Features of self-organization in ion modified nanocrystalline plasma vapor deposited AlTiN coatings under severe tribological conditions
Bibliographic record
Abstract
Features of self-organization in the hard AlTiN plasma vapor deposited (PVD) coatings have been investigated under severe frictional conditions associated with high temperatures and stresses, which are typical for high-speed cutting. Aluminum-rich (around 67at.%) (Al67Ti33)N hard PVD coating has been modified by means of the “duplex” post-treatment, including annealing in vacuum at 700°C with subsequent ion implantation by Ar+. Structure modification of the surface layer has been studied using x-ray photoelectron spectroscopy, electron energy loss fine structure, and high resolution electron energy loss spectroscopy methods. Micromechanical characteristics of the coating have been studied using the nanoindentation method. Coefficient of friction was measured in relation to temperature. Wear behavior of the coating has been investigated under severe conditions of HSC of 1040 steel. Results show that the enhancement of nonequilibrium processes during friction due to ion implantation of AlTiN coating by Ar+ leads to a dominating formation of protective triboceramics on the surface with sapphire-like structure that critically improves wear performance. Analytical modeling of the mass transfer within initial stage of wear was performed based on the concept of irreversible thermodynamics and self-organization in order to formulate the principles of friction control.
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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 | 0.001 |
| 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".