The use of 19F NMR and mass spectrometry for the elucidation of novel fluorinated acids and atmospheric fluoroacid precursors evolved in the thermolysis of fluoropolymers
Bibliographic record
Abstract
Fluoropolymers are widely used in industry and consumer products. At the thermal limit of their stability (e.g. > 260 degrees C for PTFE) numerous studies have reported a variety of thermolysis products produced upon polymer breakdown. In the current investigations our objective was to expand the knowledge of these products by advancing the techniques used to obtain their identity. The use of 19F NMR to compliment derivatization with GC-MS has been shown to facilitate the identification of novel fluorinated species, in particular fluorinated acids, that had, until recently, gone previously unreported for the thermal decomposition of fluorinated polymers using traditional techniques. The polymers chosen for the decomposition studies were poly(tetrafluoroethylene), poly(chlorotrifluoroethylene), poly(ethylene-chlorotrifluoroethylene) and poly(tetrafluoroethylene-co-tetrafluoroethylene perfluoropropyl ether) which cover the three major classes of industrially produced fluoro-polymer, co-polymer and elastomer. The use of 1D 19F and 2D 19F-19F correlation spectroscopy (COSY) NMR allowed for the observation of polyfluorinated acids and their atmospheric precursors. This in turn allowed the modification of GC-MS procedures to verify these NMR findings. NMR results also showed a plethora of unidentified and previously unreported materials, thermolysis products that await characterization.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".