Fourier transform infrared studies of ionic interactions in perfluorinated acid copolymer blends
Bibliographic record
Abstract
Abstract Ionic interactions have been shown to enhance polymer–polymer miscibility in several highly dissimilar blend systems. In some cases, the miscibility is due to proton transfer from an acidic site on one polymer to a basic site on another, which leads to ion–ion interactions. Studies that have focused on the formation of ionomer blends from highly dissimilar materials, such as fluorocarbons and hydrocarbons or aromatics and aliphatics of widely differing glass transitions, have shown that in the absence of ionic interactions, these materials are immiscible. In this study, we have used Fourier transform infrared (FTIR) spectroscopy techniques, both qualitatively and semiquantitatively, to evaluate the extent of the proton‐transfer mechanism in the enhancement of miscibility in perfluorinated acid copolymer/poly(ethyl acrylate) blends. The perfluorinated acid copolymer contains sulfonic acid groups, whereas the poly(ethyl acrylate) has been modified by the introduction of various amounts of 4‐vinyl pyridine groups as comonomers in the polymer chains. The proton‐transfer mechanism in this case consists of the transfer of the proton on the sulfonic acid group to the nitrogen on the pyridine group, forming a pyridinium cation and a sulfonate anion pair. FTIR has been used to distinguish between the pyridine and pyridinium groups through their absorption bands at 1416 and 1642 cm−1, respectively. The relative intensities of these bands, as a function of the molar concentration of the pyridine comonomers in the blend, provides a direct quantitative indication of the extent of proton transfer occurring in the system. © 2003 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 41: 1814–1823, 2003
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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".