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Record W2042336814 · doi:10.1021/ma001699w

Effect of Ligand Spacer on Silica Gel Supported Atom Transfer Radical Polymerization of Methyl Methacrylate

2001· article· en· W2042336814 on OpenAlexaff
Youqing Shen, Shiping Zhu, Robert Pelton

Bibliographic record

VenueMacromolecules · 2001
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPolymer chemistryAtom-transfer radical-polymerizationPolymerizationChemistryMethyl methacrylateDispersityRadical polymerizationChain transferEthylene glycolLiving polymerizationLiving free-radical polymerizationPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Silica gels grafted with tetraethyldiethylenetriamine (TEDETA) and di(2-picolyl)amine (DiPA) via poly(ethylene glycol) (PEG) spacers of different chain lengths were synthesized and used as CuBr support for the atom transfer radical polymerization (ATRP) of methyl methacrylate (MMA). The spacer length strongly affected the polymerization rate and polymer molecular weight control. Catalyzed by CuBr immobilized on the silica gel, the MMA polymerization rate increased with spacer length in the order of PEG 1 < PEG 10 < PEG 3 (the subscript is the number of the EG units). Copper bromide supported via three-unit PEG (SG-PEG 3 -TEDETA and SG-PEG 3 -DiPA) controlled the MMA polymerization best, producing PMMA with controlled molecular weights (initiator efficiency ca. 75%) and low polydispersities ( M w / M n ∼ 1.2−1.4). The recycled catalysts had activities similar to the fresh ones at the late stage of polymerization with improved initiator efficiencies. The PMMA- block -poly(2-( N,N -dimethylamino)ethyl methacrylate) with well-controlled molecular weight and low polydispersity was also synthesized by this support system.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.001

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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

Citations66
Published2001
Admission routes1
Has abstractyes

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