Surrogates of 2,2′-Bipyridine Designed to Chelate Ag(I) and Create Metallotectons for Engineering Hydrogen-Bonded Crystals
Bibliographic record
Abstract
6-(Pyridin-2-yl)-1,3,5-triazine-2,4-diamine ( 1 ), 6-(pyrazin-2-yl)-1,3,5-triazine-2,4-diamine ( 2 ), and 6-(pyrimidin-2-yl)-1,3,5-triazine-2,4-diamine ( 3 ) incorporate two key structural features: (1) They resemble 2,2′-bipyridine and can therefore be expected to chelate suitable metals; and (2) they simultaneous incorporate diaminotriazinyl (DAT) groups, which engage in hydrogen bonding according to reliable patterns. As a result, ligands 1 − 3 are designed to react with metals to generate predictable structures held together by multiple coordinative interactions and hydrogen bonds. In particular, they react with salts of Ag(I) to yield cationic chelates analogous to those formed by 2,2′-bipyridine itself. As planned, DAT groups play a primary role in determining the observed structures, as demonstrated by their ability to engage in particularly favorable patterns of hydrogen bonding that require substantial deformation of the geometry of metallic coordination. An elegant hydrogen-bonded zipper, created spontaneously by combining simple ligand 3 with Ag(I), illustrates the power of qualitative approaches to crystal engineering based on a dual understanding of inorganic and organic chemistry.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".