Co-gasification of Biomass with Coal and Oil Sand Coke in a Drop Tube Furnace<sup>†</sup>
Bibliographic record
Abstract
The present paper is aimed at investigating the co-gasification of biomass with coal and oil sand fluid coke. Chars were obtained from individual fuels and blends with different blend ratios of coal, oil sand coke, and biomass in a drop tube furnace at different temperatures. The chars were then gasified in a thermogravimetric analyzer (TGA) under CO 2 atmosphere to determine their reactivity. Results showed that the effect of the blending ratio of biomass to other fuels on the reactivity of the co-pyrolyzed chars is more pronounced on chars prepared at low temperatures and the effect becomes less significant as the pyrolysis temperature increases. The increased reactivity at a higher biomass blending ratio is due to the presence of synergetic effects originating from the interaction of the two fuels. Scanning electron microscopy images showed differences in shapes and particle size distribution of char particles from biomass and coal/coke. These also showed the agglomeration of coal and coke chars with biomass char particles at high temperatures. The agglomeration may be the reason for the non-additive behavior of the blends. The chars were also analyzed for the particle size distribution using a laser diffraction Mastersizer instrument and surface area with the Brunauer−Emmett−Teller (BET) technique. BET analysis showed an increase in the surface area with an increasing temperature from 700 to 1400 °C for biomass and coal, but the trend for coke was inversely related to the temperature.
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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 | 0.001 |
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".