Degradation of PFOS in concentrated saline waste streams using UV/ Sulfite process: Critical impact of aggregation
Bibliographic record
Abstract
Ultraviolet/sulfite (UV/S)-based advanced reduction has been considered a promising approach for the degradation of per- and polyfluoroalkyl substances (PFAS). Focusing on the UV/S treatment of perfluorooctane sulfonate (PFOS) in solutions representative of ion exchange (IEX) regeneration waste, this study highlights the critical need to account for and overcome PFOS aggregation when assessing degradation performance. Aggregation, rather than true degradation, can result in an apparent near-complete decrease in bulk PFOS concentration, leading to misleading interpretations. Despite adjustments in operational parameters, PFOS aggregation and subsequent surface adsorption persisted under high-ionic-strength conditions, introducing artifacts that confound accurate evaluation of degradation efficiency. The addition of cetyltrimethylammonium bromide (CTAB) as a secondary surfactant effectively mitigated aggregate formation, preventing misleading concentration artifacts. Molecular simulations revealed that CTAB promotes micellar reorganization of PFOS via two synergistic mechanisms: complex salt-bridging interactions and frontier orbital segment pairing. This restructuring also enhanced hydrated electron delivery to PFOS, enabling nearly complete degradation and up to 87 % defluorination. CTAB addition thus emerged as an effective strategy, promoting accelerated PFOS degradation under relatively mild conditions in saline solutions. The mechanistic insights drawn in this study, validated through complementary experiments and simulations, offer novel perspectives on addressing challenges in PFOS degradation.
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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".