Effect of Viscosity on Long-Range Polymer Chain Dynamics in Solution Studied with a Fluorescence Blob Model
Bibliographic record
Abstract
Fluorescence dynamic quenching experiments were conducted on three series of pyrene-labeled polystyrenes in nine organic solvents to evaluate the effect that viscosity has on their long-range polymer chain dynamics (LRPCD). Two series of polystyrenes were randomly labeled with the chromophore pyrene by either a short and rigid amide linker for the CoA-PS series or a long and flexible ether linker for the CoE-PS series. The third series was obtained by end-labeling five monodisperse polystyrenes with pyrene. The monomer and excimer fluorescence decays of all pyrene-labeled polymers were acquired and analyzed with the fluorescence blob model (FBM) for the randomly labeled polymers and the Birks’ scheme for the end-labeled polymers. The FBM analysis yielded the rate of excimer formation inside a blob, k blob, and the size of a blob, N blob . Birks’ scheme analysis yielded the rate of end-to-end cyclization, k cy, for a polystyrene chain length equal to N . After normalization, the products k blob × N blob for the randomly labeled polystyrenes and k cy × N for the end-labeled polystyrenes were found to yield identical trends, confirming that any pyrene-labeled polystyrene construct reports the same information on the LRPCD of the polystyrene backbone. The products k blob × N blob and k cy × N increased linearly with the inverse of viscosity, η −1, for η < 1 mPa·s as expected for a diffusion-controlled process. However, the trends obtained with k blob × N blob and k cy × N did not pass through the origin when η −1 → 0, suggesting that excimer formation is more efficient than expected in high-viscosity solvents. N blob was found to decrease with increasing viscosity. k blob did not change much with viscosity in all but the most viscous solvent. The product η × k blob was found to scale as ( N blob ) −1.73, where the exponent of −1.73 agrees with that expected from Flory’s theoretical predictions.
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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".