Dry sliding wear behavior and its relation to microstructure of artificially aged Al-Si-Mg/TiB2 in situ composites
Bibliographic record
Abstract
Mechanical stir casting is utilized to produce an artificially aged Al-Si-Mg alloy, whereas halide slat (K2TiF6 and KBF4) synthesis is utilized to produce Al-Si-Mg/TiB2 aluminum matrix composites. The dry sliding pin on disc wear test was conducted using a DUCOM/TR-20LE-PHM-200 machine to simulate an automobile application (Piston-Ring assembly). Where pistons are made of aluminum alloy (for the Pin) and rings are made of grey cast iron (for the disc material). At room temperature, a wear test was conducted by altering the ageing time (3, 6, 9, 12), sliding speed (2, 2.5 m/s), and applied load (14.71, 19.62, 24.52 N) with the disc speed (500 rpm) held constant (10 min). The results indicate that the aluminum matrix composite (AMC) wear rate is reduced by 37 percent at higher sliding speeds (2.5 m/s) and by 4 percent at lower sliding speeds (2.0 m/s) compared to the base alloy. Field emission scanning electron microscope-energy dispersive spectroscopy (FESEM-EDS) and X-ray photoelectron spectroscopy (XPS) analysis revealed that the formation of the mechanically mixed layer (MML) or oxidative layers on the worn surfaces reduces the wear rate under conditions of longer ageing time, higher sliding speed, and lower applied load. The research demonstrates that composite wear is a function of sliding velocity, aging period, and applied force. As sliding speed rose from 2 m/s to 2.5 m/s, the wear rate of composites dropped reasonably, yet composites are softer than basic alloys. It is conceivable due to the presence of a considerable amount of MML and the formation of oxidative layers between pins and their equivalents.
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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 | 0.000 | 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) | 0.000 | 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".