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Record W1976152790 · doi:10.1021/ja037564y

Polymerization from the Surface of Single-Walled Carbon Nanotubes − Preparation and Characterization of Nanocomposites

2003· article· en· W1976152790 on OpenAlexafffund
Zhaoling Yao, Nadi Braidy, Gianluigi A. Botton, Alex Adronov

Bibliographic record

VenueJournal of the American Chemical Society · 2003
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbon nanotubeChemistryPolymer chemistryPolymerizationMethyl methacrylateAtom-transfer radical-polymerizationAcrylatePolymerMethacrylateNanocompositeChemical engineeringOrganic chemistryCopolymer

Abstract

fetched live from OpenAlex

Single-walled carbon nanotubes were functionalized along their sidewalls with phenol groups using the 1,3-dipolar cycloaddition reaction. These phenols could be further derivatized with 2-bromoisobutyryl bromide, resulting in the attachment of atom transfer radical polymerization initiators to the sidewalls of the nanotubes. These initiators were found to be active in the polymerization of methyl methacrylate and tert-butyl acrylate from the surface of the nanotubes. However, the polymerizations were not controlled, leading to the production of high molecular weight polymers with relatively large polydispersities. The resulting polymerized nanotubes were analyzed by IR, Raman spectroscopy, DSC, TEM, and AFM. The nanotubes functionalized with poly(methyl methacrylate) were found to be insoluble, while those functionalized with poly(tert-butyl acrylate) were soluble in a variety of organic solvents. The tert-butyl groups of these appended polymers could also be removed to produce nanotubes functionalized with poly(acrylic acid), resulting in structures that are soluble in aqueous solutions.

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 score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.229
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 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

Citations443
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicCarbon Nanotubes in CompositesFrench-language works237,207