Strength and Wear Properties of Stainless Steel Coatings Produced by Cold Spray with Various Powder Sizes
Bibliographic record
Abstract
Abstract Cold spray processing of stainless steel coatings, which represent a cost-effective method for wear and corrosion resistance, has been demonstrated as technically feasible. However, these coatings have very low tensile strength in the as-sprayed condition and may also exhibit a marginally higher wear rate. In this study, the cold spraying of 316L stainless steel coatings was investigated to assess the effect of powder size distribution and post-spray heat treatment on strength and wear properties. Coatings on aluminum and steel substrates were produced with a feedstock powder obtained in three particle size distributions. All coatings were deposited under the same conditions using nitrogen as the propellant gas, and then annealed at the optimum temperature. The microstructure and mechanical properties of both as-sprayed and heat-treated coatings were evaluated and the results are presented in the paper.
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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".