Single Particle Erosion Behavior of NiTi-Based Nanolaminates and Superelastic NiTi Monolayer Coatings
Bibliographic record
Abstract
Bulk NiTi is used to make parts, such as couplings and bearings, that can be found in many industries such as the automotive, aerospace and medical sectors. Forming and machining bulk superelastic NiTi is a very difficult and costly process; however, applying NiTi as a surface coating will provide an alternate manufacturing method that will minimize machining processes. The objective of this study is to produce a superelastic NiTi-based surface coating that exhibits denting, impact and wear resistance. Superelastic NiTi has been successfully produced through vacuum deposition processes, despite this, there is a lack of a full and comprehensive study on the formation of the NiTi phase during coating development. In this study, the NiTi phase is fabricated through the annealing of sputtered deposited Ti and Ni layers in a coating. To confirm the presence of the intermetallic phases, X-ray diffraction (XRD) and energy dispersive spectrometry (EDS) analysis were performed. The erosion behavior of the coating is evaluated through single particle erosion testing, which resulted in the coatings that contained the NiTi precipitates to exhibit the best damage resistance compared to the other nanolaminates. This indicates that the superelastic NiTi phase increases the resistance to impacting particles. Microstructural evolution and NiTi formation during annealing is discussed and related to the observed damage resistance of the coatings.
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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".