Contribution of Volatile Interactions During Co-Gasification of Biomass with Coal
Bibliographic record
Abstract
Thermo-gravimetric behavior during steam co-gasification of Japanese cedar and coal was investigated. The difference between co-gasification behavior and the average gasification behavior of cedar and coal indicates two synergetic peaks. The first peak occurred between 300 °C and 550 °C while the second peak was observed above 800 °C. The first peak coincides with volatile release and therefore associated with volatile interactions while the second peak is linked with catalytic effect of alkali and alkaline earth metal (AAEM). Acid washed cellulose and Na rich lignin chemicals were used as artificial biomass components. In reference to Japanese cedar, mixture of cellulose and lignin i.e. simulated biomass, was also investigated. Co-gasification of cellulose with coal and co-gasification of lignin with coal, demonstrates contribution of volatile interactions and AAEM catalysis respectively. Morphology of partially gasified blends, shows hastened pore development and physical cracking on coal particles. Brunauer−Emmett−Teller (BET) surface area of the charred blend was lower than the average surface area for charred biomass and coal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".