Characterisation and evaluation of Al-8011 metal matrix composites reinforced with B<SUB align="right">4C + carbon nano tubes particulate
Bibliographic record
Abstract
In this study, a novel metal matrix composite (MMC) was created by reinforcing an Al-8011 alloy with carbon nanotube (CNT) and boron carbide (B4C) hybrid particles. The composites' density (ρ), Poisson's ratio (v), and Young's modulus (E) were calculated using the rule of mixture. Hardness, tensile, and compression strengths were measured on relevant specimens according to ASTM standards. The hybrid reinforced composite (5% B4C + 1.5% CNT) reached 123.6 HRA in the hardness test. 5% B4C + 1.5% CNT reinforcement improved tensile strength to 310.2 MPa. Compression strength, on the other hand, reduced as B4C and CNT percentages increased. For applications demanding the greatest hardness and tensile stresses, the MMC of Al-8011 alloys with 5% B4C and 1.5% CNT was optimal. For the most compressive applications, it was determined that Al-8011 doped with 1% B4C and 1.5% CNT would be the optimal choice. The hybrid reinforcements of B4C and CNT improved the composite, making it suitable for structural applications.
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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".