Molecular dynamics simulation of pull-out Halloysite nanotube from polyurethane matrix
Bibliographic record
Abstract
Molecular dynamics (MD) simulation has been applied to study of pull-out of Halloysite nanotubes (HNTs) from a polyurethane (PU) matrix. First, the Machine learning (ML) particle swarm optimization (PSO) method was used to obtain force field parameters for MD from data of density functional theory (DFT) calculations. The current study shows the possibility of using a PSO technique to modify the force field with DFT data with less than 5 kcal/mol discrepancy. Second, we considered the influence of atomic interface on pulling out of HNT from PU. Energy variation has been proposed as the cohesion strength between matrix and nanoparticle. In addition, the best Lennard Jones parameters in the MD simulation make good agreement with an experimental sample stress-strain response.
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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".