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Record W2288574478 · doi:10.1088/0953-8984/28/3/035301

Localization of the electronic excitations in single-walled carbon nanotubes with embedded line impurities

2015· article· en· W2288574478 on OpenAlexafffund
P.G. Komorowski, M. G. Cottam

Bibliographic record

VenueJournal of Physics Condensed Matter · 2015
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZigzagCarbon nanotubeGrapheneNanotubeImpurityTridiagonal matrixMaterials scienceLattice (music)Condensed matter physicsElectronic structureMolecular physicsPhysicsNanotechnologyQuantum mechanicsEigenvalues and eigenvectorsGeometryMathematics

Abstract

fetched live from OpenAlex

A matrix operator formalism is used to study the excitations in long, single-walled carbon nanotubes with the dynamic electronic properties described by a tight-binding model where the interactions between atoms take place via nearest-neighbour hopping. Defects in the form of substitutional impurity atoms are introduced to study the localized electronic modes of the nanotube as well as the propagating modes of the pure (host) material. The impurities are assumed to have the form of one or more line defects parallel to the nanotube axis. Two geometric configurations are investigated corresponding to the longitudinal axis of the nanotube being parallel to either a zigzag or an armchair direction of the graphene lattice. A tridiagonal matrix technique is employed to solve the electronic operator equations that provide a description of the frequencies of the discrete modes of the system and their spatial amplitudes. Numerical examples are presented for different nanotube diameters and spatial configurations of the impurity lines.

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 score0.060
Threshold uncertainty score0.186

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 head0.023
GPT teacher head0.257
Teacher spread0.234 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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