κ <sup>2</sup> <i>‐N</i> , <i>N</i> ′‐Sulfurdiimide and κ <sup>1</sup> ‐ <i>O</i> ‐Sulfinylamine Complexes of Tin(IV) Chloride
Bibliographic record
Abstract
Abstract A series of Sn(IV) chloride complexes with sulfur diimide (SDI, R‐NSN‐R) ligands are presented, including structural characterization of first‐in‐class complexes of bidentate diaryl‐SDIs, [SnCl 4 {κ 2 ‐ N , N ′‐S(NAr) 2 }] (Ar = 4‐X‐C 6 H 4 ‐), and an oxygen‐coordinated sulfinylamine, [SnCl 4 {κ 1 ‐ O ‐OSNPh} 2 ]. As part of the comprehensive experimental and DFT computational investigation, 119 Sn NMR analysis revealed a dynamic exchange equilibrium in acetonitrile between SDI ligands and solvent, providing insight into their complicated solution‐state chemical and electrochemical behavior. Voltammetric experiments show that, despite this dynamic equilibrium, the SDI ligands appear to suppress typical Sn(IV) reduction pathways. While tentative due to the complex behavior, this suggests that SDIs are functioning as redox‐active (RA) ligands. In conjunction with our previous systematic characterization of diaryl‐SDIs, these findings highlight their potential as an easily derivatized and highly redox‐tunable category of RA ligand and emphatically warrant further investigation.
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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) | 0.002 | 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".