Liquefaction of Pinewood in Supercritical Carbon Dioxide (SCCO<sub>2</sub>)
Bibliographic record
Abstract
Liquefaction of lignocellulosic biomass is a promising process to produce liquid biofuels and valuable chemicals. The main purpose of this work is to efficiently liquefy biomass into energy-dense bio-oils through direct liquefaction. Pinewood sawdust was liquefied in supercritical carbon dioxide (SCCO2) at various temperatures (225-375°C) and residence time (0-4 hours) with alkaline catalyst (K2CO3). The results showed that the yield of bio-oils varied from 12 wt% to 29 wt% under various conditions. The optimal parameters for SCCO2 liquefaction were 300°C and 2 hours in this study, which generated the maximum bio-oil yield 29 wt%. The effects of temperature and residence time on SCCO2 liquefaction process were discussed. Multiple analytical methods such as GC-MS, FT-IR and elemental analyzer were applied to study the compositions and properties of liquid bio-oils. Keywords: Bio-oils, Biomass, Liquefaction, Supercritical carbon dioxide.
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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".