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Record W2316439472 · doi:10.1166/jnn.2003.185

Elastic Buckling of Multiwall Carbon Nanotubes under High Pressure

2003· article· en· W2316439472 on OpenAlexaff
Chen Wang, C. Q. Ru, A. Mioduchowski

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2003
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceCarbon nanotubeBucklingComposite materialShell (structure)StiffnessRADIUSBendingBending stiffnessNanotubeMechanical properties of carbon nanotubes

Abstract

fetched live from OpenAlex

This paper studies elastic buckling of individual multiwall carbon nanotubes under radial pressure. The analysis is based on a multiple-elastic-shell model in which each of the concentric tubes of a multiwall carbon nanotube is described as an individual elastic shell. According to their radius-to-thickness ratios, the multiwall carbon nanotubes discussed here are classified into three types: thin, thick, and (almost) solid. The critical pressure for elastic buckling is calculated for examples of all three types. It is found that a thin N-wall nanotube (defined by a radius-to-thickness ratio larger than 4) is approximately equivalent to a single-layer elastic shell whose effective bending stiffness and thickness are N times the effective bending stiffness and thickness of single-wall carbon nanotubes. Based on this result, an approximate method is suggested for replacing the problematic multiwall nanotube of many layers with a multilayer elastic shell of fewer layers. In particular, the critical pressure predicted by the present model is in good agreement with known experimental results.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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

Citations83
Published2003
Admission routes1
Has abstractyes

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