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Record W2064230095 · doi:10.1002/pola.21308

Solubilizing single‐walled carbon nanotubes with pyrene‐functionalized block copolymers

2006· article· en· W2064230095 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.

Bibliographic record

VenueJournal of Polymer Science Part A Polymer Chemistry · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
Fundersnot available
KeywordsCarbon nanotubePyreneCopolymerPolymerNanotubePolymer chemistryMaterials scienceSolubilityChemical engineeringHildebrand solubility parameterNon-covalent interactionsChemistryNanotechnologyOrganic chemistryMoleculeComposite materialHydrogen bond

Abstract

fetched live from OpenAlex

Abstract The effect of pyrene distribution within pyrene‐functionalized random and block copolymers on noncovalent polymer/single‐walled carbon nanotube (SWNT) interactions was investigated. The block copolymers served as superior solubilizing agents in comparison with the random copolymers. Also, increasing the pyrene content within a polymer, while a constant molecular weight was maintained, improved SWNT solubility and therefore had to result in stronger polymer–nanotube interactions. However, increasing the length of the pyrene‐containing block diminished nanotube solubility, likely because of a lower number of polymer chains that were capable of binding to the nanotube surface. Atomic force microscopy and transmission electron microscopy indicated that the polymer–SWNT interactions were capable of partially debundling the nanotubes into individual solvated structures. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 1941–1951, 2006

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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.220
Teacher spread0.212 · 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