Long Range Polymer Chain Dynamics of Highly Flexible Polysiloxane in Solution Probed by Pyrene Excimer Fluorescence
Bibliographic record
Abstract
A poly(dimethylsiloxane-co-(3-aminopropyl)methylsiloxane) polymer (PDMS with 20.3 mol % of (3-aminopropyl)methyl siloxane monomer) has been labeled randomly with 1-pyreneacetyl groups to generate a series of polysiloxanes (Py-PDMS) with pyrenyl contents ranging from 0.7 mol % to 5.2 mol % of the total number of structural units. The remainder of the amino groups were acetylated to avoid intra-chain quenching of the excited singlet states of pyrene via exciplex formation with free amino groups while allowing the formation of excimers to proceed. The fluorescence spectra and temporal decays of the Py-PDMS samples were acquired in tetrahydrofuran (THF), N,N-dimethylformamide (DMF), and dioxane. blob, the average rate constant for intra-chain pyrene excimer formation, was determined from the analysis of the fluorescence decays. blob was found to equal 1.16 (±0.13) × 109, 1.14 (±0.12) × 109, and 0.99 (±0.10) × 109 s−1 in THF, DMF, and dioxane, respectively, at room temperature. They are the largest values found to date for any polymeric backbone in these solvents. The qualitative relationship found here between blob and the chemical structures of the polymers indicates that the luminescence characteristics of randomly labeled polymers is a very useful method to probe the long range dynamics of chains of almost any polymer that is amenable to substitution by a lumophore.
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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 | 0.001 |
| 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".