Effect of Side-Chain Length on the Polymer Chain Dynamics of Poly(alkyl methacrylate)s in Solution
Bibliographic record
Abstract
Eight series of poly(alkyl methacrylate)s bearing different side chains and one series of poly(methyl acrylate) were randomly labeled with pyrene, and their ability to form pyrene excimer was characterized quantitatively by steady-state and time-resolved fluorescence to demonstrate that such measurements provide a quantitative measure of polymer chain dynamics (PCD) in solution. Each series of pyrene-labeled polymer showed increased excimer formation with increasing pyrene content, but the increase was more pronounced for the polymers known to be more flexible based on their reported glass transition temperature ( T g ). In the case of the poly(alkyl methacrylate)s with a linear side chain, a shorter side chain resulted in increased excimer formation. Replacing a linear side chain with a more rigid one containing the same number of carbon atoms resulted in decreased mobility of the polymer. Fluorescence Blob Model (FBM) analysis of the fluorescence decays provided a more accurate representation of those pyrenes that formed excimer by diffusion and thus reflected PCD more precisely. Global FBM analysis of the pyrene monomer and excimer fluorescence decays yielded the blob size N blob and the product k blob × N blob which reflects PCD. For each series, both N blob and k blob × N blob remained constant with pyrene content. Their average value ⟨ N blob ⟩ and ⟨ k blob × N blob ⟩ decreased substantially with increasing side-chain length, addition of the α-methyl substituent to poly(methyl acrylate) to yield poly(methyl methacrylate), or increased rigidity of the side chain, demonstrating that an increase in bulkiness or stiffening of the side- or main chain is associated with a pronounced decrease in chain mobility. These experiments are the first to demonstrate that pyrene excimer formation can be used to characterize quantitatively PCD in solution in the same manner that T g is being used to characterize PCD in the bulk.
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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".