Multiple Hydrogen Bonds Promoted ESIPT and AIE‐active Chiral Salicylaldehyde Hydrazide
Bibliographic record
Abstract
Abstract The simpler, the better! A series of simple and highly fluorescent salicylaldehyde hydrazide molecules (41 samples) have been designed and prepared. Even though these soft materials contain a very small π‐conjugated system, they can go through multiple intramolecular and intermolecular hydrogen bonds promoted excited‐state intramolecular proton‐transfer (ESIPT) to display strong blue, green, yellow, and orange aggregation‐induced emission (AIE) with large Stokes shifts (up to 184 nm) and high fluorescence quantum yields (Ф up to 0.20). Unusual mechanochromic fluorescence enhancements are also found in some solid samples. Through coordination, hydrogen and halogen bonds, these flexible molecules can be used as Mg2+ (Ф up to 0.46) probes, universal anion (Ф up to 0.14) and unprotected amino acids (Ф up to 0.16) probes, and chiral diamine (enantiomeric selectivity and Ф up to 0.36 and 0.062, respectively) receptors. Combining their advantages of AIE and biocompatibility, these low cytotoxic dyes have potential application in living cell imaging. Furthermore, the effects of different functional groups on the molecule arrangement, ESIPT, AIE, probe, and chiral recognition properties are also examined, which provide a simple and bright paradigm for the design of multiple‐stimuli‐responsive smart materials.
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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) | 0.001 | 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".