Micromechanics Modeling of Bi-Axial Stretching Effects on the Electrical Conductivity of CNT-Polymer Composites
Bibliographic record
Abstract
In this paper, the bi-axial stretching effects on the electrical conductivity of carbon nanotube (CNT)-polymer composites are studied by a mixed micromechanics model with the consideration of the electrical conductive mechanisms. The bi-axial stretching effects are characterized by volume expansion of composite, re-orientation of CNTs and change of conductive networks. Simulation results demonstrate that the bi-axial stretching decreases the electrical conductivity of the composites due to the dominant role of the stretching-induced change in conductive networks, i.e., the increase in the percolation threshold, the separation distance among CNTs and the breakdown of the networks. It is also found that the bi-axial stretching enhances the decreasing rate of the electrical conductivity and increases the distribution randomness of the CNTs in the bi-axial stretching plane, as compared to a uni-axial stretching case. Furthermore, the dependency of the variation of electrical conductivity on the CNT concentration and sizes is also investigated. Possible reasons for the variation trends are interpreted. The study in this paper is expected to provide an increased understanding on the stretching effects upon the electrical conductivity of CNT-polymer composites.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".