Real-Time XANES Measurement of Se Reduction by Zerovalent Iron in a Flow-through Cell, and Accompanying Se Isotope Measurements
Bibliographic record
Abstract
An anoxic flow-through cell experiment was conducted to examine mechanisms controlling the real-time reduction of selenate (Se(VI)) by zerovalent iron (ZVI), which is commonly used in permeable reactive barriers to treat dissolved contaminants including Se(VI). Changes in selenium (Se) isotope composition were examined by increasing the influent Se concentration over time, thus changing the proportion of Se removed from solution. At the conclusion of the experiment, an anoxic Se-free solution was pumped through the cell to assess the stability of the reaction products. At all stages, X-ray absorption data were obtained from the solid phase and Se isotope data from the aqueous phase. Reduced Se in the form of adsorbed Se(IV), Fe 2 SeO 4, Se(0), and iron selenides accumulated on the ZVI over time. A linear regression function was fit to the δ 82/76 Se values of the effluent, yielding an isotopic separation of 9.6‰. A Rayleigh curve was fit to the isotope data from the effluent samples collected during the rinse stage with an effective fractionation of 2.4‰. The results from this experiment can be used to elucidate the effect of multiple concurrent mechanisms on Se isotope behavior.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".