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Record W2056009746 · doi:10.1088/0953-8984/17/34/l02

Nondispersive and dispersive collective electronic modes in carbon nanotubes

2005· article· en· W2056009746 on OpenAlexaff
Ricardo Pérez, William Que

Bibliographic record

VenueJournal of Physics Condensed Matter · 2005
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCarbon nanotubeZigzagMaterials scienceOptical properties of carbon nanotubesElectron energy loss spectroscopyCarbon fibersSelective chemistry of single-walled nanotubesElectronChemical physicsTight bindingSpectroscopyElectronic structureNanotubeNanotechnologyMolecular physicsCondensed matter physicsPhysicsQuantum mechanicsComposite material

Abstract

fetched live from OpenAlex

We propose a new theoretical interpretation of the electron energy-loss spectroscopy results of Pichler {\it et al.} on bulk carbon nanotube samples. The experimentally found nondispersive modes have been attributed by Pichler {\it et al.} to interband excitations between localized states polarized perpendicular to the nanotube axis. This interpretation has been challenged by a theorist who attributed the modes to optical plasmons carrying nonzero angular momenta. We point out that both interpretations suffer from difficulties. From our theoretical results of the loss functions for individual carbon nanotubes based on a tight-binding model, we find that the nondispersive modes could be due to collective electronic modes in chiral carbon nanotubes, while the observed dispersive mode should be due to collective electronic modes in armchair and zigzag carbon nanotubes. Momentum-dependent electron energy-loss experiments on individual carbon nanotubes should be able to confirm or disprove this interpretation decisively.

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 score0.006
Threshold uncertainty score0.694

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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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

Citations7
Published2005
Admission routes1
Has abstractyes

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