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Record W2188739590

Determination of Non-local Elasticity Constants for the Torsional Buckling of Single-Wall Carbon Nanotubes Using Molecular Dynamics

2009· article· en· W2188739590 on OpenAlexaff
Farzad Khademolhosseini, R. K. N. D. Rajapakse, Alireza Nojeh

Bibliographic record

VenueTechConnect Briefs · 2009
Typearticle
Languageen
FieldMaterials Science
TopicNonlocal and gradient elasticity in micro/nano structures
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsZigzagBucklingCarbon nanotubeElasticity (physics)Molecular dynamicsMaterials scienceContinuum mechanicsWork (physics)Classical mechanicsMechanicsStructural engineeringNanotechnologyPhysicsComposite materialMathematicsThermodynamicsGeometryEngineeringQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

Recently, devices have been developed which use Carbon Nanotubes (CNTs) as torsional spring elements [1]. In order to define the range of applicability of CNTs in such devices, it is important to fully understand their torsional response, and to investigate failure modes such as the torsional buckling limit. Currently available continuum models are inaccurate as they are unable to account for the size effects that inevitably exist in such devices. In this work, a modified nonlocal continuum shell model for the torsional buckling of CNTs is proposed. This is done through modifying classical continuum models by incorporating basic concepts from nonlocal elasticity. Furthermore, molecular dynamics (MD) simulations are performed on a range of Zigzag and Armchair nanotubes with different diameters. It is easily seen that compared to classical models, the modified nonlocal model provides a much better fit to MD simulation results. Values of the nonlocal constants are calculated as 0.6 and 0.8 for Zigzag and Armchair CNTs respectively.

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 score0.277
Threshold uncertainty score0.557

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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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