Cold Spray of Mixed Sn-Zn and Sn-Al Powders on Carbon Fiber Reinforced Polymers
Bibliographic record
Abstract
Carbon fiber reinforced polymers (CFRPs) have been increasingly used in the latest generations of aircraft and helicopters for lightweight purposes, but this leaves vulnerability against lightning strike. Cold spray is one coating approach to metallize the polymers, thus making them lightning strike proof. It has been reported that direct cold spray of metals onto CFRP is difficult. However, research at McGill University has shown that tin coatings can be cold sprayed on CFRP, but the deposition efficiency is very low. In this work, aluminum and zinc powders were mixed with tin to investigate the effect of mixing on deposition efficiency of the coating. The mixed metal powders were cold sprayed on CFRP with a low-pressure cold spray system at various conditions. It was found that the addition of aluminum or zinc resulted led to increased deposition efficiencies compared to pure tin, but there are many differences in the details of the effect of Al and Zn additions on the deposition characteristics. The deposition mechanism of the mixed metal powders on CFRP is discussed, and the effect of mixing powders on the deposition efficiency is evaluated.
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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".