Effect of salts and pH on the removal of perfluorooctanoic acid (PFOA) from aqueous solutions through precipitation and electroflocculation
Bibliographic record
Abstract
This study shows that salt type and pH affect the removal of perfluorooctanoic acid (PFOA) from water through flocculation and electro-enhanced flocculation. PFOA concentrations decreased by approximately 80% with 20 mM FeCl 3 and initial pH = 3–10. Electro-enhanced flocculation at pH = 3 reduced PFOA concentrations in water by approximately 70% with CaCl 2 and KCl, and by 50% with NaCl. At alkaline pH, PFOA removal was approximately 20% with CaCl 2 and KCl. PFOA removal was negligible without salts or with AlCl 3 , and with NaCl at alkaline pH. Differences in PFOA removal are likely due to the settling behaviour of the cation-PFOA complexes formed.
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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 | 0.001 |
| 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".