Modeling Geochemical and Reactivity Changes of Different Iron Materials
Why this work is in the frame
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Bibliographic record
Abstract
Including declining reactivity of iron, resulting from precipitation of secondary minerals, into reactive transport models is a key component for better estimation of longevity of iron permeable reactive barriers (PRBs). In this study, the accumulation of secondary minerals and reactivity loss were coupled using an empirically-derived relationship that was incorporated into an existing multi-component reactive transport code. The simulation results were compared to the observations from column experiments, which were designed to evaluate the changes of the reactivity of different iron materials for cis-dichloroethene (cis-DCE) treatment in the presence of dissolved CaCO3. The model provided a reasonable representation of the evolution of iron reactivity toward cis-DCE treatment and the changes in geochemical conditions for each material. The modeling results suggest that iron material having a high corrosion rate is not beneficial in the presence of a high concentration of dissolved CaCO3 because of a faster migration of cis-DCE profiles and greater porosity loss closer to the influent end. This study shows that declining reactivity of iron due to mineral precipitation should be considered at the design stage of iron PRB construction.
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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) | 0.001 | 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 it