Influence of Biomass Pyrolysis Temperature, Heating Rate and Type of Biomass on Produced Char in a Fluidized Bed Reactor
Bibliographic record
Abstract
Biomass pyrolysis experiments were carried out in a fluidized bed reactor (FBR) and produced char yields were measured for 3 kinds of softwoods, 3 kinds of hardwoods, 2 kinds of herbaceous plants and 3 kinds of agricultural residues. Pyrolysis temperature range was between 300 °C and 1200 °C, and heating rate was fast (100–1000 °C/s) or slow (10 °C/min). After the pyrolysis, produced char was collected with bed particles and only the char was separated from bed particles by sieving. Surface of the produced char was observed by SEM to confirm bed particles adhesion behavior on the surface of char. Char-bed particles (alumina particles) adhesion were observed mainly under fast pyrolysis condition for most of the biomass samples. Char yields by fast pyrolysis were much lower than those by slow pyrolysis of Eucalyptus camaldulensis (hardwood), Japanese cypress (softwood), Switchgrass (herbaceous plant) and Bagasse (agricultural residue), respectively. In the case of fast pyrolysis condition, char yields from softwood species were lower than those from other biomass species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".