Is FeEt<sub>2</sub>(2,2‘-dipyridyl)<sub>2</sub> a Ziegler Catalyst for Polymerization of the Polar Monomer Acrylonitrile?
Bibliographic record
Abstract
This paper describes a reinvestigation into the putative role of a Ziegler process during polymerization of acrylonitrile by the compound FeEt 2 (2,2‘-dipyridyl) 2 . For this very efficient polymerization initiator, acrylonitrile coordination is reported to be a precondition for polymerization, seemingly more compatible with a Ziegler than with a conventional radical process. Consistent with the previous observations, we do indeed find evidence for a sequence of events in which acrylonitrile displaces a dipy ligand of FeEt 2 (dipy) 2, coordinating via the C C bond in η 2 -fashion rather than via the nitrogen. Subsequent steps involve β-hydrogen elimination from one of the ethyl groups to give a hydrido-ethylene-ethyl intermediate, followed by concomitant reductive elimination of ethane and hydride migration to the acrylonitrile to form a 2-cyanoethyliron compound. The latter then undergoes iron−carbon bond homolysis, the resulting cyanoethyl radical initiating a conventional but possibly living radical chain polymerization process. Investigated as possible ethylene polymerization catalysts are FeEt 2 (dipy) 2 “activated” with B(C 6 F 5 ) 3 and [Ph 3 C][B(C 6 F 5 ) 4 ], and both FeCl 2 (dipy) 2 and FeCl 2 (dmby) (dmby = 6,6‘-dimethyl-2,2‘-dipyridyl) activated with AlMe 3, AlEt 3, and MAO. Some of these related, potentially catalytic systems polymerize acrylonitrile, but none initiate ethylene polymerization, probably ruling out the possibility of a Ziegler process by this system for any monomer.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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 | 0.000 |
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".