Determination of Non-local Elasticity Constants for the Torsional Buckling of Single-Wall Carbon Nanotubes Using Molecular Dynamics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".