The Use of <sup>19</sup>F NMR to Interpret the Structural Properties of Perfluorocarboxylate Acids: A Possible Correlation with Their Environmental Disposition
Bibliographic record
Abstract
The use of perfluorinated anionic carboxylic acids (PFCAs) as surfactants is common and widespread. Investigations of PFCAs have shown that their physical properties and toxicological aspects are dependent upon the carbon chain length. The magnitude of these properties is not a linear function of chain length and as yet no explanation of these unique observations has been made. Their environmental dissemination is expected to be nonproportional to the PFCAs chain length. An understanding of the fundamental underlying reason for this novel physical property, chain length trend, would aid further investigators' interpretation of their environmental and toxicological observations. In this study we have utilized 19 F NMR techniques, such as, chemical shift, spin−lattice ( T 1 ), and spin−spin ( T 2 ) relaxation phenomena, coupling constants, and variable-temperature NMR to furnish a qualitative explanation of why increasing the carbon chain length causes unexpected intrinsic property changes within this group of chemicals. Results indicate that polyfluorinated chains adopt helical twist geometry unlike their hydrocarbon counterparts which exhibit a zigzag geometry. Variable-temperature 19 F NMR showed that chain rigidity within these molecules is also a function of the fluorocarbon chain length. There is a distinct change in geometry and rigidity of the acid chain between 8 and 10 carbon lengths. These unique geometric changes in this class of compound must be considered when assessing their dissemination in the environment, for example, in the case of environmental modeling.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.001 |
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".