Preparation of an Active Neodymium Catalyst for Regioselective Butadiene<i>cis</i>-Polymerization Supported by a Dianionic Modification of the 2,6-Diiminopyridine Ligand
Bibliographic record
Abstract
Treatment of the 2,6-diiminopyridine ligand 2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N C(CH 3 )} 2 (C 5 H 3 N) with 2 equiv of Me 3 SiCH 2 Li afforded the corresponding {[2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)] 2 - ( 1 ) dianion via deprotonation of the two methyl groups attached to the two imine functions. Reaction of 1 with NdCl 3 (THF) 3 yielded {[2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)]Nd(THF)}(μ-Cl) 2 [Li(THF) 2 ]·0.5(hexane) ( 2a ), whose recrystallization from DME gave the corresponding ionic {[2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)]NdCl 2 (DME)}{Li(DME) 3 ]( 2b ). With the exception of the reaction with (allyl)MgBr, which proceeded readily with 2b to form the allyl derivative {[2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)]Nd(η 3 -C 3 H 5 )Br}{Li(DME) 3 } ( 3 ), compounds 2a, b are not suitable starting substrates for further alkylation reactions. A viable synthetic strategy for the preparation of alkyl derivatives of 2 consisted instead of the pretreatment of NdCl 3 (THF) 3 with RLi [R = Me 3 SiCH 2, CH 3 ] at low T followed by treatment with either the diimine ligand or 1 . According to this procedure, the terminally bound alkyl derivative [2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)]Nd[CH 2 Si (CH 3 ) 3 ](THF) ( 4 ) was prepared and subsequently crystallographically characterized. The same synthetic procedure with MeLi afforded {[2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)]Nd}(μ-CH 3 ) 2 [Li(THF) 2 ] ( 5 ) and {[2,6-{[2,6-(i-Pr) 2 C 6 H 3 ]N-C (CH 2 )} 2 (C 5 H 3 N)]Nd}(μ-Cl)(μ-X)[Li (THF) 2 ] ( 6 ) [X = Cl 53%, Me 47%] depending on the MeLi/Nd ratio. Both 5 and 6 as well as 2a are potent catalysts for the cis -polymerization of butadiene.
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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".