Corrosion Protection of Mg-Alloys with Cold Sprayed Composite Coatings
Bibliographic record
Abstract
Abstract Due to the demand for improved fuel economy as well as increased safety features, weight reduction is one of the major aims in the automotive industry. Future lightweight automotive components for the next car generation will probably use lots of magnesium alloy. These will form galvanic couples with other materials and may induce phenomena accelerating the corrosion rate of automotive components. The materials used were magnesium alloy AZ31B and several types of cold sprayed coating. The relative performance of each cold sprayed corrosion preventive compounds (CPC) was assessed in combination with the materials under several different electrochemical and accelerated corrosion tests. Baseline data for AZ31B with no CPC applied was also collected. CPC characteristics and properties are also included and discussed. The studies on bare Mg/Steel couples validated accelerated corrosion but found that CPC cold sprayed coatings mitigate corrosion rates. Thus Mg/Fe interfaces with defect-free cold sprayed coatings CPC can prevent buildup of corrosion products and reduce galvanic corrosion of automotive components.
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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".