Effect of Graphite Addition on Aluminum Hybrid Matrix Composite by Powder Metallurgy Method
Bibliographic record
Abstract
The requirement for optimal strength and lightweight materials is a challenge in today's automotive industry. In this study, the synthesis of aluminum matrix hybrid composites containing magnesium and copper with the addition of graphite 0, 1, 3, and 5% by volume was carried out using powder metallurgy techniques and investigated the effect of the treatment given. The investigation of composite properties was carried out by testing density, porosity, hardness, wear rate, XRD, and SEM investigations integrated with EDS. Optimal conditions indicated composite with a content of 5% volume of graphite with the lowest porosity level of 5.10%, the relative density of 88.67%, and the highest hardness at 50.37 HV, followed by superior wear resistance. This result is supported by observing secondary phase formation and microstructure through XRD and SEM-EDS. The addition of graphite in the composite supports optimizing physical and mechanical properties as a lightweight composite. It deserves to be considered as an alternative material for automotive components.
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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 | 0.000 | 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) | 0.001 | 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".