General and Galvanic Corrosion Behavior of Aluminized Ultra-High Strength Steel (UHSS) and Magnesium Alloy AZ35 Altered by Plasma Electrolytic Oxidation Coating Processes
Bibliographic record
Abstract
Ultra-high strength steel (UHSS) and magnesium (Mg) alloy have found their importance in response to automotive strategy of light weighting. UHSS to be metal-formed by hot stamping usually has a hot-dipped aluminum-silicon alloy layer on its surface to prevent the high temperature scaling during the hot stamping and corrosion during applications. In this paper, a plasma electrolytic oxidation (PEO) process was used to produce ceramic oxide coatings on aluminized UHSS and Mg with intention to further improve their corrosion resistances. A potentiodynamic polarization corrosion test was employed to evaluate general corrosion properties of the individual alloys. Galvanic corrosion of the aluminized UHSS and magnesium alloy coupling with and without PEO coatings was studied by a zero resistance ammeter (ZRA) test. It was found that the heating-cooling process simulating the hot stamping would reduce anti-corrosion properties of aluminized UHSS due to the outward iron diffusion. The PEO coating could reduce corrosion current and increase corrosion potential of aluminized UHSS. A denser PEO coating, usually produced using a bipolar current processing mode and thus showing a higher polarization corrosion resistance, was not always good for the galvanic corrosion prevention of the steel and Mg coupling. The corrosion behaviors could be explained based on surface area ratios and corrosion potential gaps (corrosion driving forces) of anode (the Mg sample) vs. cathode (the steel sample) altered by the difference of current modes in PEO coating processes.
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".