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Record W4399116647 · doi:10.1002/sia.7336

Studying quantum effects of fine scaling on the buckling behavior of CNTs under torsional loading using the density functional theory and molecular mechanics approach

2024· article· en· W4399116647 on OpenAlexaff
M. Mirnezhad, R. Ansari, Seyed Reza Falahatgar, P. Aghdasi

Bibliographic record

VenueSurface and Interface Analysis · 2024
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBucklingZigzagCarbon nanotubeMaterials scienceNanotubeScalingNanotechnologyQuantumBridging (networking)Continuum mechanicsComposite materialMechanicsPhysicsGeometryQuantum mechanicsMathematicsComputer science

Abstract

fetched live from OpenAlex

In this study, we introduce a comprehensive investigation into the buckling behavior of carbon nanotubes (CNTs) using a combined approach of quantum mechanics and molecular mechanics methods. A novel aspect of our research lies in the exploration of the quantum effects of fine scaling on the buckling behavior of finite‐length nanotubes across various dimensions and chiralities. Specifically, we analyze the critical buckling strain variations in CNTs with distinct lengths, diameters, and chiralities, revealing pronounced differences influenced by atomic arrangement and the type of structure used in nanotube construction. Our findings elucidate that at smaller dimensions, nanotubes exhibit a higher critical buckling strain than other chiralities, while zigzag atomic arrangements demonstrate greater resistance to torsional loading at larger diameters. Additionally, we compare the buckling behavior of nanotubes obtained by wrapping armchair and zigzag nanosheets, highlighting differential resistance trends. This research not only underscores the critical role of quantum effects in determining nanotube buckling but also provides valuable insights into the nuanced influences of atomic arrangement and nanosheet type on the mechanical properties of CNTs. Thus, our work contributes a novel perspective to the field, bridging the gap between quantum mechanics and the mechanical behavior of nanostructures, which has significant implications for the design and application of nanoscale materials

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)0.000
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 score0.150
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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

Citations12
Published2024
Admission routes1
Has abstractyes

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