Lactide Polymerization with Chiral β-Diketiminate Zinc Complexes
Bibliographic record
Abstract
N, N ′-Di( S -phenylethyl)-2-amino-4-iminopent-2-ene, S,S - nacnac CH(Me)Ph H, 1a, and N, N ′-dibenzyl-2-amino-4-iminopent-2-ene, nacnac Bn H, 1b, react with ZnEt 2 to form the corresponding nacnac ZnEt complexes 2a and 2b . Neither complex is reactive with 2-propanol or methyl lactate to produce the corresponding alkoxide complexes. In reactions with 2b, ligand redistribution occurs and nacnac Bn 2 Zn was obtained. Reaction of 1a and 1b with Zn(N(SiMe 3 ) 2 ) 2 yielded nacnac ZnN(SiMe 3 ) 2, 6a and 6b . From further reactions with 2-propanol nacnac ZnO i Pr, 7a and 7b, were obtained. Both complexes were catalytically active for polymerization of rac -lactide with apparent first-order rate constants of k app = 0.013−0.019 min −1 and 0.019−0.038 min −1 for 7a and 7b, respectively. Obtained polymers were highly heterotactic, with P r = 0.84−0.87 ( 7a ) and 0.65−0.71 ( 7b ). Analysis of remaining monomer after 75% conversion showed negligible ee and indicates that chiral 7a does not show enantioselectivity in rac -lactide polymerization. Complex 7a, but not 7b, catalyzes unselective transesterification of the polymer during and after polymerization. PLA microstructures in polymerizations with 7b were independent of temperature (23 or 0 °C) or monomer/catalyst ratio (100:1 to 400:1). However, slightly higher P r values were obtained in the presence of 10−100 equiv of MeCN or pyridine. Complexes nacnac Bn 2 Zn, 2b, 6b, and 7a were characterized by an X-ray diffraction study.
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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) | 0.001 | 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".