Impact of a Non-Phthalate Based Internal Donor on the Polymerization Behaviour of a Novel Ziegler - Natta Catalyst
Bibliographic record
Abstract
With a global share of nearly 20% in the thermoplastics market and an annual growth rate of more than 4%, polypropylene plays a special role in the group of so-called "commodity polymers". One key reason for this success is the flexibility in terms of composition and property design. The major part of the industrial production of polypropylene is based on MgCl2-supported Ziegler-Natta catalysts. [1] Starting from the third generation Ziegler-Natta catalysts, an internal electron donor has been widely used to boost the performance of the catalyst; it does not only influence the activity, but also controls the molecular structure, like the isotacticity and comonomer insertion in case a second monomer is applied. [2-3] Actually, the electron donor is one of key factors to classify the generation of Ziegler-Natta catalysts.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".