Examining Mechanisms of Groundwater Hg(II) Treatment by Reactive Materials: An EXAFS Study
Bibliographic record
Abstract
Laboratory batch experiments were conducted to examine mechanisms of Hg(II) removal by reactive materials proposed for groundwater treatment. These materials included granular iron filings (GIF), 1:1 (w/w) mixtures of metallurgical granular Fe powder + elemental S (MGI+S) and elemental Cu + elemental S (Cu+S), granular activated carbon (GAC), attapulgite clay (ATP), ATP treated with 2-amino-5-thiol-1,3,4-thiadiazole (ATP-a), and ATP treated with 2,5-dimercapto-1,3,4-thiadiazole (ATP-d). Following treatment of simulated groundwater containing 4 mg L(-1) Hg for 8 or 16 days, the solution pH values ranged from 6.8 to 8.8 and Eh values ranged from +400 to -400 mV. Large decreases in aqueous Hg concentrations were observed for ATP-d (>99%), GIF (95%), MGI+S (94%), and Cu+S (90%). Treatment of Hg was less effective using ATP (29%), ATP-a (69%), and GAC (78%). Extended X-ray absorption fine structure (EXAFS) spectra of Hg on GIF, MGI+S, and GAC indicated the presence of an Hg-O bond at 2.04-2.07 Å, suggesting that Hg was bound to GIF corrosion products or to oxygen complexes associated with water sorbed to activated carbon. In contrast, bond lengths ranging from 2.35 to 2.48 Å were observed for Hg in Cu+S, ATP-a, and ATP-d treatments, suggesting the formation of Hg-S bonds.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".