Temperature Dependence of Polymer Diffusion in Poly(vinyl acetate-<i>c</i><i>o</i>-dibutyl maleate) Latex Films
Bibliographic record
Abstract
We describe polymer diffusion and its temperature dependence in poly(vinyl acetate- co -dibutyl maleate) [P(VAc−DBM)] latex films prepared from 4:1 w/w ratio of VAc:DBM. Two sets of polymers were investigated: one set containing 50% gel (high- M ); the other set, with M w ≈ 250 000 ( M 250K ), free of a measurable gel content. Despite their similar chemical compositions, as determined by 1 H NMR, these two sets of samples exhibited different glass transition temperatures ( T g ). Latex particles were labeled with 9-methacryloxymethylphenanthrene as the donor dye and 2 ‘ -acryloxy-4 ‘ -methyl-4-( N, N -dimethylamino)benzophenone as the acceptor. Polymer diffusion was monitored by nonradiative energy transfer (ET), and apparent diffusion coefficients ( D app ) were calculated from the ET data using a simple diffusion model. These values increased with temperature and were characterized by an apparent activation energy ( E a ) of 37 ± 2 kcal/mol for the high- M polymer and 45 ± 2 kcal/mol for the M 250K sample. Rheology measurements at different fixed temperatures were carried out to follow the response of the dynamic moduli ( G ‘, G ‘ ‘ ) with respect to frequency ( ω ). A master curve based on the Williams−Landel−Ferry (WLF) equation could be constructed as a plot of shift factors vs 1/ T, and shift factors for D app for both sets of polymers as well as for the G ‘, G ‘ ‘ values fell on the same curve. Thus, the difference in E a values for the polymer diffusion can be ascribed to changes in the microscopic friction coefficient and the differences in T g of the two sets of samples.
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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 | 0.000 | 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 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".