Molecular Dynamics Simulation of Single-Walled Carbon Nanotube – PMMA Interaction
Bibliographic record
Abstract
Mechanical performance of nanocomposites is strongly dependent on the interaction properties between the matrix and the reinforcement. Therefore, the aim of this work is to investigate the carbon nanotube – polymer interaction in nanocomposites. With the ever-increasing power of computers, and enormous advantage of parallel computing techniques, molecular dynamics is the favourite technique to simulate various atomic and molecular systems for this application. In order to simulate nanocomposites using molecular dynamics techniques, a stepwise approach was followed. First, a single-walled carbon nanotube was modelled as the reinforcing material. The validity of the model was examined by applying simple tension boundary conditions and comparing the results with the literature. Next, PMMA chains, with different geometries and molecular weights, were modelled employing the chemical potentials extracted from the literature. The last step included the modelling of the nanotubes surrounded by the matrix material and the investigation of the energy minimization for the system. Based on the results, the non-covalent interaction energy between a single-walled carbon nanotube and the PMMA matrix was obtained.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".