Multiscale Modeling of Nano-Reinforced Structural Adhesive Bonds
Bibliographic record
Abstract
In this work, the mechanical properties of carbon nanotube reinforced structural adhesive bonds are investigated both theoretically and experimentally. The theoretical investigations employ a novel multiscale modeling technique that integrates governing atomistic constitutive laws in a continuum framework. This technique takes into account the discrete nature of the atomic interactions at the nanometer length scale and the interfacial characteristics of the nanotube and the surrounding polymer matrix. Appropriate formulations are developed to allow for the atomistic-based continuum modelling of nano-reinforced structural adhesive bonds on the basis of a nanoscale representative volume element that accounts for the nonlinear behaviour of its constituents; namely, the reinforcing carbon nanotube, the surrounding adhesive and their interface. This model is used to evaluate the constitutive response of carbon nanotubes with varied chiral indices. The newly developed representative volume element is then used with analytical micromechanical modeling techniques to investigate the homogeneous and dispersion of the reinforcing element into the adhesive considered upon the linear elastic properties.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".