Evaluation of Phosphorescent Rhenium and Iridium Complexes in Polythionylphosphazene Films for Oxygen Sensor Applications
Bibliographic record
Abstract
Three metal complexes [Re(bpy)(CO) 3 (CN- t -Bu)]Cl ( 1 ) (where bpy = 2,2-bipyridine), Bu 4 N[Ir(ppy) 2 (CN) 2 ] ( 2 ), and Ir(ppy) 3 ( 3 ) (where ppy = 2-phenylpyridine and Bu 4 N = tetrabutylammonium cation) were evaluated as oxygen sensors in poly(( n- butylamino)thionylphosphazene) ( n BuPTP) matrixes. The phosphorescent dyes 2 and 3 exhibit long lifetimes and high quantum yields in degassed dichloromethane and toluene solutions and when dissolved in the polymer matrix. These two dyes exhibited exponential decays both in solution and in the polymer films, with somewhat longer lifetimes (for 2, τ 0 = 4.78 μs; for 3, τ 0 = 1.40 μs) in the polymer film. All three dyes gave linear Stern−Volmer plots, but 1 was rather sensitive to photodecomposition. The slopes of the Stern−Volmer plots for these dyes were compared to those measured previously for platinum octaethyl porphine (PtOEP) and ruthenium tris-diphenylphenanthroline chloride ([Ru(dpp) 3 ]Cl 2 . Attempts to explain the differences in slope using τ 0 as the sole scaling parameter were unsuccessful. To explain these results, we calculated the effective capture radius for quenching by oxygen, which was 1.7 nm for 2 and 2.7 nm for 3, relative to a value of 1.0 nm for PtOEP. Thus, dye 3 is 2.7 times more sensitive to quenching by oxygen than PtOEP and more than 5 times more sensitive than [Ru(dpp) 3 ]Cl 2 .
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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) | 0.001 | 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 | 0.001 | 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".