Comparative study on adsorption of perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) by different adsorbents in water
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perfluorinated compounds (PFCs) are emerging environmental pollutants. Perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are the two primary PFC contaminants that are widely found in water, particularly in groundwater. This study compared the adsorption behaviors of PFOS and PFOA on several commercially available adsorbents in water. The tested adsorbents include granular activated carbon (GAC: Filtrasorb 400), powdered activated carbon, multi-walled carbon nanotube (MCN), double-walled carbon nanotube, anion-exchange resin (AER: IRA67), non-ion-exchange polymer, alumina, and silica. The study demonstrated that adsorption is an effective technique for the removal of PFOS/PFOA from aqueous solutions. The kinetic tests showed that the adsorption onto AER reaches equilibrium rapidly (2 h), while it takes approximately 4 and 24 h to reach equilibrium for MCN and GAC, respectively. In terms of adsorption capacity, AER and GAC were identified as the most effective adsorbents to remove PFOS/PFOA from water. Furthermore, MCN, AER, and GAC proved to have high PFOS/PFOA removal efficiencies (≥98%). AER (IRA67) and GAC (Filtrasorb 400) were thus identified as the most promising adsorbents for treating PFOS/PFOA-contaminated groundwater at mg L(-1) level based on their equilibrium times, adsorption capacities, removal efficiencies, and associated costs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it