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Record W2072991751 · doi:10.1039/c1py00023c

The effect of molecular weight on the supramolecular interaction between a conjugated polymer and single-walled carbon nanotubes

2011· article· en· W2072991751 on OpenAlexafffund
Patigul Imin, Fuyong Cheng, Alex Adronov

Bibliographic record

VenuePolymer Chemistry · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsSteacie Institute for Molecular SciencesMcMaster UniversityBrockhouse Institute for Materials Research
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbon nanotubePolymerTetrahydrofuranConjugated systemGel permeation chromatographySolubilityAbsorption (acoustics)Materials sciencePolymer chemistryChemical engineeringChemistryAnalytical Chemistry (journal)Organic chemistryNanotechnologySolvent

Abstract

fetched live from OpenAlex

The synthesis and fractionation of poly[2,7-(9,9-dioctylfluorene)-alt-2,5-(3-dodecylthiophene)] resulted in the isolation of eight different molecular weight (Mw) samples ranging from Mn of 5 to 85 kg mol−1. These individual polymer samples were fully characterized by Gel Permeation Chromatography, Nuclear Magnetic Resonance, as well as absorption and fluorescence spectroscopy. Each sample was separately mixed and ultrasonicated with single-walled carbon nanotubes (SWNTs) in tetrahydrofuran, and the nanotube concentration within the resulting solutions was measured. It was found that the solubility of the polymer–SWNT complexes strongly depends on the Mw of the conjugated polymer, with a maximum concentration reached when Mw ranged between 10 and 35 kg mol−1. Higher and lower Mws resulted in substantially reduced nanotube concentrations.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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 teacher head, 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

Citations38
Published2011
Admission routes2
Has abstractyes

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