High temperature fluidized bed zero valent iron process for flue gas nitrogen monoxide removal
Bibliographic record
Abstract
A fluidized bed zero valent iron (ZVI) reactor was designed for nitrogen monoxide (NO) removal with typical flue gas temperatures based on ZVI’s strong reducing abilities. Three different parameters: temperature, influent concentration, and ZVI dosage were tested. Higher NO removals were observed for higher temperature, which was contributed to either higher diffusivity for NO or higher rate constant at higher temperature instead of thermodynamic aspect, since enthalpy change of the chemical reaction (ΔH) is negative and equilibrium constant is decreased when temperature is increased. At the same temperature, ZVI capacities (as mg NO/g ZVI) were constant for both influent concentration and ZVI dosage variation. Activated energies were determined for two different stages: before and after breakthrough. Before breakthrough, excess ZVI was presented and the reaction was described as a pseudo-first order reaction, and the activated energy (Ea) for the first stage was calculated as 46.5 kJ/mol according to the Arrhenius equation. After breakthrough, the presence of ZVI was not in excess and the reaction order of ZVI and NO was considered as 2nd order (1 order in [NO] and 1 order in ZVI), and Ea was determined to be 7.5 kJ/mol.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".