Improving Fracture Toughness of Alumina With Multi‐ Walled Carbon Nanotube and Alumina Fiber Reinforcements
Bibliographic record
Abstract
Alumina has been widely used for personal armour plate due to its relatively low cost, acceptable hardness and fracture toughness. With the increasing threat level, a much improved ceramic material with better ballistic performance and lighter weight is required. This paper is presents a research work, where alumina reinforced with 2D and 3D alumina fiber mats has been successfully developed for evaluation. The 2D alumina fiber reinforced alumina composite consists of an alumina matrix reinforced with 18 vol% of alumina fiber mats. And the 3D fiber reinforced alumina composite is made with alumina matrix with a 2D alumina fiber mats along with multi-walled carbon nanotubes vertically grown onto the fiber mats. In this study, a detailed examination on fracture surfaces of both 2D and 3D reinforced composites is conducted with scanning electron microscopy to elucidate the contribution of multi-walled carbon nanotubes and alumina fibers in enhancing the fracture toughness of the alumina matrix. Transmission electron microscopy investigation is also conducted on the composite with the 3D reinforcement to provide information on the morphological features at the fiber/matrix regions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".