Investigation of the Fundamental Frequency of Double Walled Carbon Nanotubes Using Molecular Mechanics Approach by an Averaging Van Der Waals Forces Modeling
Bibliographic record
Abstract
Carbon nanotubes have received a lot of attention since their introduction in 1991 because of novel properties that show substantial promises for use in many applications. Their usage depends on the strength of our knowledge of their properties. In this work, molecular mechanics approach is used to study the mechanical properties of multi-wall carbon nanotubes. In particular this paper investigates fundamental frequency of double walled carbon nanotubes. Carbon nanotubes are big and long molecules that can be regarded as mechanical structures. In modeling of multi-walled carbon nanotubes, two distinct atomic bonds are required to be modeled, i.e. covalent bonds between the neighboring carbon atoms in the same layer and Van der Waals bonds between close atoms in neighboring layers. In this approach, for modeling of each wall; covalent bonds are modeled by beam joints such that atoms are considered to be concentrated masses at the ends. Interactions of neighboring walls that are mainly due to Van der Waals forces are treated to be truss rods in modeling. The most challenging aspect of modeling is to define truss rod properties as they are highly nonlinear. We utilized an averaging method for finding truss rod properties. Finite Element Method is employed to obtain Fundamental frequencies. Results are compared to available researches and a close agreement is observed. Results indicate that by increasing aspect ratio, fundamental frequency of double walled nanotubes decrease. In addition, double walled carbon nanotubes have higher fundamental frequencies at clamp-clamp in comparison to clamp-free condition; however, this difference becomes negligible as aspect ratio increases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".