Multiphase Structure of Bio-oils
Bibliographic record
Abstract
The multiphase complex structure of biomass pyrolysis oils can be attributed to the presence of char particles, waxy materials, aqueous droplets, droplets of different nature, and micelles formed of heavy compounds in a matrix of hollocellulose-derived compounds and water. Bio-oil complexity is illustrated by use of two oils produced from the vacuum pyrolysis of softwood bark residues (SWBR) and hardwood rich in fibers (HWRF). The effect of waxy materials on bio-oil behavior was studied by differential scanning calorimetry (DSC), optical microscopy, and surface tension measurements as well as by steady and dynamic rheological techniques. At around 45 °C the melting of waxy materials occurs. Bio-oil cooling rate was found to have an important effect on some bio-oil rheological characteristics. This may be due to crystallization of waxy materials. Strain and frequency sweep tests proved the existence of a network (gel) structure in the bottom layer of oils derived from SWBR. This structure may be formed of relatively heavy oligomeric compounds that are associated in form of micelles. The observed network structure disappears above 60 °C. The HWRF-derived oil behaves much more like a Newtonian fluid.
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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) | 0.002 | 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".