Diamido-Ether Uranium(IV) Alkyl Complexes as Single-Component Ethylene Polymerization Catalysts
Bibliographic record
Abstract
The synthesis and characterization of two new uranium(IV) dialkyl complexes supported by two different diamido ether ligands are reported. The reaction of [{({2,6- i Pr 2 C 6 H 3 }N{CH 2 CH 2 }) 2 O}UCl 2 ] ([{ dipp NCOCN}UCl 2 ]) with 2 equiv of KCH 2 Ph generates the organoactinide [{ dipp NCOCN}U(CH 2 Ph) 2 ] ( 3 ), which shows an η 1 -, η 2 -benzyl arrangement of the alkyl ligands in the solid state. Reaction of [({ t BuN(SiMe 2 )} 2 O)UCl 2 ] ([{ t Bu NON}UCl 2 ]) with 2 equiv of LiCH(SiMe 3 ) 2 yields the alkyl-bridged uranium dimer [{ t Bu NON}U{CH(SiMe 3 )(SiMe 2 CH 2 )}] 2 ( 4 ), which forms via γ C−H activation of the CH(SiMe 3 ) 2 substituent. Reaction of 3 and 4 as well as previously reported [{ t Bu NON}U(CH 2 SiMe 3 ) 2 ] ( 1 ) and [{ dipp NCOCN}U(CH 2 SiMe 3 ) 2 ] ( 2 ) with 1 atm of ethylene under ambient conditions produced high molecular weight polymers, demonstrating that diamido ether actinide complexes can act as ethylene polymerization catalysts; activities up to 560 g/mol·h·atm using 1 were observed. Reaction of 1 and 2 with 1 atm of ethylene and 1 equiv of B(C 6 F 5 ) 3 demonstrated a 4-fold decrease in activity of the catalyst. Reaction of 1 or 2 with an excess of MMAO or Et 2 AlCl did not yield any polymer formation upon the addition of ethylene. After reaction of 1 with Et 2 AlCl, removal of volatiles in vacuo yielded a dark red liquid that, upon standing, formed green crystals of [{ t Bu NON}U{(μ-Cl) 2 AlEt 2 } 2 ] ( 5 ), indicating a route for catalyst deactivation by aluminum-based cocatalysts.
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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) | 0.001 | 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".