Sulfidation of Magnetite for Superior Dechlorination of Trichloroethene
Bibliographic record
Abstract
The reported contributions of magnetite to the abiotic natural attenuation of chlorinated ethenes have generated interest in its potential for soil and groundwater remediation. In this study, we investigated the impact of the two-step sulfidation method on the physicochemical properties and reactivity of magnetite with trichloroethene (TCE). We systematically evaluated the effect of different sulfur precursors (dithionite, thiosulfate, and sulfide) and sulfur-to-iron ([S/Fe] dosed ) molar ratios on the reactivity. Results were compared to those of sulfidated nZVI (S-nZVI) as a benchmark for assessing the efficacy of sulfidated magnetite (S–Fe 3 O 4 ). The findings indicated limited reactivity of magnetite when sulfidated with dithionite and thiosulfate. However, sulfidation with sulfide yielded reaction rates comparable to those of S-nZVI, particularly at lower [S/Fe] dosed ratios. At higher [S/Fe] dosed ratios (>0.1), sulfide-sulfidated magnetite (S–Fe 3 O 4_S ) exhibited reaction rates surpassing those of S-nZVI, with the major dechlorination product being acetylene. Nonetheless, reusability experiments demonstrated that the performance of S–Fe 3 O 4 diminished with aging. These results show that S–Fe 3 O 4_S achieved complete transformation of TCE to acetylene, with reaction rates comparable to S-nZVI. Given its lower cost of production, engineered S–Fe 3 O 4_S remediation systems could serve as a more affordable alternative for in situ chemical reduction of TCE with further research and development.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".