Linear free energy relationship based estimates for the congener specific relative reductive defluorination rates of perfluorinated alkyl compounds
Bibliographic record
Abstract
Linear free energy relationships (LFERs) were developed to estimate the congener specific relative rates of reductive defluorination for a suite of perfluorinated compound (PFC) classes. The LFERs were based on the semiempirically calculated lowest unoccupied molecular orbital energy (ELUMO) using gas and aqueous phase computations with the PM6 and RM1 methods. PFC classes in the modeling effort included the C1 through C8 perfluoroalkyl sulfonates (PFSAs), carboxylates (PFCAs), sulfonyl fluorides (PFSFs), sulfonamides and their derivatives (SAs), and the perfluorotelomer alcohols (PFTAls), olefins (PFTOls), and acids (PFTAcs). Gas and aqueous phase calculations using the PM6 method predict that branched PFSA, PFCA, and PFSF congeners will have more rapid reductive defluorination kinetics than their linear counterparts. The RM1 method predicts that only PFSFs will display intrahomologue dependent branching effects. For the PFSAs and PFSFs, both the PM6 and RM1 methods predict no significant difference in mean rates of reductive defluorination between the homologue groups. For the PFCAs, the PM6 method suggests no significant difference in inter-homologue mean rates of reductive defluorination, whereas the RM1 method predicts a significant increase with a lengthening perfluoroalkyl chain. All approaches used suggest that the intrahomologue variability in reduction rates increases with increasing chain length for PFSAs, PFCAs, and PFSFs, implying that the larger homologue groups in these classes will see a more rapid linearization of the congener profiles under reducing conditions than their lower homologue counterparts. Chain length has a negligible effect on the estimated rates of SA reductive defluorination, but a significant role for the fluorotelomer derivatives. Ratios of rates between the C8:C1 straight chain telomeric congeners are expected to range up to 200-fold depending on the computational combination. The kinetics for reductively defluorinating PFC starting materials will likely be 2 to 3 orders of magnitude more rapid than for most of the partially defluorinated degradation products. Significant quantities of partially defluorinated PFCs are thus expected to be observed under steady state conditions during reductive treatment processes, leading to a potentially significant reservoir of these compounds residing in reducing environmental and biological systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".