Simultaneous <scp>NO<sub><i>x</i></sub></scp> and <scp>SO<sub>2</sub></scp> removal during wet flue gas desulfurization, using copper smelter slag slurry combined with yellow phorphorus
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The study of copper slag has attracted the attention of scholars from both China and around the world. But few have paid attention to its applications in the simultaneous removal of SO 2 and NO x in wet flue gas desulfurization (WFGD), becasue WFGD technique is inappropriate for directly treating NO x owing to the low solubility of NO. This work aims to improve NO x removal efficiency in WFGD technology using copper slag slurry associated with the oxidation of NO x by yellow phosphorus. Different operating conditions, including dispersion of P 4 , solid‐liquid ratio, initial pH value of copper slag slurry, reaction temperature, oxygen content, and gas flow rate, were compared regarding the efficiency of SO 2 and NO x simultaneous removal. The characterizations were carried out on the liquid and solid part of fresh and spent copper slag slurry after filtration. The results indicated that a great amount of metals ions, such as Fe 3+ and Zn 2+ , were leached by reacting with produced acids (H 2 SO 4 , HNO 3 , and H 3 PO 4 ), which had a liquid‐phase catalytic oxidation on S IV species (SO 3 2− /HSO 3 − ), leading to promotion in absorption for SO 2 . The copper slag played a significant role in dispersing the yellow phosphorus and promoting ozone generation, thus improving NO x removal efficiency. The reaction pathway can be divided into three parts: (a) ozone generation induced by yellow phosphorus, (b) the oxidation of NO by O 3 and then dissolution in aqueous solution, and (c) the dissolution of SO 2 and the liquid‐phase oxidation for SO 2 through metal ions produced by the reaction between acid and copper slag.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it