Temperature Sensing of Thiolate Addition by Phenolate Merocyanine Dyes: Importance of the Quinone Methide Resonance Structure
Bibliographic record
Abstract
Merocyanine (MC) dyes containing an aromatic donor vinyl linked to a cationic acceptor serve as chemosensors for analyte detection. Their electrophilicity permits anion detection through addition reactions that disrupt dye conjugation. Herein, we demonstrate the temperature influence on thiolate addition to MCs containing the N -methylbenzothiazolium (Btz) acceptor. The zwitterionic phenolate dye (PhOBtz) displays impressive temperature sensitivity to thiolate addition, with the brightly colored phenolate favored upon heating and the colorless thiolate adduct favored upon cooling. In contrast, MC dyes containing neutral donors (PhOMeBtz and PhNMe 2 Btz) display only moderate temperature sensitivity to thiolate capture and release. Extraction of thermodynamic parameters demonstrates a strong enthalpic driving force for thiolate addition to PhOBtz that is absent for PhOMeBtz and PhNMe 2 Btz. Variable temperature 1 H NMR studies demonstrate that PhOBtz adopts the para -quinone methide ( p -QM) resonance structure. Thus, thiolate addition to PhOBtz resembles 1,6-conjugate addition to p -QMs which is accompanied by a large increase in the π-stabilization energy upon adduct formation. Manipulation of PhOBtz electrophilicity by attaching chlorine substituents to the phenolate caused the thiolate adducts to dissipate over time for p -QM regeneration. Our work provides new design ideas for the utility of phenolate MC dyes, given that they are carriers of the p -QM electrophile.
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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) | 0.000 | 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) | 0.000 | 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 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".