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Record W4391346144 · doi:10.1021/acscatal.3c05570

Stereoblock vs Stereoblend: Orchestrating Competing Living Coordination Chain Transfer Polymerizations for the One-Pot Production of New Viscoelastic Grades of Poly(4-methyl-1-pentene)

2024· article· en· W4391346144 on OpenAlexaff
Danyon M. Fischbach, Charlotte M. Wentz, Saeid Mehdiabadi, João B. P. Soares, Lawrence R. Sita

Bibliographic record

VenueACS Catalysis · 2024
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversity of Alberta
FundersNational Science Foundation
KeywordsTacticityPolymerizationViscoelasticityPolymer chemistryCyclopentadienyl complexMaterials scienceChain transferMonomerCopolymerMolar massBrittlenessCatalysisPolymerChemistryOrganic chemistryComposite materialRadical polymerization

Abstract

fetched live from OpenAlex

By exerting control over two populations of coexisting cyclopentadienyl, amidinate (CPAM) group 4 metal active species that possess different stereoselectivities for chain growth propagation during the living coordinative chain transfer polymerization (LCCTP) of 4-methyl-1-pentene, controlled production of grades for poly(4-methyl-1-pentene) (PMP) materials that display a tunable range of viscoelastic properties can be achieved in “one-pot” fashion. Analytical and spectroscopic investigations reveal that these differences in viscoelastic properties are associated with formation of atactic/isotactic PMP stereoblends, rather than a stereoblock chain architecture. These results serve to establish the ability of low molar mass atactic PMP to function as an effective property modifier for commercially important isotactic PMP, which in its pure form is highly brittle with low tensile strength. The further outcome of these studies is extension of multistate LCCTP as a tool for expanding the range of accessible grades and properties of polyolefins that can be produced from the limited small set of industrially significant olefins.

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)0.001
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 score0.090
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.253
Teacher spread0.215 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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