Effect of viscosity and dielectric constant variation on fractional fluorescence quenching analysis of coumarin dye in binary solvent mixtures
Bibliographic record
Abstract
Photo physical properties of fluorescent organic compounds give an immense improved knowledge on characteristics of excited state that is beneficial to devise innovate molecules and understand their performance in particular applications. Coumarin derivatives have been extensively investigated in this regard. This article narrates steady state fluorescence quenching measurements of a coumarin derivative namely 3-hydroxy-3-[2-oxo-2-(3-oxo-3H-benzo[f]chromen-2-yl)-ethyl]-1,3-dihydro-indol-2-one (3HBCD) in a binary mixture of acetonitrile and 1,4-dioxane. Aniline is used as quencher. Fluorescence intensity is large in acetonitrile and decreases as the percentage of 1,4-dioxane in the solvent mixture increases. With modest quencher concentration a deviation towards the x axis is noticed in the Stern-Volmer (S-V) plots. This downward curvature is interpreted as due to the presence of 3HBCD in different conformers in the lowest energy level. Ground state intramolecular hydrogen bonding formation is observed due to the conformational changes in the solute. Figured estimations of various quenching parameters recommend that, while dynamic quenching prompts linearity in S-V plot at lower quencher concentration, increasing quenching efficiency with increasing medium viscosity suggests that reaction is not entirely controlled by material diffusion. Stern-Volmer constant increases with decreasing medium dielectric constant.
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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 | 0.001 |
| 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".