Upgrading Fast Pyrolysis Oil with Vacuum Gas Oil by Catalytic Hydrodeoxygenation in Supercritical Ethanol
Bibliographic record
Abstract
This work demonstrated an effective approach to upgrading bio-oils by upgrading pyrolysis bio-oil with vacuum gas oil (VGO) by catalytic hydrodeoxygenation (HDO) in supercritical ethanol with both hydrogen gas and formic acid as the in situ hydrogen source. The effects of supercritical ethanol, bio-oil/VGO mass ratio, reaction temperature, hydrogen source, and reaction time on co-upgrading pyrolysis bio-oil with VGO over Ru/Al 2 O 3 were investigated in this study. Crude bio-oil, crude VGO, and co-upgraded oils were characterized comparatively for their physical/chemical properties and compositions. It was found that the optimal reaction conditions of co-upgrading bio-oil with VGO were at a 4:1 mass ratio, in supercritical ethanol, with hydrogen gas as the hydrogen source, and at 350 °C for 2 h over the Ru/Al 2 O 3 catalyst. The obtained co-upgraded oils have improved thermal stability and homogeneity, which could be used as an environmentally friendly and sustainable feed for large-scale upgrading in a petroleum refinery.
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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) | 0.000 | 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".