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Record W2017526691 · doi:10.1021/ma9028129

Copper-Catalyzed Bimolecular Coupling of α,ω-Dibromide-Functionalized Poly(γ-caprolactone)

2010· article· en· W2017526691 on OpenAlexafffund
Xiaoze Jiang, Maria Vamvakaki, Ravin Narain

Bibliographic record

VenueMacromolecules · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolymer chemistryChemistryPolycaprolactoneCaprolactoneCatalysisPolymerizationCopperCoupling reactionMonomerDisproportionationBromideMolar mass distributionOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

α,ω-Dibromide-functionalized poly(γ-caprolactone) was synthesized by reacting α,ω-dihydroxy-terminated poly(γ-caprolactone) with an excess of 2-bromoisobutyryl bromide, leading to above 99% esterification. The resulting dibromide end-functionalized polycaprolactone (Br-PCL-Br) was found to “polymerize” in the presence of an excess of copper(I) chloride catalyst without the addition of vinyl monomers. Size exclusion chromatography (SEC) clearly revealed that the molecular weight of the “polymerized” macroinitiator shifts to higher values, and a broad peak was obtained with the main peak centered at a molecular weight which was twice that of the Br-PCL-Br precursor, suggesting that the main reaction is bimolecular coupling (∼80%), while a shoulder at molecular weights about 6−7 times that of the macroinitiator was also observed attributed to multimolecular coupling. The effects of the reaction temperature and the presence of copper(II) catalyst on the radical coupling reactions were also studied. A higher temperature or a lower copper(II) catalyst concentration favored the bimolecular as opposed to the multimolecular coupling, suggesting the possible occurrence of side reactions such as disproportionation and elimination, which hindered further coupling of the free chain ends.

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 score0.004
Threshold uncertainty score0.998

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.228
Teacher spread0.220 · 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

Citations17
Published2010
Admission routes2
Has abstractyes

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