Influence of secondary component hardness when cold spraying mixed metal powders on carbon fibre reinforced polymers
Bibliographic record
Abstract
Tin has successfully been cold-sprayed onto carbon fibre reinforced polymers (CFRPs) in previous studies at McGill University. To improve the coating conductivity for lightning strike protection (LSP) purposes, other metal powders (aluminum, copper and zinc) were added to tin and also sprayed. Results indicated that addition of any of the aforementioned secondary components provided a noticeable increase in deposition efficiency (DE); it was hypothesised that a tamping mechanism might explain the improvement. In this study, aluminum and several aluminum alloys (5083, 6061, 7075) were mixed with tin powders to understand how the hardness of secondary components with similar densities may affect the DE. Mixing tin with other metallic powders is discussed and tamping is further explored as a mechanism in the cold spraying of mixed powders on CFRPs.
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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".