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Record W2008390730 · doi:10.1002/masy.200951102

Simulation of Propylene Polymerization in Industrial Reactors Using Ziegler‐Natta Catalysts in the Presence of Electron Donors

2009· article· en· W2008390730 on OpenAlexaff
Ahmad Alshaiban, João B. P. Soares

Bibliographic record

VenueMacromolecular Symposia · 2009
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNattaTacticityPolypropyleneCatalysisPolymerizationElectron donorZiegler–Natta catalystMetalloceneMaterials sciencePolymer sciencePolymer chemistryOrganic chemistryChemical engineeringChemistryComposite materialEngineeringPolymer

Abstract

fetched live from OpenAlex

Abstract Heterogeneous Ziegler‐Natta catalysts are still the most important catalysts for the industrial production of polyolefins, despite the discovery of high‐activity metallocene systems in the eighties. Despite of their huge commercial importance, several aspects of Ziegler‐Natta catalysts are still poorly understood from both qualitative and quantitative points of view. Especially for polypropylene, a very important factor controlling product quality is the effect of the electron donor used to modify the catalyst. In this manuscript we present, for the first time, a quantitative mathematical model that describes the effect of electron donors on the tacticity of polypropylene made with multiple‐site type catalysts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.259
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2009
Admission routes1
Has abstractyes

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