Wear behavior of self-propagating high-temperature synthesized Cu-TiO2 nanocomposites
Bibliographic record
Abstract
In this paper, the copper-based nanocomposites with TiO2 nanoparticles were synthesized by the self-propagating high-temperature synthesis (SHS) process. The effect of the different amounts of excess copper, in comparison with the stoichiometric ratio (CuO:Ti ratios of 1:1, 2:1, and 3:1), on the phase formation of achieved samples was studied. A thermodynamical study showed that increasing the excess copper powder reduces the adiabatic temperature, which helps the phase formation. The maximum Brinell hardness (89) was obtained for the sample with the CuO:Ti ratio of 1:1. Finally, the wear behavior of the synthesized nanocomposites was evaluated by the pin on disk test, and the variation of friction coefficient and lost weight were measured. The friction coefficient decreased by the formation of phases and distribution of titanium oxide particles during the SHS process in the presence of the stoichiometric ratio of CuO:Ti. Therefore, the wear behavior was improved. The lowest depth of wear trace was measured 0.68 where the ratio of CuO: Ti was 1:1.
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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) | 0.000 | 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 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".