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Record W2043829918 · doi:10.2202/1542-6580.1273

Alternate Co-Catalysts For Ziegler-Natta High Temperature Olefin Polymerization

2005· article· en· W2043829918 on OpenAlexafffund
Jesus Vela-Estrada

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2005
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsNova Chemicals (Canada)
FundersNOVA Chemicals
KeywordsNattaOlefin polymerizationCatalysisPolymerizationOlefin fiberMaterials scienceChemistryPolymer chemistryOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Typically a Ziegler-Natta catalyst formulation includes the use of alkyl aluminum compounds and this investigation involves the substitution of triethyl aluminum (TEAL) with n-BuLi. It was found that this lithium compound, used as first co-activator, produced polyethylene at rates high enough for solution polymerization technology. Catalyst activity and molecular weight data were collected from a lab-scale continuous polymerization reactor at 150, 170 and 190oC. A balance between n-BuLi and a second alkyl aluminum compound (AA-2), used as second co-activator in the catalyst formulation, enabled the catalyst to achieve a performance (catalyst activity and polymer molecular weight) similar to that obtained with TEAL. It is proposed that the optimum balance between these two compounds is related to the difference in the reducing power of n-BuLi and AA-2, and one of the chain transfer reactions is to AA-2.

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 categoriesInsufficient payload (model declined to judge)
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 score0.035
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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.

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

Citations1
Published2005
Admission routes2
Has abstractyes

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