Altering bio-oil composition by catalytic treatment of pinewood pyrolysis vapors over zeolites using an auger - packed bed integrated reactor system
Bibliographic record
Abstract
Pine wood pyrolysis vapors were catalytically treated using zeolite catalysts. An auger fed reactor was used for the pine wood pyrolysis while a packed bed reactor mounted on the top of the auger reactor housed the catalyst for the treatment of pine wood pyrolytic vapors. The pyrolytic vapors produced at 450 oC were passed through zeolite catalysts maintained at 425 oC at a weight hourly space velocity (WHSV) of 12 h-1. Five zeolites, including ZSM-5, mordenite, ferrierite, zeolite-Y, and zeolite-beta (all in H form), were used to study the effect of catalyst properties such as acidity, pore size, and pore structure on catalytic cracking of pine wood pyrolysis vapors. Product bio-oils were analyzed for their chemical composition (GC-MS), water content, density, viscosity, acid value, pH, and elemental compositions. Thermogravimetric analysis (TGA) was performed to analyze the extent of coking on zeolite catalysts. Application of catalysis to biomass pyrolysis increased gas product yields at the expense of bio-oil yields. While all the zeolites deoxygenated the pyrolysis vapors, ZSM-5 was found to be most effective. The ZSM-5 catalyzed bio-oil, rich in phenolics and aromatic hydrocarbons, was less viscous, had relatively lower acid number and high pH, and possessed oxygen content nearly half that of un-catalyzed bio-oil. Brønsted acidity, pore size, and shape-selective catalysis of ZSM-5 catalyst proved to be the determining factors for its activity. TGA results implied that the pore size of catalysts highly influenced coking reactions. Regeneration of the used catalysts was successfully completed at 700 oC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".