Cooperative effect through different bridges in nickel catalysts for polymerization of ethylene
Bibliographic record
Abstract
A series of mononuclear (M 1 and M 2 ) and dinuclear (C 1 –C 6 ) Ni α‐diimine catalysts activated by modified methylaluminoxane were used in polymerization of ethylene. Catalyst C 2 bearing the optimum bulkiness showed the highest activity (1.6 × 10 6 g PE (mol Ni) −1 h −1 ) and the lowest short‐chain branching (32.5/1000 C) in comparison to the dinuclear and mononuclear analogues. Although the mononuclear catalysts M 1 and M 2 polymerized ethylene to a branched amorphous polymer, the dinuclear catalysts led to different branched semicrystalline polyethylenes. Homogeneity and heterogeneity in the microstructure of the polyethylene samples was observed. Different trends for each catalyst were assigned to syn and anti stereoisomers. In addition, thermal behavior of the samples in the successive self‐nucleation and annealing technique exhibited different orders and intensities from methylene sequences and lamellae thickness in respect of each stereoisomer behavior. Higher selectivity of hexyl branches obtained by catalyst C 2 showed a cooperative effect between the centers. The results also revealed that for catalysts C 5 and C 6 , selectivity of methyl branches led to very high endotherms and crystalline sequences with melting temperatures higher than that of 100% crystalline polyethylene indicating ethylene/propylene copolymer analogues. For catalysts C 3 and C 4 , more vinyl end groups were a result of the long distance between the Ni centers. Kinetic profiles of polymerization along with a computational study of the precatalysts and catalysts demonstrated that there is a direct relation between rate constant, energy interval of catalyst and precatalyst, and interaction energy of Et···methyl cationic active center (Et···MCC or π–Comp.). Based on this, narrow energy interval (activation energy) of precatalyst and catalyst leads to fast and higher activation rate (catalyst M 2 ), and strong interaction of ethylene and catalyst leads to high monomer uptake and productivity (catalyst C 2 ). Moreover, theoretical parameters including electron affinity, Mulliken charge on Ni, chemical potential and hardness, and global electrophilicity showed optimum values for C 2 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.011 | 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 teacher head, 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".