Fabrication of ceramic deposits by cold gas spraying : connection between the powder caracteristics and the physical properties of the coatings
Bibliographic record
Abstract
Cold spray is based on the acceleration at a supersonic velocity (up to 1200 m.s-1) of unmelted pow- der particles through a de Laval nozzle by a high-pressure gas (e.g. N2). As the powder is not molten in the gas, the deposit is mostly generated by the powder plastic deformation and/or brittle fragmentation and its mechanical anchorage when impacting the substrate at high kinetic energy. Up to date, cold spray has been mostly dedicated to ductile materials (i.e. metals). However, cold spray of brittle materials (i.e. ceramics) has recently gained attention, particularly with agglomerated powders. In the specific case of ceramics, the challenge consists mostly in controlling the powder fragmentation at the impact to optimize the coating quality (i.e. low porosity and good mechanical adhesion) and its construction rate. In this thesis several routes have been investigated, mostly with hydroxyapatite. In the first one, the influence of the powder properties have been studied, and specifically the shape and size of the nanoparticles inside the agglomerates. Since the adherence is mostly mechanical, acicular and fine particles are of interest because their entanglement is way better, and makes the construction of the coating easier. In the second route, coatings obtained have been optimized through the equipment used, the choice of the spraying parameters, as well as the substrate. Interesting results have been carried out especially working on the spraying cinematic and using PEEK sublayer sprayed with flame spraying. Finally, in the last route, experiments have been done under vacuum, in conditions close to the one in aerosol deposition. By reducing the bow shock, the deposition efficiency is substantially improved, leading to thick 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".