Characterizing the Quenching Process for Phosphorescent Dyes in Poly[((<i>n</i>-butylamino)thionyl)phosphazene] Films
Bibliographic record
Abstract
We compare the results of oxygen quenching experiments for four phosphorescent dyes [platinum octaethylporphyrin (PtOEP), platinum octaethylporphyrin ketone (PtOEPK), platinum tetrakis(pentafluorophenyl)porphyrin (PtTFPP), and Ru(dpp) 3 Cl 2 (dpp = 4,7-diphenyl-1,10-phenanthroline)] in a low-glass-transition-temperature polymer matrix [poly[(( n -butylamino)thionyl)phosphazene] (C 4 PATP).] The Pt dyes have exponential unquenched decays, but nonexponential decays in the presence of O 2 . These data fit well to a two-site model in which the dyes in the short lifetime environment are more readily quenched by oxygen. Ru(dpp) 3 Cl 2 in C 4 PATP has a nonexponential decay under all conditions and is much better described by a Gaussian distribution of decay rates with a common mean quenching rate. Time-scan experiments with PtOEP, PtTFPP, and Ru(dpp) 3 Cl 2 gave very similar values for the diffusion coefficient for oxygen in the polymer ( D O 2 = (3.7−4.0) × 10 -6 cm 2 s -1 ). For each of these three dyes, lifetimes and intensities gave identical Stern−Volmer plots. From the slopes of these plots one can calculate the permeability P O 2 and solubility S O 2 = P O 2 / D O 2 of oxygen in the matrix. In this calculation, one must assume a value (commonly taken to be 1.0 nm) for α R eff, the probability of quenching per encounter times the effective quenching radius of the dye. We find differences in calculated P O 2 values that can only be explained in terms different sensitivities of the dyes to quenching by oxygen.
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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 | 0.001 |
| 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) | 0.001 | 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".