Fracture of Graphene-Ceramic Composites With Defect
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Utilized in various protective barriers, electronics, energy devices, and aerostructures, silicon carbide (SiC) is celebrated for its superb thermo-chemo-mechanical properties. Particularly, modifying SiC with various additives such as graphene-based inclusions has recently proved to be a practical way to attain damage-tolerant SiC ceramic matrix composites with various multifunctionalities. Nonetheless, the presence of defect in the aforementioned hybrid material could have noticeable impact on their mechanical properties including fracture performance. Such problem received less attention so far due to the difficulties in tracking defects in experiments and incapability of the traditional modeling and computational platforms. In that regard, the fracture of hybrid graphene-SiC system with defect is examined in this work. To this end, phase field model of brittle fracture is developed to address damage mechanics and crack propagation across the defective graphene-SiC hybrid materials. The numerical results reveal that the location and density of defects have adverse influence on the resistance to complete fracture of the above-mentioned hybrid materials. Basically, the resistance to complete fracture decreases for the graphene-ceramic composite with defect closer to the initial notch location. Further, resistance to complete fracture is lowered remarkably as the density of defect increases inside the ceramic matrix; thus, defect is anticipated to be considered as a design parameter to achieve reliable and multifunctional graphene-ceramic composites with enhanced fracture properties.
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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) | 0.005 | 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