An Svet Study of the Localised Corrosion of ZE20 Mg Alloy in Chloride Containing Electrolyte
Bibliographic record
Abstract
The localised corrosion behaviour of ZE20 magnesium alloy (composition Mg-2.4Zn-0.2Ce) is studied by a scanning vibrating electrode technique (SVET) in immersion conditions. Such alloys have improved ductility compared to commercial alloys due to the random structure produced by Ce additions, making them suitable for lightweight automotive parts. The alloy has been developed such that ductility and strength are optimised (27% elongation, 135 MPa yield strength; 225 MPa ultimate tensile strength) for such applications where ‘crashworthiness’ and formability are key. The corrosion resistance of magnesium alloys is still a significant challenge and understanding the mechanism by which corrosion occurs is fundamental to advancing performance. In the current study, SVET is used to measure the time-resolved local current density distributions in situ over freely corroding sample surfaces. The localised corrosion rates of ZE20 are studied in terms chloride concentration and pH. Figure 1 shows representative current density maps of the alloy freely corroding in immersion conditions. Figure 1 Surface plot showing the distribution of normal current density (jz) above a ZE20 magnesium alloy sample at times (a) 5 h and (b) 6.5 h following immersion in aerated 2 M aqueous NaCl at pH 7. Figure 1
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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".