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Record W2131470828 · doi:10.1017/s1727719100002823

Molecular Dynamics Simulation of Double-Walled Carbon Nanotube Vibrations: Comparison With Continuum Elastic Theories

2009· article· en· W2131470828 on OpenAlexaff
Sara Shayan-Amin, Hamed Dalir, Anooshiravan Farshidianfar

Bibliographic record

VenueJournal of Mechanics · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsMcGill University
Fundersnot available
KeywordsConcentricCarbon nanotubeMaterials scienceStiffnessVibrationTimoshenko beam theoryRotary inertiaMoment of inertiaClassical mechanicsInertiaPhysicsMechanicsComposite materialAcousticsGeometry

Abstract

fetched live from OpenAlex

ABSTRACT Double-walled carbon nanotubes (DWNTs) are expected to be useful as elements in improving conventional polymer-based fibers and films. An extensive molecular dynamics simulation and continuum analyses are carried out to estimate the influence of matrix stiffness and the intertube radial displacements on free vibration of an individual DWNT. The effects of nanotube length and chirality are also taken into account. The continuum analyses are based on both Euler-Bernoulli and Timoshenko beam theories which considers shear deformation and rotary inertia and for both concentric and non-concentric assumptions considering intertube radial displacements and the related internal degrees of freedom. New intertube resonant frequencies are calculated. Detailed results are demonstrated for the dependence of resonant frequencies on the matrix stiffness. The results indicate that internal radial displacement and surrounding matrix stiffness could substantially affect resonant frequencies especially for longer doublewalled carbon nanotubes of larger innermost radius at higher resonant frequencies, and thus the latter does not keep the otherwise concentric structure at ultrahigh frequencies.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.258
Teacher spread0.249 · 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

Citations16
Published2009
Admission routes1
Has abstractyes

Explore more

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