Cold-Sprayed Aluminum Alloys: Exploring the Differences Between 6061 and 7075
Bibliographic record
Abstract
Abstract Cold spray is a solid-state metal powder deposition technique that has proven to be highly effective in depositing a wide range of metals, including aluminum and its alloys. However, higher strength, heat treatable Al alloys appear to exhibit variable deposition efficiencies and responses to heat treatments designed to increase ductility. This work is aimed at understanding the sources of these variabilities. In this study, 6061 (0.9% Mg, 0.6% Si, 0.3% Cu, 0.1% Cr, 0.1% Fe) alloy is compared to 7075 (6% Zn, 1.6% Cu, 2.4% Mg, 0.2% Cr, 0.3% Fe) alloy. These are common heat treatable alloys, but they exhibit quite different cold spray characteristics. Generally, 7075 is more problematic in terms of deposition efficiency and the mechanical properties after heat treatment. The alloys were processed under various cold spray conditions, including laser assisted cold spray designed to soften the 7075, and subjected to heat treatments intended to increase ductility. The microstructure and mechanical properties of the as sprayed and heat-treated coatings were characterized and compared. The results of this investigation will reveal possible mechanisms explaining the different cold spray behaviors and some suggestions will be proposed to overcome the problems associated with 7075.
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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 | 0.001 | 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".