A doubly protonated fluorescent dye for acid-base measurement
Bibliographic record
Abstract
Commonly employed pH-sensing dyes include coumarins, rhodamines, fluoresceins, and cyanines, each offering distinct spectral properties and tunability. The design of fluorescent acid-base sensors typically involves organic dye molecules with functional groups that can interact with OH − ions. Here, we demonstrate a distyrylbenzene-based fluorescent base-sensing dye (double-protonated carboxy-functionalized 1,4-bis(4-pyridyl-2-vinyl)benzene; c-P4VB⋅2HX, where X = Cl but can also be other anions) that provides a larger color change and a wider range of base concentrations due to the two-step deprotonation, compared to any previously-reported fluorescent base sensors. The c-P4VB⋅2HCl is orange luminescent in its doubly protonated state, which evolves through yellow, greenish, and finally electric blue in its unprotonated state, with fluorescence quantum efficiencies typically higher than 50 %. The c-P4VB⋅2HCl and its unprotonated form (c-P4VB) are highly soluble in moderately polar solvents like (short-chained) alcohols, dimethyl sulfoxide, and dimethyl formamide, and modestly soluble in water, due to the combination of pyridine groups and the caproic acid functional group. The reaction equilibria for the two deprotonation stages were investigated, the effect of the added OH – concentration and ambient temperature on the emission color and spectra were quantified, and biological imaging was finally demonstrated.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".