Characterization by Fluorescence of the Distribution of Maleic Anhydride Grafted onto Ethylene−Propylene Copolymers
Bibliographic record
Abstract
An ethylene−propylene random copolymer (EP) was maleated according to two different procedures which were expected to yield different distributions of succinic anhydride (SAH) along the backbone. The two maleated EPs, referred to as EP-I and EP-II, were labeled with fluorescent dyes such as pyrene and/or naphthalene by reacting 1-pyrenemethylamine (or 1-naphthalenemethylamine) with the SAH moieties randomly attached along the EP copolymer. As a result, the distribution of dyes mimics that of the SAH moieties along the polymer backbone. The labeled EP copolymers thus obtained were studied by steady-state and time-resolved fluorescence techniques in solution. Hexane and tetrahydrofuran (THF) were chosen as solvents. Pyrene excimer formation and fluorescence resonance energy transfer measurements were performed to demonstrate that the SAH moieties are attached to EP-I in a less clustered manner than to EP-II. These conclusions were confirmed by analyzing the fluorescence decays of the pyrene-labeled EPs with a blob model developed in the laboratory. Viscosity measurements were performed on both pyrene-labeled EP copolymers to evaluate the effect that SAH clustering has on the solution properties of the polymers in hexane. The solution viscosity of the pyrene-labeled EP-I increases less steeply with polymer concentration than that of the pyrene-labeled EP-II. This effect is due to the higher SAH clustering observed with EP-II, which leads to a more efficient formation of interpolymeric aggregates held together via dipolar associations between the anhydride moieties. This study establishes that fluorescence can be applied to investigate the microstructure of maleated EP copolymers and that SAH clustering of a maleated EP copolymer can affect its properties in apolar solvents.
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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) | 0.000 | 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".