A Study of the Mixed Powders Interaction Behavior Upon Impact in Cold Spray
Bibliographic record
Abstract
Abstract In this study, two sizes of iron and stainless steel powders were binarily mixed into four groups with different weight percent fractions and the various mixtures and single-component powders were cold sprayed onto aluminum substrates. The deposition efficiencies (DE) of the powder mixtures and single-component powders were measured and are compared. The results show that the four binary mixtures exhibit different DE characteristics as a function of stainless steel wt% and that the small size mixtures have higher DE relative to the single-component iron powder. The difference is explained by particle-particle interactions (tamping and retention) that occur upon impact and only in the small size mixtures. The study also finds that changing spray parameters, such as feed rate, stand-off distance, gun travel speed, and gas temperature and pressure, has no effect on particle-particle interactions.
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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".