Effect of Hot Deformation on the Wear Behavior of Al2O3/ A356 Nano-Composites
Bibliographic record
Abstract
In the present work, Al2O3/A356 nano composites with different Al2O3 nano sizes (10 and 20 nm) and weight percentages (1 and 2 wt.%) have been prepared using rheocasting technique and followed by hot deformation at 250 °C with different ratios (30 and 40%). Pin on disc wear test was used to study wear behavior of prepared Al2O3/A356 nano composites while scanning electron microscopy used to build up the wear mechanism. The results showed that the hot deformed nano Al2O3 /A356 composites have lower wear rate compared with non deformed one. Furthermore, with increasing the particle size and percentage of Al2O3 nano particles, wear rate decreased. The optimal result was achieved at the nano-composite containing 20 nm Al2O3 particles after hot deformation with ratio of 40%. SEM studies of the worn surfaces of nano composites showed that the main wear mechanism was oxidative in conjunction with metallic one.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".