Tuning the Selectivity/Specificity of Fluorescent Metal Ion Sensors Based on N<sub>2</sub>S<sub>2</sub> Pyridine-Containing Macrocyclic Ligands by Changing the Fluorogenic Subunit: Spectrofluorimetric and Metal Ion Binding Studies
Bibliographic record
Abstract
Two new fluorescent chemosensors for metal ions have been synthesized and characterized, and their photophysical properties have been explored; they are the macrocycles 5-(2-quinolinylmethyl)-2,8-dithia-5-aza-2,6-pyridinophane (L5) and 5-(5-chloro-8-hydroxyquinolinylmethyl)-2,8-dithia-5-aza-2,6-pyridinophane (L6). Both systems have a pyridyl-thioether-containing 12-membered macrocycle as a binding site. The coordination properties of these two ligands toward CuII, ZnII, CdII, HgII, and PbII have been studied in MeCN/H2O (1:1 v/v) and MeCN solutions and in the solid state. The stoichiometry of the species formed at 25 degrees C have been determined from absorption, fluorescence, and potentiometric titrations. The complexes [CuL5](ClO4)(2).1/2MeCN, [ZnL5(H2O)](ClO4)2, [HgL5(MeCN)](ClO4)2, [PbL5(ClO4)2], [Cu3(5-Cl-8-HDQH-1)(L6H-1)2](ClO4)(3).7.5H2O (HDQ=hydroxyquinoline), and [Cu(L6)2](BF4)(2).2MeNO2 have also been characterized by X-ray crystallography. A specific CHEF-type response of L5 and L6 to the presence of ZnII and CdII, respectively, has been observed at about pH 7.0 in MeCN/H2O (1:1 v/v) solutions.
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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".