Mechanical properties of CNT-reinforced Ni <sub>3</sub> Al composites: the role of chirality, temperature, and volume fraction
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Bibliographic record
Abstract
[Formula: see text] is an extremely significant reinforcing phase in nickel-based single crystal superalloys. As an alternative strengthening method to improve its mechanical properties, carbon nanotube (CNT)-reinforced [Formula: see text] composites have recently been synthesized in experiments. Here, in order to explore the corresponding influence factors and the underlying mechanism, tensile and compressive mechanical properties of CNT-[Formula: see text] composites are systematically investigated by using molecular dynamics simulations. It is shown that the dispersion of a minor fraction of a CNT into [Formula: see text] matrix leads to a sufficient enhancement in the stiffness of CNT-[Formula: see text] composites compared with the pure [Formula: see text]. It is demonstrated that CNT reinforcement takes effect in the elastic stage under compression while it works continuously during tension. Compared with armchair CNTs, zigzag CNTs are predicted to provide more strength for raising the elastic modulus while armchair CNTs can provide superior elongation. Particularly, CNTs are found to hinder the generation of slip bands under tensile loading owing to the robust interfacial interactions. Furthermore, quantitative analysis reveals that the impact of volume fraction of CNT is much more significant than the size effect. The role of chirality, temperature and volume fraction of CNT obtained in the present work could provide beneficial references for subsequent theoretical and experimental investigations, and shed some light on the design of CNT-reinforced composites in nanoscale engineering.
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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 it