Development of Cu Coating on Ceramic Substrates by Low Pressure Cold Spray and its Deposition Mechanism Analysis
Bibliographic record
Abstract
Cold spray (CS) is a solid-state deposition technique of micron-sized metallic powder in an ultra-high velocity gas using a de Laval nozzle. CS is a unique deposition technique due to its use of relatively lower gas temperatures in comparison to other thermal processes. Consequently, high-temperature oxidation and phase transformations of deposited powders are largely restricted while the operating cost of CS is much lower than that of other thermal processes. Generally, the low pressure cold spray (LPCS) technique is used for the deposition of metallic powders on metallic substrates, while only a few studies of metallic particle deposition on ceramic substrates have been conducted, and it was found that the deposition of metallic powders on ceramic substrates was quite difficult. In this study, improved LPCS deposition of copper coatings on zirconia substrates was investigated. It is known that deposition of a metallic powder on a ceramic substrate is difficult due to the differences in material bonding and several properties of the two materials. These difficulties in LPCS deposition were solved using three different approaches, namely 1) use of copper and aluminum composite powders and 2) laser pre-treatment and 3) laser texturing of zirconia substrates. It was found that pure copper powder coatings on the as-received and various treated substrates were delaminated in the interface as expected. However, the deposition was improved for all substrates by using the copper and aluminum composite powder. While the laser pre-treated substrate was not effective for the deposition of the copper and aluminum composite powder, thick coatings were obtained for the deposition on the laser pre-treated with heat treatment substrate and the laser-textured substrate.
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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".