Mercury Adsorption and Oxidation Performance of an Iron-Based Oxygen Carrier during Coal Chemical Looping Process
Bibliographic record
Abstract
During chemical looping combustion (CLC) and chemical looping gasification (CLG) of coal, the release, migration, and speciation of mercury in coal are significantly influenced by oxygen-carrier materials; however, the underlying mechanism remains inadequately addressed. In this work, the effect of a typical iron-based oxygen carrier on the release behavior of mercury from a bituminous coal and a lignite was investigated based on the Ontario-Hydro method. It is found that the effect of the iron-based oxygen carrier is attributed to three aspects: the enhanced release rate of mercury from coal, the adsorption of the released mercury, and the oxidization of gaseous Hg0 into Hg2+. With the increasing temperature, the adsorbance of mercury by the iron-based oxygen carrier decreases, while the oxidation of mercury enhances. Even at 900 °C, the adsorbance of mercury by the oxygen carrier remained at 0.1687 g/g, with a relative content of Hg2+ at 22.55%. Additionally, it was observed that iron-based oxygen carriers can physically absorb both Hg0 and Hg2+, while chemisorption refers to complex-compound formation between the iron-based oxygen carrier and mercury.
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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".