Fluorescence studies of a series of monodisperse telechelic α,ω-dipyrenyl poly(<i>N</i>-isopropylacrylamide)s in ethanol and in water
Bibliographic record
Abstract
Steady-state and time-resolved fluorescence measurements were performed on solutions in ethanol and in water (23 °C) of a series of poly(N-isopropylacrylamide)s labeled with a pyrenyl group at each chain end (Py2-PNIPAM) and ranging in molecular weight (Mn) from 5 900 to 44 500 g·mol−1. Water and ethanol are of similar solvent quality towards the PNIPAM chain. The pyrene labels, in contrast, are soluble in ethanol but not in water. The efficiency of excimer formation for Py2-PNIPAM samples in ethanol decreased with increasing chain length, a trend typical of pyrene end-labeled polymers in good solvents. The ratio IE/IM, where IE is the Py excimer emission intensity and IM is the Py monomer emission intensity, scaled as Mn−1.4, where Mn is the number-average molecular weight of the sample. The kinetics of excimer formation were more complex for aqueous Py2-PNIPAM solutions, as a consequence of pyrene–pyrene association prior to excitation. The excimer time-dependent profiles exhibited significantly faster rise times, compared with the situation in ethanol, and they could not be fitted with the traditional Birks scheme. The results are discussed in the context of the solution properties of telechelic amphiphilic PNIPAMs and are compared with data gathered previously in studies of dipyrenyl end-labeled poly(ethylene oxides), the only other polymers soluble in water and organic solvents subjected to similar studies in the past.
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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 | 0.000 |
| 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 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".