Impact of Sodium Humate Coating on Collector Surfaces on Deposition of Polymer-Coated Nanoiron Particles
Bibliographic record
Abstract
The affinity between nanoscale zerovalent iron (nano-ZVI) and mineral surfaces hinders its mobility, and hence its delivery into contaminated aquifers. We have tested the hypothesis that the attachment of poly(acrylic acid)-coated nano-ZVI (PAA-nano-ZVI) to mineral surfaces could be limited by coating such surfaces with sodium (Na) humate prior to PAA-nano-ZVI injection. Na humate was expected to form a coating over favorable sites for PAA-nano-ZVI attachment and hence reduce the affinity of PAA-nano-ZVI for the collector surfaces through electrosteric repulsion between the two interpenetrating charged polymers. Column experiments demonstrated that a low concentration (10 mg/L) Na humate solution in synthetic water significantly improved the mobility of PAA-nano-ZVI within a standard sand medium. This effect was, however, reduced in more heterogeneous natural collector media from contaminated sites, as not an adequate amount of the collector sites favorable for PAA-nano-ZVI attachment within these media appear to have been screened by the Na humate. Na humate did not interact with the surfaces of acid-washed glass beads or standard Ottawa sand, which presented less surface heterogeneity. Important factors influencing the effectiveness of Na humate application in improving PAA-nano-ZVI mobility include the solution chemistry, the Na humate concentration, and the collector properties.
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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 | 0.001 |
| 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".