Synthesis and Characterization of Readily Modified Poly(aryl)(alkoxy)stannanes by use of Hypercoordinated Sn Monomers
Bibliographic record
Abstract
Abstract The synthesis and solid‐state molecular structures of two dichlorido(aryl)(alkyl) tin compounds, 5 and 8, both key intermediates to tunable polystannane architectures, are reported. The materials were further investigated by single‐crystal XRD and a DFT analysis of their preferential “open and closed” geometries. Conversion of said compounds to their dihydride analogues was undertaken, followed by their application as monomers for polystannane polymer synthesis. The properties of two asymmetrical polystannanes prepared by transition‐metal‐catalyzed dehydropolymerization of dihydrido(aryl)alkylstannanes (6 and 9) were investigated. The first product was the structurally simple, modest molecular weight, semi‐crystalline light‐ and moisture‐stable polystannane 10 with NMR (119Sn) evidence of prominent Sn←O hypercoordination along the polymer backbone. The second was the lower molecular weight, tosylated four‐coordinate polystannane 11 with no evidence of hypercoordination. Differential scanning calorimetry (DSC) of polymer 10 revealed a reversible semi‐crystalline nature, whereas an amorphous character was detected for polymer 11. Polystannane 10 was also found to be exceptionally stable to both moisture and light (>6 months) and a promising candidate for the design of readily modified (i.e., tunable) polystannane materials.
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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".