Effect of Graphite on Mechanical and Tribological Properties of Al6061/SiC Hybrid Composites
Bibliographic record
Abstract
This study investigates the effects of incorporating graphite into a Al6061/SiC hybrid metal matrix composite on its mechanical and wear properties.The composites are fabricated using a stir casting technique, with SiC and Graphite particles added in different weight percentages ranging from 2-8%.Mechanical properties such as hardness, tensile strength, flexural strength, and compressive strength are evaluated.Results show that the composite with 6 wt.% of hybrid reinforcement exhibits significant improvement in hardness (30%), tensile strength (10.82%), compressive strength (68.14%), and flexural strength (85%) compared to pure Al6061 alloy.Furthermore, a wear test is performed using a pin-on-disc machine under dry conditions to assess the influence of parameters on the wear rate and coefficient of friction (COF).Tests are conducted at various loads (1-3 kgf), sliding speeds (150-450 rpm), and sliding distances (1000-2000 m).Among all reinforcements, the composite with 6% hybrid reinforcement exhibits the lowest wear rate and COF.Overall, this study provides valuable insights into the mechanical and wear properties of Al6061/SiC/graphite hybrid composites and highlights their potential for various industrial applications.These findings may pave the way for further research in the field of metal matrix composites and their applications.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".