Direct Measure of the Local Concentration of Pyrenyl Groups in Pyrene-Labeled Dendrons Derived from the Rate of Fluorescence Collisional Quenching
Bibliographic record
Abstract
The model-free analysis (MFA) was applied to measure the average rate constant (<k>) for pyrene excimer formation (PEF) in a series of pyrene-labeled dendrons referred to as Pyx-G(N), where x (= 2N) is the number of pyrenyl labels born by a dendron of generation N ranging from 1 to 6. <k> was measured in four different solvents, namely tetrahydrofuran (THF), toluene, N,N-dimethylformamide (DMF), and dimethylsulfoxide (DMSO). <k> was found to increase linearly with increasing local pyrene concentration ([Py]loc), where [Py]loc had been determined mathematically for the Pyx-G(N) dendrons. The slope of each straight line changed with the nature of the solvent and represented kdiff, the bimolecular rate constant for PEF. kdiff depended on the solvent viscosity (η) and the probability (p) for PEF upon encounter between an excited and a ground-state pyrene. In a same solvent, kdiff for the Pyx-G(N) dendrons was about 360 ± 30 times smaller than kdiff obtained for ethyl 4-(1-pyrene)butyrate (PyBE), a pyrene model compound similar to the pyrene derivative used to label the dendrons. The massive decrease in kdiff observed for the Pyx-G(N) samples reflected the massive loss in mobility experienced by the pyrenyl labels after being covalently attached onto a macromolecule compared to freely diffusing PyBE. Interestingly, the kdiff values obtained for the Pyx-G(N) dendrons and the PyBE model compound followed similar trends as a function of solvent, indicating that the difference in behavior between the kdiff values obtained in different solvents were merely due to the changes in the η and p values between the solvents. Normalizing the <k> values obtained with the Pyx-G(N) dendrons by the kdiff values obtained for PyBE in the same solvents accounted for changes in η and p, resulting in a master curve upon plotting <k>/(fdiff × kdiff) as a function of [Py]loc, where fdiff was introduced to account for some pyrene aggregation in the higher generation dendron (Py64-G(6)). This result demonstrates that <k> represents a direct measure of [Py]loc in pyrene-labeled macromolecules.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".