Dissolved Selenium(VI) Removal by Zero-Valent Iron under Oxic Conditions: Influence of Sulfate and Nitrate
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Dissolved Se(VI) removal by three commercially available zero-valent irons (ZVIs) was examined in oxic batch experiments under circumneutral pH conditions in the presence and absence of NO 3 – and SO 4 2– . Environmentally relevant Se(VI) (1 mg L –1 ), NO 3 – ([NO 3 —N] = 15 mg L –1 ), and SO 4 2– (1800 mg L –1 ) were employed to simulate mining-impacted waters. Ninety percent of Se(VI) removal was achieved within 4–8 h in the absence of SO 4 2– and NO 3 – . A similar Se(VI) removal rate was observed after 10–32 h in the presence of NO 3 – . Dissolved Se(VI) removal rates exhibited the highest decrease in the presence of SO 4 2–; 90% of Se(VI) removal was measured after 50–191 h for SO 4 2– and after 150–194 h for SO 4 2– plus NO 3 – depending on the ZVI tested. Despite differences in removal rates among batches and ZVI materials, Se(VI) removal consistently followed first-order reaction kinetics. Scanning electron microscopy, Raman spectroscopy, and X-ray diffraction analyses of reacted solids showed that Fe(0) present in ZVI undergoes oxidation to magnetite [Fe 3 O 4 ], wüstite [FeO], lepidocrocite [γ-FeOOH], and goethite [α-FeOOH] over time. X-ray absorption near-edge structure spectroscopy indicated that Se(VI) was reduced to Se(IV) and Se(0) during removal. These results demonstrate that ZVI can be effectively used to control Se(VI) concentrations in mining-impacted waters.
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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 | 0.000 |
| 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 it