The Adsorption of Perfluorooctane Sulfonate onto Sand, Clay, and Iron Oxide Surfaces
Bibliographic record
Abstract
Fluorinated anionic surfactants have drawn considerable attention due to recent work showing significant concentrations in surface waters and biota from around the globe. A detailed understanding of the transport and fate of fluorinated surfactants through soil and like media must include an elucidation of mineral surface chemistry. Five materials were equilibrated with solutions of perfluorooctane sulfonate (PFOS) to characterize adsorption: kaolinite, Ottawa sand standard, synthetic goethite, Lake Michigan sediment, and iron-coated sand from Mappsville, VA. Aqueous and adsorbed PFOS was quantified with LC/MS (mass balance average: 101 ± 12 %, n = 37). The materials showed a near linear increase in adsorption as the equilibrium concentrations increased. Isotherms and calculated solid/solution distribution ratio experiments indicated that PFOS adsorption is significant but smaller than hydrocarbon analogues or organic compounds of similar molecular weight. Surface area normalized adsorption increased for the materials in the following order: goethite < kaolinite < high iron sand < Ottawa sand standard. Experimental results and comparisons to published data suggest that organic carbon may play an important role in sorption whereas electrostatic attraction may play a role when organic carbon is not present.
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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 | 0.000 | 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 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".