Mechanical and Morphological Investigation of Aluminium 7075 Reinforced with Nano Graphene / Aluminium Oxide / Inconel Alloy 625 Using Ultrasonic Stir Casting Method
Bibliographic record
Abstract
Aluminium Hybrid Metal Matrix Nano Composites (AHMMNCs) are finding widespread use in the aerospace, marine, defence, and automotive industries due to its high stiffness, high strength-to-weight ratio, and outstanding wear resistance. Hybrid nano composite materials are commonly used in engineering applications due to their proper mechanical organisation. Mechanical property improvement of hybrid nano composites is now a prominent field of research in materials and industrial technology. Aluminium alloy 7075 was reinforced with 0.5, 1.5%, and 2.0 wt. percent of nano-graphene (20-30nm), 2,4,6,8 wt percent of aluminium oxide (50m), and 2,4,6,8 wt percent of Inconel alloy 625 and 1wt percent of magnesium utilising an ultrasonic stir casting process in this study. Mechanical characteristics of the hybrid nano-composite material were evaluated using tension, compression, hardness, and flexural tests. SEM was used for morphology inquiry examination.
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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".