Transformation of 6:2 Fluorotelomer Sulfonate by Cobalt(II)-Activated Peroxymonosulfate
Bibliographic record
Abstract
Abstract Peroxymonosulfate (PMS)-based advanced oxidation processes generate highly reactive SO4•– and are promising for water treatment. In this study, we investigated the reaction mechanism of 6:2 fluorotelomer sulfonate (6:2 FTS) with Co2+-activated PMS. 6:2 FTS was simultaneously transformed to perfluoroalkyl carboxylic acids (C2–C7 PFCAs) of different chain lengths, with perfluorohexanoic acid (C6) as the predominant one. The mass balance of the intermediates and products versus the initially added 6:2 FTS was close to 100% over the reaction period. Using chemical scavenging methods, we identified that •OH, instead of SO4•–, was the oxidant initiating the reaction of 6:2 FTS. •OH was mainly produced from SO4•– reacting with H2O. Thus, the reactivity of 6:2 FTS was controlled by the factors affecting the production and scavenging of both SO4•– and •OH. Density functional theory calculations showed that •OH oxidizes 6:2 FTS by H-abstraction from ethyl carbons. This is the first study that demonstrates that •OH in Co2+-activated PMS can play a significant role in contaminant transformations. The results indicate that great caution should be taken when PMS or other agents that generate •OH are used for the treatment of water containing 6:2 FTS or its structural analogs.
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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) | 0.001 | 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".