Sequential Extraction Study of Stability of Adsorbed Mercury in Chemically Modified Activated Carbons
Bibliographic record
Abstract
Activated carbons chemically modified with sulfur and bromine are known for their greater effectiveness in capturing vapor Hg from coal combustion and other industrial flue gases. The stability of captured Hg in spent activated carbons determines the final fate of Hg and is critical to devising Hg control strategy. However, it remains a subject that is largely unknown, particularly for Br-treated activated carbons. Using a six-step sequential extraction procedure, this work evaluated the leaching potential of Hg captured with four activated carbons, one lignite-derived activated carbon, and three chemically treated with Br(2), KClO(3), and SO(2). The results demonstrated clearly the positive effect of Br- and SO(2)-treatment on the stability of captured Hg. The Hg captured with brominated activated carbon was very stable and likely in the form of mercurous bromide complex. Sulfur added at high temperature with SO(2) was able to stabilize a majority of Hg by forming sulfide and possibly sulfonate chelate. The presence of sulfate however made a small fraction of captured Hg (<10%) labile under mild conditions. Treating activated carbon with KClO(3) lowered the overall stability of captured Hg. A positive dependence of Hg stability on Hg loading temperature was observed for the first time.
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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 | 0.001 |
| 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".