Bridged Dinuclear Tripodal Tris(amido)phosphane Complexes of Titanium and Zirconium as Diligating Building Blocks for Organometallic Polymers
Bibliographic record
Abstract
Abstract Appropriate bridging ligands allow for the preparation of bimetallic titanium and zirconium precursors to transition‐metal‐containing polymers using the formally trianionic P(CH2NArR)3 ligand (where ArR = Ph, and 3,5‐Me2C6H3 for a and b, respectively). Lithiation of the known amidophosphane ligand precursors P(CH2NHArR)3 (1a,b) with 3 equiv. of nBuLi cleanly provided the diethyl ether adducts P(CH2NArR)3Li3(OEt2)1.5 (2a,b). The THF adduct P(CH2NPh)3Li3(THF)5 (2a‐THF) was characterized by X‐ray crystallography. Protonolysis reactions were used to prepare the mononuclear titanium complexes P(CH2NArR)3TiOC6H4tBu (4a,b) and dinuclear species [P(CH2NPh)3TiNMe2]2‐μ‐4,4′{O[3,3′,5,5′‐(C6H2Me2)2]O} (5a), [P(CH2NPh)3Ti]2(μ‐O) (6a), and P(CH2N‐3,5‐Me2C6H3)3Ti‐μ‐O‐Ti(NMe2)3 (7b), from P(CH2NArR)3TiNMe2. The reactions of 1a,b with Zr(NEt2)4 afforded metal complexes of the type P(CH2NArR)3ZrNEt2 (8a,b). The chloride complexes P(CH2NArR)3ZrCl(THF) (9a,b) were prepared by treatment of HNEt3Cl with 1 or 2. The complexes 9a,b reacted with cyclopentadienyllithium (C5H5Li) to produce P(CH2NArR)3ZrCp (10a,b), which were also prepared by the reactions of the lithium salts 2a,b with CpZrCl3. The dilithium salt of the fulvalene dianion (Li2C10H8) reacts with 9a,b to produce the dinuclear complexes trans‐[P(CH2NArR)3Zr]2(μ‐η5:η5‐C10H8) (10a,b), respectively. The facile preparation of transition‐metal‐containing polymers from the bridged dinuclear complexes was illustrated by the reaction of 6a with half an equivalent of [Rh(CO)2(μ‐Cl)]2, which precipitated polymeric Cl(CO)Rh[P(CH2NPh)3Ti]2(μ‐O). (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2008)
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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) | 0.003 | 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".