Aqueous Leaching of Ultrashort-Chain PFAS from (Fluoro)polymers: Targeted and Nontargeted Analysis
Bibliographic record
Abstract
Abstract Fluoropolymers are a class of per- and polyfluoroalkyl substances (PFAS) defined as high molecular weight plastics containing only carbon-based backbones with F atoms directly attached. Here, we used targeted and nontargeted analytical methods to quantify the aqueous leaching of small-molecule PFAS from three types of fluoropolymer tubing material and three types of nonfluorinated polymer tubing material. C2–C4 perfluoroalkyl carboxylic acids (PFCAs) were quantified with ion chromatography–mass spectrometry, and C4–C9 PFCAs were quantified with liquid chromatography–tandem mass spectrometry. A new 19F nuclear magnetic resonance (NMR) method with lower detection limits provided an unbiased, nontargeted view of all fluorinated chemicals in the aqueous leachate. C2–C4 PFCAs had a higher concentration than longer-chain PFCAs. All tubing tested, including the nonfluorinated polymers, contained trifluoroacetic acid (C2 PFCA) concentrations above the blank. NMR identified additional fluorinated chemicals, especially in the nonfluorinated PEEK, a common replacement for fluoropolymers in laboratory chromatography systems. Overall, each fluoropolymer tested had different fingerprints of C2–C4 PFCAs, which may be related to their synthetic production such as processing aids, residuals, and inhibitors used; fluorinated chemicals were also identified from nonfluorinated polymers. The outcome of this work informs better trace analysis in the laboratory and presents an indication of how fluoropolymers and other plastics can be an emission source to the environment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".