Inner Diameter High-Velocity Air Fuel (ID-HVAF) Spraying of Copper, Compared to Cold Spray
Bibliographic record
Abstract
Abstract As a supersonic solid-state deposition process, Cold Spray (CS) has a unique role among other thermal spray techniques as it uses compressed and heated gas to accelerate particles to a critical velocity. CS can be an expensive process, especially when helium is used as a processing gas. In recent thermal spray developments, High-Velocity Air Fuel (HVAF) has taken a specific place in terms of providing dense and strong coatings similar to CS, but also coatings with less oxidation than High- Velocity Oxy-Fuel (HVOF). In contrast to these techniques, HVAF uses a mixture of fuel and air, instead of pure oxygen as in HVOF, to accelerate particles. Therefore, HVAF appears as a relatively cheaper and environmentally friendly alternative for the deposition of a wide variety of materials. The aim of this research is to produce fully dense copper coatings with limited oxidation using an inner diameter (ID) HVAF system and to compare the microstructure with CS copper coatings. Coating microstructures, surface roughness, and microhardness are studied using different characterization methods such as Scanning Electron Microscopy (SEM). Through this paper, the influence of both spray processes, CS and ID-HVAF, on the deposition of copper coatings is discussed. Cross-sectional studies of different coatings show a fairly dense microstructure for CS and ID-HVAF coatings. Moreover, it is discussed how the copper coating properties can change upon modifying the spray parameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".