Water-Based Oxygen-Sensor Films
Bibliographic record
Abstract
The luminescent cyclometalated iridium complex [Ir(fppy)(2)(t-Bu-iCN)(2)]CF(3)SO(3), 1 (fppy = 4-(2-pyridyl)benzaldehyde, and t-Bu-iCN = tert-butyl isocyanide), was synthesized and characterized by X-ray crystallography and (1)H NMR, absorption, and emission spectroscopies. Complex 1 was quantitatively bound to the water-soluble amine-functionalized polymer Silamine D208-EDA by reductive amination, to produce 2. The quantum yield of emission and excited state lifetime of 2 (varphi(em) = 0.23 and tau = 20.6 mus) are comparable to that of the model complex [Ir(tpy)(2)(t-Bu-iCN)(2)]CF(3)SO(3), 3 (tpy = 2-(p- tolyl) pyridine) with varphi(em) = 0.28 and tau = 35.6 mus. Aqueous blends of 2 with Silamine and colloidal microcrystalline cellulose (MC) were used to prepare oxygen-sensor films. Oxygen sensitivities of these films were determined as a function of Silamine:MC ratio and obeyed Stern-Volmer kinetics. The optimum oxygen-sensor film composition was 2 in 1:1 Silamine:MC, which had an oxygen sensitivity of 0.502 over an atmospheric pressure range of 0.007-45 psi. Temperature sensitivity (percentage loss of intensity per degrees C) of this film was determined to be -1.1 and -1.4% degrees C(-1) at vacuum and 1 bar atmospheric pressure, respectively. These results were compared to those of films incorporating dispersions of 1 and 3. Luminescence microscopy of 9:1, 1:1, and 1:5 Silamine:MC films of 2 show that the charged iridium complex in 2 associates with the surface of MC and lifetime measurements of these films show an increase in lifetime with increasing MC fraction. The optimum quenching sensitivity observed for the 1:1 Silamine:MC film suggests that the diffusion of oxygen must decrease with increasing fraction of MC and thereby decrease oxygen sensitivity. These novel materials offer an environmentally friendly alternative to the preparation of oxygen-sensor films.
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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) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".