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Record W2944075827 · doi:10.1002/marc.201900087

Synthesis of Diblock and Triblock Polymers from Cyclooctadiene and Norbornene Via ROMP in Miniemulsion

2019· article· en· W2944075827 on OpenAlexafffund
Olga Lidia Torres‐Rocha, Xiaowei Wu, Chunyang Zhu, Cathleen M. Crudden, Michael F. Cunningham

Bibliographic record

VenueMacromolecular Rapid Communications · 2019
Typearticle
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsROMPNorborneneMiniemulsionCopolymerMaterials sciencePolymer chemistryPolymerizationMonomerRing-opening metathesis polymerisationMetathesisPolymerDispersion polymerizationGrubbs' catalystComposite material

Abstract

fetched live from OpenAlex

The synthesis of diblock and triblock linear polyolefins via ring opening metathesis polymerization (ROMP) in an aqueous nanoparticle dispersion is presented. The different block polyolefins are synthesized from the cyclic olefins 1,5-cyclooctadiene and norbornene (NB), using a water-soluble TEGylated ruthenium alkylidene catalyst, yielding the structures PCOD-b-PNB, PNB-b-PCOD, and PCOD-b-PNB-b-PCOD. High monomer conversion (>90%), monitored by NMR, is achieved in relatively short times (≈1 h) for the polymerization of each block. The livingness of the system, essential to obtain block copolymers, is confirmed by gel permeation chromatography. Latex particles' size during the multiple steps range between 90 and 150 nm. The results demonstrate that it is possible to obtain nanoparticle latexes from ROMP-based monomers with block copolymer architectures, creating the opportunity to copolymerize olefins bearing different functional groups for the synthesis of new materials.

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 categoriesMeta-epidemiology (narrow)
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 score0.049
Threshold uncertainty score1.000

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 science0.0010.001
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 head0.008
GPT teacher head0.238
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

Citations2
Published2019
Admission routes2
Has abstractyes

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