Steady‐State Model for Olefin Polymerization With a Two‐Site Vanadium Catalyst in a Continuous Stirred‐Tank Reactor
Bibliographic record
Abstract
Abstract Summary: In this study, a process for continuous EP(D)M production is examined and a mechanistic kinetic model is developed to explain the behavior exhibited by this vanadium‐catalyzed solution polymerization process. The catalyst system without promoter and without hydrogen, produces polymer with bimodal molecular weight distributions (MWDs), while the addition of catalyst promoter causes an order of magnitude increase in catalyst productivity and eliminates the higher‐MW component in the MWD. The addition of hydrogen also precludes bimodal MWDs, regardless of the presence of promoter. In all cases, the polymerization rate has a zero‐order rather than a first‐order response to monomer concentration. The zero‐order response of polymerization rate to monomer concentration is described using a mechanism of monomer coordination to form a stable complex prior to insertion. The bimodal MWDs at high monomer feeds (corresponding to low monomer conversion), in the absence of catalyst promoter and hydrogen, are explained by a two‐site type catalyst model in which both monomer insertion and the formation of the second‐site type occur after the monomer forms a stable coordinated complex with the first catalyst site type. The model reconciles the molecular weight development with these seldom‐discussed features of vanadium catalysis. Propylene acting as a coordinating ligand at a coordinatively unsaturated vanadium catalyst site (adapted from ref.[7]). magnified image Propylene acting as a coordinating ligand at a coordinatively unsaturated vanadium catalyst site (adapted from ref.[7]).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".