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Record W1973443046 · doi:10.1021/ma802147s

Supramolecular Functionalization of Single-Walled Carbon Nanotubes with Conjugated Polyelectrolytes and Their Patterning on Surfaces

2008· article· en· W1973443046 on OpenAlexaff
Fuyong Cheng, Patigul Imin, Sorin Lazar, Gianluigi A. Botton, Glynis de Silveira, Ognian Marinov, M. Jamal Deen, Alex Adronov

Bibliographic record

VenueMacromolecules · 2008
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
Fundersnot available
KeywordsPolyelectrolyteCarbon nanotubeSurface modificationPolymerPhenyleneMaterials scienceRaman spectroscopyNanotubeConjugated systemPolymer chemistryChemical engineeringSupramolecular chemistrySpectroscopyAbsorption spectroscopyNanotechnologyChemistryOrganic chemistryMolecule

Abstract

fetched live from OpenAlex

The interaction between single-walled carbon nanotubes and two anionic conjugated polyelectrolytes, poly[2,5-bis(3-sulfonatopropoxy)-1,4-phenylene- alt -1,4-phenylene) sodium salt and poly[2,5-bis(3-sulfonatopropoxy)-1,4-ethynylphenylene- alt -1,4-ethynylphenylene] sodium salt, was investigated. It was found that the supramolecular polymer−nanotube assembly occurred efficiently and produced stable complexes that could be purified from excess free polymer in solution. These complexes were characterized using absorption spectroscopy, fluorescence spectroscopy, Raman spectroscopy, and electron microscopy. It was further found that patterning of these polymer−nanotube complexes could be accomplished by utilizing electrostatic attraction with a prepatterned, cationically charged surface. Patterned features were found to be electrically conducting with a measured sheet resistance value of 0.68 ± 0.01 MΩ for features having a thickness on the order of several nanometers.

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 score0.001
Threshold uncertainty score0.439

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 head0.016
GPT teacher head0.205
Teacher spread0.190 · 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

Citations46
Published2008
Admission routes1
Has abstractyes

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