Migration and emissions of selenium during chemical looping combustion of coal
Bibliographic record
Abstract
Abstract Selenium is one of the most volatile toxic elements in coal, and its emissions must be strictly controlled. Chemical looping combustion (CLC) is a clean and efficient technology for coal. Herein, the iron‐based oxygen carrier (OC) was used as an adsorbent to study the migration and emissions of selenium during the CLC of coal. Due to the oxidation and adsorption of selenium by iron‐based OC, most of the selenium was retained in OC or distributed in the CO 2 stream. The proportion of gaseous selenium released into the atmosphere was less than 10%—significantly lower than that from the traditional combustion process of coal, which had a value of 91.79%. The presence of OC increased the distribution phase of selenium, promoted the conversion of gaseous selenium to solid selenium, and reduced selenium emissions in flue gas. During CLC of coal, the fuel reactor (FR) temperature and the number of OC re‐oxidation cycles played an important role in the emissions and retention of selenium. The increasing FR temperature increased the gaseous selenium in the CO 2 stream, reduced the particulate selenium absorbed by OC, and reduced the selenium emissions in the atmosphere. After 10 continuous CLC cycles, the selenium concentration in OC increased from 0.889 to 8.20 mg kg −1 . The continuous cycling of CLC could realize the enrichment of selenium from coal to OC. Furthermore, the migration and transformation mechanism of selenium during CLC was deduced by experiments and thermodynamic simulation. This research provides a suitable reference for reducing selenium emissions and developing CLC technology.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".