Reforming of Glycerol into Bio-Crude: A Parametric Study
Bibliographic record
Abstract
The reforming of glycerol was investigated using a micro-reactor in the presence of MoCoP/zeolite catalyst. The parameters which were investigated include initial hydrogen pressure, reaction temperature, residence time, and feedstock concentration. The liquid products were separated into water-soluble components and bio-oil by liquid-liquid extraction with water and ethyl acetate. The bio-oil, gaseous products, char, and unreacted glycerol were quantified relative to the initial mass of glycerol feed. The composition of the bio-oil was determined by GC/MS. The optimum conditions for the reforming of glycerol into bio-crude in the presence of MoCoP/zeolite catalyst were found to be: 300°C reaction temperature, 5 MPa initial hydrogen pressure, 60 min reaction time, and 100% glycerol feed. While dilution of the glycerol feedstock with water had a negative effect on bio-oil yield, reforming of pure glycerol produced the highest bio-oil yield (40 wt.% at 300°C, 1 h, and 5 MPa H 2 ). The amount of char deposited on the catalyst decreased with extended reaction time, increased reaction temperature, and elevated initial hydrogen pressure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".