Effect of diethanolamine and triethanolamine on the properties of electroplated Zn–Ni alloy coatings from acid bath
Bibliographic record
Abstract
Abstract In the present work, zinc–nickel alloy coatings have been produced under direct current conditions from an acid bath with different concentrations of diethanolamine (DEA) and triethanolamine (TEA). The produced coatings were analysed through chronopotentiometry, microhardness, X‐ray diffraction and MEB techniques. The compositional analysis of the films showed that the Zn–Ni electrodeposition is anomalous for all the systems. Ethanolamines augmented the anomalous behaviour. The hindering in the Ni (II) reduction will be more effective due to complexation of Ni (II) catalyst with ethanolamines. Electrochemical and structure analysis of deposits indicated the presence of γ and highly Zn‐enriched phases. The presence of these additives resulted also in coatings with finer grains. The behaviour of modified Zn–Ni alloy coatings in corrosion solution of 3% NaCl was investigated through potentiodynamic polarisation and electrochemical impedance spectroscopy. It was found that the obtained Zn–Ni/3 mM TEA alloy exhibited better corrosion resistance compared to pure Zn–Ni alloy electrodeposited at similar conditions. © 2012 Canadian Society for Chemical Engineering
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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 | 0.000 | 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".