Reduction of carbon content in waste-tire combustion ashes by bio-thermal treatment
Bibliographic record
Abstract
Application of bio-catalyst (NOE-7F) in thermal treatment can adequately dispose dark-black fly ashes from co-combustion of both waste tires and coal. After thermal treatment of fly ashes by adding 10% NOE-7F, the carbon contents reduced by 37.6% and the weight losses increased by 405%, compared with the fly ashes without mixing with NOE-7F. The combustion behaviors of wasted tires combustion fly ashes with NOE-7F were also investigated by both thermogravimetric analysis (TGA) and differential thermal analysis (DTA). The results verify that NOE-7F has positive effects on the combustion of residual carbon and toxic polycyclic aromatic hydrocarbons (PAHs) enhance the energy release and reduce the toxicity during the process of thermal treatment. Furthermore, using NOE-7F to dispose high-carbon content fly ashes did improve the compressive strength of fly ashes and concrete mixtures. Therefore, NOE-7F is a promising additive which could decrease treatment cost of high-carbon content fly ashes and reduce the amount of survival toxic PAHs.
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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".