Duplex surface engineering of cold spray Ti coatings and physical vapor-deposited TiN and AlTiN thin films
Bibliographic record
Abstract
Abstract The feasibility of a duplex coating based on cold spray technology and magnetron sputtering was evaluated for repair applications requiring a ‘thin-on-thick’ layered structure. Commercially pure angular-shaped Ti grade 4 particles are fed to a cold spray gun and accelerated toward a Ti alloy substrate to deposit thick coatings (∼4.5 mm). TiN and AlTiN thin films are deposited on polished cold spray coatings using a four-source closed-field unbalanced magnetron sputtering (CFUBMS) system. Microstructure was characterized using focused ion beam (FIB) lift-out, scanning electron microscopy (SEM), and electron channeling contrast imaging (ECCI). The nanoindentation technique was used to evaluate the mechanical properties of coatings. The H/E ratios and H 3 /E 2 ratios for TiN films were found to be 0.098 and 0.26 GPa, respectively, while those for AlTiN films were measured at 0.066 and 0.052 GPa, respectively, suggesting higher capacity of TiN films to withstand both elastic and plastic deformation. Using scratch testing, the adhesion of TiN and AlTiN thin films to cold spray Ti was investigated, with TiN-Ti duplex coatings exhibiting better performance compared to AlTiN-Ti coatings. Tribological testing was performed on duplex coatings using a reciprocating tribometer equipped with an alumina ball counterface. The wear rate for AlTiN-Ti coatings after 2000 sliding cycles was found to be (1.0 × 10 −3 ± 0.1 × 10 −3 mm 3 /Nm), three orders of magnitudes higher than that for TiN-Ti (8 × 10 −6 ± 2 × 10 −6 mm 3 /Nm. SEM was used to reveal worn surface morphologies and cross-sectional analysis of the wear track. Subsurface microstructural changes due to wear were examined using focused ion beam cross-sectioning, revealing bending cracks and tribofilm formation.
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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".