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Packed column reactor for continuous atom transfer radical polymerization: Methyl methacrylate polymerization using silica gel supported catalyst

2000· article· en· W2067472077 on OpenAlexafffund
Youqing Shen, Shiping Zhu, Robert Pelton

Bibliographic record

VenueMacromolecular Rapid Communications · 2000
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolymerizationMonomerCatalysisPolymerPolymer chemistryMolar mass distributionMethyl methacrylatePacked bedSilica gelMaterials scienceAtom-transfer radical-polymerizationChemical engineeringChemistryChromatographyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

A continuous column reactor packed with silica gel supported CuBr-HMTETA catalyst has been successfully developed for ATRP of MMA. The reactor had a good catalytic stability up to 100 h. The MMA conversion decreased with an increasing feeding flow rate. The polymerization kinetics was first order with respect to the monomer. The molecular weight increased linearly with conversion, demonstrating the living character. Possible flow back-mixing and polymer trapping in the pores of silica gel caused some broadening in the molecular weight distribution. This type of packed column reactor is believed to be a significant development for possible commercial exploitation of the ATRP process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.003

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 head0.022
GPT teacher head0.271
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations92
Published2000
Admission routes2
Has abstractyes

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