Bibliographic record
Abstract
Reaction of the secocubane [Sn3(mu2-NHtBu)2(mu2-NtBu)(mu3-NtBu)] (1) with dibutylmagnesium produces the heterobimetallic cubane [Sn3Mg(mu3-NtBu)4] (4) which forms the monochalcogenide complexes of general formula [ESn3Mg(mu3-NtBu)4] (5a, E = Se; 5b, E = Te) upon reaction with elemental chalcogens in THF. By contrast, the reaction of the anionic lithiated cubane [Sn3Li(mu3-NtBu)4]- with the appropriate quantity of selenium or tellurium leads to the sequential chalcogenation of each of the three Sn(II) centres. Pure samples of the mono- or dichalcogenides are, however, best obtained by stoichiometric redistribution reactions of [Sn3Li(mu3-NtBu)4]- and the trichalcogenides [E3Sn3Li(mu3-NtBu)4]- (E = Se, Te). These reactions are conveniently monitored by using 119Sn NMR spectroscopy. The anion [Sn3Li(mu3-NtBu)4]- also acts as an effective chalcogen-transfer reagent in reactions of selenium with the neutral cubane [{Snmu3-N(dipp)}4] (8) (dipp = 2,6-diisopropylphenyl) to give the dimer [(thf)Sn{mu-N(dipp)}2Sn(mu-Se)2Sn{mu-N(dipp)}2Sn(thf)] (9), a transformation that results in cleavage of the Sn4N4 cubane into four-membered Sn2N2 rings. The X-ray structures of 4, 5a, 5b, [Sn3Li(thf)(mu3-NtBu)4(mu3-Se)(mu2-Li)(thf)]2 (6a), [TeSn3Li(mu3-NtBu)4][Li(thf)4] (6b), [Te2Sn3Li(mu3-NtBu)4][Li([12]crown-4)2] (7b'') and 9 are presented. The fluxional behaviour of cubic imidotin chalcogenides and the correlation between NMR coupling constants and tin-chalcogen bond lengths are also discussed.
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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) | 0.003 | 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".