Mechanochemical Destruction of Per-and Polyfluoroalkyl Substances in four Aqueous Film Forming Foam Formulations using amended Silica Sand and Potassium Hydroxide
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFAS) are a diverse group of manmade, fluorinated organic chemicals that gained notoriety for their diverse application, widespread distribution in the environment and toxicity. One of the main sources of PFAS to the environment is through aqueous film forming foam (AFFF), intended for use on fuel fires. AFFF may enter the environment through system testing, training activities, emergency use or accidental release. When AFFF enters the environment PFAS readily adsorb to porous media through hydrophobic and electrostatic interactions. As a result, PFAS impacted porous media may act as a long-term source of contamination to groundwater, potentially influencing water resources and human health. There is a demand for effective treatment of PFAS impacted porous media. Ball milling has emerged as a potential treatment option for PFAS, however, the viability of treating AFFF impacted porous media has been seldom explored. In this work four AFFF formulations were amended onto silica sand and milled without and with the use of potassium hydroxide (KOH) as a co-milling reagent. Six hour milling trials were conducted using a planetary ball mill with stainless steel grinding media. Significant destruction of perfluorosulfonic acids, perfluorocarboxylic acids (PFCAs), fluorotelomer sulfonates, fluorotelomer betaines and fluorotelomer sulfonamido betaines was observed. With the use of KOH as a co-milling reagent the total PFAS destruction percentage in all four AFFFs exceeded 90%. Greater destruction of PFAS was observed in fluorotelomer dominant AFFFs when compared to perfluoroalkyl acid dominant AFFFs. PFCAs and soluble fluoride were identified as destruction byproducts. KOH as a co-milling reagent had the effect of reducing PFCA byproduct formation and increasing fluoride recovery in three of four AFFFs. Fluoride recoveries indicate PFAS molecule defluorination occurs by ball milling. When PFAS in AFFF is compared to PFAS destruction in single analyte trials, less destruction is observed, displaying the necessity of evaluating realistic AFFF contamination events over single or multi analyte mixtures.
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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".