Synthetic, structural, and computational investigations of N-alkyl benzo-2,1,3-selenadiazolium iodides and their supramolecular aggregates
Bibliographic record
Abstract
Despite their versatility, the application of telluradiazoles as supramolecular building blocks is considerably constrained by their sensitivity to moisture. Albeit more robust, their selenium analogues form weaker supramolecular interactions. These, however, are enhanced when one nitrogen atom is bonded to an alkyl group. Here we investigate general methods for the synthesis of such derivatives. Methyl, iso-propyl and tert-butyl benzo-2,1,3-selenadiazolium cations were prepared by direct alkylation or cyclo-condensation of the alkyl-phenylenediamine with selenous acid. While the former reaction only proceeds with the primary and tertiary alkyl iodides, the latter is very efficient. Difficulties reported in earlier literature are attributable to the formation of adducts of benzoselenadiazole with its alkylated cations and side reactions initiated by aerobic oxidation of iodide. However, the cations themselves are resilient to oxidation and stable in acidic to neutral aqueous medium. X-ray crystallography was used in the identification and characterization of the following compounds: [C6H4N2(R)Se](+)X(-), (R = CH(CH3)2, C(CH3)3; X = I(-), I3(-)], [C6H4N2(CH3)Se](+)I(-), and [C6H4N2Se][C6H4N2(CH3)Se]2I2. Formation of SeN secondary bonding interactions (chalcogen bonds) was only observed in the last structure as anion binding to selenium is a strong competitor. The relative strengths of those forces and the structural preferences they enforce were assessed with DFT-D3 calculations supplemented by AIM analysis of the electron density.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".