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Record W2046136931 · doi:10.1002/marc.200500335

Surface‐Initiated Atom Transfer Radical Polymerization of Oligo(ethylene glycol) Methacrylate: Effect of Solvent on Graft Density

2005· article· en· W2046136931 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMacromolecular Rapid Communications · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEthylene glycolAtom-transfer radical-polymerizationPolymer chemistryMonomerChemistryMethacrylateMaterials sciencePolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Summary: Oligo(ethylene glycol) methacrylate (OEGMA) was grafted from silicon wafer surfaces by surface‐initiated atom transfer radical polymerization (ATRP) with Cu I Br/2,2′‐bipyridine (bpy) as a catalyst and various water/alcohol mixtures as solvents. The ellipsometric thickness of the poly(OEGMA) layer on the surface increased linearly with monomer conversion in solution. High graft densities were achieved in alcohols. The graft density of poly(OEGMA) in methanol was found to be 0.26 chains · nm −2 , which is 50% higher than that in water/methanol (30:70, v/v). The differences in graft density were correlated to the conformation of tethered poly(OEGMA) chains. Large poly(OEGMA) coils on the surface in the presence of water limited the access of initiation sites to the catalyst complex and monomer molecules. Development of poly(OEGMA) layer thickness on the silicon surface vs monomer conversion. image Development of poly(OEGMA) layer thickness on the silicon surface vs monomer conversion.

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.

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 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 score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.304
Teacher spread0.278 · 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