The Performance of Zn-Ni Alloy Coating Electrodeposited from Stabilized Bath
Bibliographic record
Abstract
A metallic part corrodes when it undergoes electrochemical reactions which cause the surface and structural deterioration of the metal. Through electroplating, metallic components can be protected from corrosion by coating them with Zn-Ni alloys. This study examined the electrodeposition of a Zn-Ni alloy film on a steel substrate from a chloride bath containing ethylene-diamine-tetraacetic acid (EDTA). A Pourbaix diagram using the OLI software was used to determine the stability of the Zn-Ni plating bath and the suppression of hydrogen evolution reaction (HER). Comparing the composition of Zn-Ni coating deposited in the EDTA bath with the pure Zn-Ni coating, the EDTA bath yielded higher deposition thickness and an average crystallite size reduction. The Zn-Ni coating deposited from the EDTA bath has a lower dissolution rate and better corrosion resistance properties than the non-EDTA bath. Polarization tests exhibited that the Zn-Ni alloy deposited from 0.119 mol/l EDTA bath at 20 mA/cm2 current density showed lower corrosion current (Icorr) and more positive corrosion potential (Ecorr). Atomic force microscopy (AFM) and Vickers microhardness testing were used to characterize the morphological properties, topographic structures, and microhardness of Zn-Ni coatings.
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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 | 0.001 |
| 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 | 0.001 | 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".