibrium and thereby affects the vapor phase volume fraction, influencing the broader reaction environment and overall product distribution. Experimental evidence from an earlier study shows that high pressure (2.5–4.0 MPa) suppresses coke yield (2.4 ± 0.35 wt %) at a comparable vacuum residue conversion to that at low-pressure reactions (3.9 ± 0.79 wt % at 0.5–2.0 MPa). This study aims to elucidate the influence of pressure on cracking pathways, hydrogen transfer, and addition reactions through a suite of spectroscopic analyses (UV–vis, FTIR, and 1 H NMR), which were used to further characterize the structural changes in these liquid products. Spectroscopy reveals that low-pressure conditions promote aromatic condensation and the loss of alkyl constituents, as evidenced by a decreased aliphatic-to-aromatic hydrogen ratio and increased aromaticity in the products, changes that promote higher coke yields. In contrast, high initial pressure preserves more aliphatic content and favors hydrogen redistribution instead of hydrogen loss. Specifically, higher pressure led to an increased methylene-to-methyl ratio ( n CH 2 / n CH 3 ) and a higher methyl hydrogen content in the liquid products, which suggests enhanced methyl transfer reactions under these conditions. These findings provide valuable molecular insights into how pressure can optimize visbreaking and mitigate coke formation by retaining hydrogen-rich light species in the liquid phase.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".