Kinetic Study of Preoxidized Asphaltene Hydroprocessing in Aqueous Phase
Bibliographic record
Abstract
The solubilized asphaltene in water (SAW) was prepared by low-temperature oxidation in aqueous phase and used as a feedstock of hydroprocessing reaction. Hydroprocessing experiments were carried out in a 100 mL batch reactor within the temperature range of 280–320 °C in the presence of presulfided NiMo/γ-Al 2 O 3 catalyst. A lumped kinetic model with four components including water-soluble fractions, water-insoluble fractions, liquid hydrocarbons, and gas products was proposed, which accurately predicted the experimental results. The activation energy of global reaction was calculated to be 83 kJ/mol. At 320 °C, the liquid hydrocarbons yield increased around 8% by prolonging the residence time from 1 to 6 h. For 3 h residence time, by increasing the reaction temperature from 280 to 320 °C, the liquid yield was increased 5% and the conversion was enhanced by 8%. Increasing the reaction temperature affected the quality of products; that is, liquid hydrocarbons with lower boiling point distribution were obtained at higher reaction temperatures. At 320 °C, phenol derivative products disappeared, indicating the progress of deoxygenation at higher reaction temperatures. Fourier transform infrared analyses confirmed that disappearance of carboxylate functional groups through decarboxylation or protonation was the main reason for the production of water-insoluble fractions after the hydroprocessing. An extended Henry’s law with γ–ϕ approach was implemented to predict the thermodynamics status of the system at reaction conditions. The occurrence of reaction in the liquid phase was confirmed, where at 320 °C more than 80 wt % of water remained in the liquid phase and the liquid level in the reactor increased 25%.
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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 | 0.000 |
| 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".