Corrosion Study of Cold Sprayed Aluminum Coatings onto Al 7075 Alloy
Bibliographic record
Abstract
Abstract Aluminum coatings were deposited onto Al7075 T651 structural alloy using both cold spraying and arc spraying. Arc spray coatings were produced using optimized parameters for two atomizing gases, namely air and nitrogen. Cold spray coatings were produced using a low pressure system with air and nitrogen as propelling gases. Six surface preparation procedures prior to deposition were evaluated. Interface quality of as-deposited coatings was investigated by means of fluorescent dye interface penetration technique, bond strength testing and backscattered electron microscopy. Environmentally assisted cracking tests were performed to study the corrosion protection capability of the resulting coatings for structural applications. Micrographs of samples taken before and after cyclic load testing in salt water immersion were compared. The results demonstrated that the Al coatings produced by both arc spray and cold spray provide to Al7075 alloy a cathodic protection against cracking and localized corrosion. However, to obtain such coating properties arc spray technique required advanced surface preparation prior to deposition. For cold spray, the surface preparation has minimal influence on the coating properties thus making this process more advantageous than arc spraying for this application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".