Synthesis and Properties of Hypercoordinate Stannanes and Polystannanes
Bibliographic record
Abstract
Asymmetric tetraorganotin (IV) compounds containing either a flexible propyl alcohol ligand (10) or a semi-flexible ethyl 2-pyridyl ligand (11) were synthesized in good yields via select hydrostannylation reactions. The triphenyl derivatives were converted in good yields to their dihalide stannane intermediates (6, 7), respectively, by mild sequential chlorination with HCl or by reaction with Br2. The dihalides were converted to reactive dihydride monomers (8, 9) by a reaction with LiAlH4 or NaBH4 in good yields. All stannane intermediates and monomers were fully characterized by NMR (1H, 13C, 119Sn) spectroscopy and high-resolution mass spectrometry. DFT calculations were also performed on the ethyl 2-pyridyl stannane intermediates 2 and 7, which revealed optimized structure geometry and electronic energies. From the three methods that were used, M05-2X-GD3 showed the lowest mean sum of squared distances (MSSD) value and the lowest electronic energies of the hypercoordinate structures. Polymerization of the corresponding dihydrides in the presence of both early and late transition metal catalysts produced moderate molecular weight polymers 10a and 11a. Compound 10a was cast onto a transparent film for the first time and was additionally coated on a PET film. While the cast film on PET showed good flexibility, an initial evaluation of its electronic properties using a 4-probe conductivity device revealed no intrinsic semi-conductivity. Optimization of the polymerization of 10a involved a catalyst screening, using alternative dehydrocoupling catalysts. A new ethyl 2- pyridyl containing polystannane 11a was synthesized with a Mw of 11,200 Da using RhCl(PPh3)3, and 119Sn NMR revealed the presence of both 4- and 5-coordinate Sn centers randomly distributed along the backbone.
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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".