Mobility Enhancement of Mn Oxide during Permanganate Oxidation of TCE
Bibliographic record
Abstract
Manganese (Mn) oxide precipitation during in situ permanganate oxidation of organic compounds can cause pore clogging, reduce permeability, and increase resistance to mass transfer. Stability of Mn oxide is required to enhance oxidation effectiveness. Batch tests were conducted at eight polyphosphate (PP) to permanganate ( ) mass ratios (0 to 8) at three MnO 4 −1 concentrations (500, 1000, or 2000 mg/L) for identifying mass ratios to maximize stability of Mn oxide produced in the presence of trichloroethylene (TCE). In general, stability of Mn oxide was the maximum at mass ratio of approximately 4. Three column tests were designed to investigate the impact of PP on overall removal of 4.6 or 7.0 g TCE emplaced as nonaqueous phase liquid within the column porous media. Water flush, chemical flush using alone (1000 mg/L), and chemical flush using (1000 mg/L) and PP (4000 mg/L) were conducted. Mass removal of TCE and changes in media permeability were estimated over a period of 78 to 312 h (12 to 49 pore volumes [PVs]). Column tests demonstrated enhanced removal (~90%) of TCE during chemical flush with and PP in 12 PVs as compared with approximately 64% during ‐only flush and approximately 26% during water flush. Pressure drop changes across the column captured change in media permeability and revealed that water flush and PP and flush caused significantly lower flow resistance as compared with ‐only flush. These results indicate that PP was capable of mobilizing Mn oxide away from the reaction zones, thereby reducing pore clogging and enabling better and long‐term contact between TCE and the aqueous phase.
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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 | 0.000 | 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 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".