Comparison of two methods used for high temperature tribological testing of protective thin coatings
Bibliographic record
Abstract
This study aims to contribute to the better understanding of results obtained by different methods used for high temperature tribological evaluation of hard coatings. For these purposes tribological testing directly at high temperatures and testing of annealed coatings at room temperature were compared. In this study, high temperature tribological behavior of 3 μm thick TiAlN coating (3050 HV0.05) was evaluated using high temperature pin-on-disk tribometer. Coating was prepared on EN X38CrMoV5 steel samples using cathodic arc deposition. Coated samples were tested against Al2O3 ball, in air atmosphere, at room temperature, 300 °C, 500 °C, 600 °C, and 700 °C, and after being previously annealed (PA) at these temperatures. Stylus profilometry, confocal microscopy, focused ion beam, and energy dispersive spectroscopy were employed for evaluation of the wear tracks. At room temperature (RT) the steady-state COF was 0.72. Tribo-tests at 300 °C and 500 °C resulted with steady COF which slightly increased to a maximum value of 0.7 and 1, respectively. COF for tests at 600 °C and 700 °C, after reaching a max value of 0.95 and 0.85, declined for both cases. Each of the tribo-tests on PA samples displayed COF values similar to RT tests, but with pronounced oscillations. Tribo-tests at RT and on PA samples produced similar wear tracks that displayed combination of both adhesive and abrasive wear mechanism, while abrasive and oxidative wear mechanism was observed at high temperatures. At 600 °C coating degradation due to oxidation of substrate initiated, and at 700 °C coating was completely damaged. It is suggested that declining COF at 600 °C and 700 °C is due to formation of Fe-O and Cr-O inside of wear tracks. Additionally, oscillations of COF on PA samples are suggested to be the consequence of adhesive wear of coatings. Finally, detailed analysis revealed that, apart from their COF, tribo-tests on PA samples are quite similar to RT tests, but significantly differ from high temperature tests.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".