Synthesis of Fluorocarbon−Vinyl Acetate Copolymers in Supercritical Carbon Dioxide: Insight into Bulk Properties
Bibliographic record
Abstract
Tetrafluoroethylene (TFE), chlorotrifluoroethylene (CTFE), and vinylidene fluoride (VDF) were copolymerized with vinyl acetate (VAc) in supercritical fluid CO 2 by a free radical mechanism and without the use of a surfactant. A series of copolymers were synthesized with yields as high as 83% for TFE−VAc, 91% for CTFE−VAc, and 70% for VDF−VAc copolymers. Their weight-average molar masses, relative to polystyrene, were between 120 and 290 kg mol -1, and polydispersity was between 1.6 and 2.4. A range of compositions was prepared with the amount of fluorocarbon in the copolymer varying from 13 to 84 mol %, as determined by elemental analysis. Monomer reactivity ratios were estimated using the error-in-variable method to be r CTFE = 0.014 ± 0.05, r VAc = 0.44 ± 0.03; r TFE = −0.009 ± 0.06, r VAc = 0.95 ± 0.08; and r VDF = −0.4 ± 0.04, r VAc = 1.67 ± 0.6. Proton NMR was used to estimate copolymer composition, based on triad sequences. These data, together with the reactivity ratio data, indicate that the fluorocarbons cross-propagate with VAc and that VAc propagates randomly. All samples were characterized by DSC for T g with P(CTFE- co -VAc) having a T g between 42 and 53 °C, P(TFE- co -VAc) between 34 and 41 °C, and P(VDF- co -VAc) between 20 and 33 °C. Hydrolysis of vinyl acetate to vinyl alcohol (VA) in P(TFE- co -VAc) yielded terpolymers, P(TFE- co -VAc- co -VA), with >80% of VAc hydrolyzed to VA, thereby providing a reactive functional group for further modification. Interestingly, only a small decrease in molar mass was observed after the hydrolysis of vinyl acetate to vinyl alcohol, reflecting the loss of acetic acid and suggesting that these polymers are linear. The results presented herein are particularly interesting because no surfactant (or dispersion agent) was required for apparent solubility in CO 2 . The fluoropolymers prepared herein may find utility in coatings or paint applications.
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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".