Experiment of the Macromolecular Chitosan to Remove Mercury in the Flue Gas of Coal Combustion
Bibliographic record
Abstract
A one-dimension furnace test bench experiment is conducted to study the Chitosan sorbent’s adsorption efficiency of mercury in coal-fired flue gas. In this work, the method of Ontario Hydro and Atomic Absorption Spectrometry is used to analyze the form distribution and content of the mercury in the flue gas of coal combustion. At the same time, three kinds of modified Chitosan(CS)sorbents are prepared to remove the mercury in the flue gas. The results show that the element mercury is more than bivalent mercury and the ratio is 3:2. The CS sorbents can adsorb Hg0. The mercury adsorption efficiency is 96.34% at 80℃, especially the CS can remove the SOx and NOx simultaneously. The chitosan, it’s a new and effective adsorption in the field of heavy metal removing in flue gas.
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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".