Correlating the Layer Properties of Ni-alumina Composite Coatings and the Mechanism of Codeposition
Bibliographic record
Abstract
<p>Ni-Al<sub>2</sub>O<sub>3</sub> composite coatings electrodeposited from Watt’s electrolyte include Al<sub>2</sub>O<sub>3</sub> nano-and submicron particles. The effect of particle size and concentration of the particles in the electrolyte were investigated on the morphology and incorporation value of particles into the deposits. The influence of alumina particles on the electrodeposition behavior of Ni was also studied by means of electrochemical impedance spectroscopy. The results achieved from the impedance measurements and the correlation with the layer characterization could help to better understand the codeposition mechanism derived from the impact of different particle characteristics including size and concentration on the nature of the double-layer. The increase in the concentration of particles from 1 to 20 g/l resulted in an increase of the double-layer capacity and decrease of the charge transfer resistance, while the addition of submicron particles had a higher influence on the characteristics of the double-layer compared to the nano particles. Although the alumina particles with submicron size could stimulate the incorporation of particles faster than those with nano size, the strengthening performance of the layers not only depended on the incorporation value of the particles, but also on the microstructure of the deposits.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".