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Record W2094808474 · doi:10.1063/1.2179970

Vibration of a double-walled carbon nanotube aroused by nonlinear intertube van der Waals forces

2006· article· en· W2094808474 on OpenAlexaff
Kun Xu, Xin Guo, C. Q. Ru

Bibliographic record

VenueJournal of Applied Physics · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
Keywordsvan der Waals forceVibrationCarbon nanotubeDeflection (physics)CoaxialNonlinear systemAmplitudeHarmonic balanceFundamental frequencyClassical mechanicsMaterials scienceMechanicsPhysicsNanotechnologyOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

Vibration of a double-walled carbon nanotube aroused by nonlinear interlayer van der Waals (vdW) forces is studied. The interlayer vdW forces as a nonlinear function are described by the interlayer spacing. The inner and outer carbon nanotubes are modeled as two individual elastic beams. Detailed results are demonstrated for double-walled carbon nanotubes (DWCNTs) with an aspect ratios of 10 and 20, based on the simply supported, fixed, or free end conditions, respectively. Harmonic balance method is used to analyze the relation between the amplitudes of deflection and the frequencies of coaxial and noncoaxial free vibrations. Our results indicate that the nonlinear factors of vdW forces have little effect on the coaxial free vibration, and that the deflection amplitudes increase rapidly with the increasing frequency, which are almost the same with those of the linear free vibration. On the other hand, the nonlinear factors of vdW forces have a great effect on noncoaxial free vibration. The relation between the deflection amplitudes and the frequencies shows nonlinear trend, which indicates that the aspect ratio and end condition almost have no affect on the noncoaxial amplitudes of DWCNTs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.232
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations109
Published2006
Admission routes1
Has abstractyes

Explore more

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