Saccharin Effects on Direct-Current Electroplating Nanocrystalline Ni–Cu Alloys
Bibliographic record
Abstract
Poor surface finish and coarse dendrite structure are the major challenges in direct-current (dc) plating of nanosized Ni–Cu alloy coatings. This investigation was initiated to understand the effect of saccharin on the formation of nanosized Ni–Cu alloy coatings by sediment codeposition, and the role of saccharin in improving surface finish and suppressing coarse dendrite growth during sediment codeposition. It was found that only 0.5 g/L addition of saccharin could form dendrite-free nanocrystalline Ni–Cu alloy coatings with a mirror-finish surface. The Cu content in the Ni–Cu alloy coatings can be controlled to be as low as 10 wt % by changing the current density. The grain size in the coatings was determined by X-ray diffraction and electron microscopy analysis to be 15.7 nm on average. The amount of ordered -type Ni–Cu nanophase was found to be insignificant in comparison with that in pulse plated coatings. Saccharin suppresses the reduction of Cu and acts as a leveling and grain size reduction agent in Ni–Cu alloy codeposition. From steady-state polarization and impedance analysis, it is believed that these saccharin effects are produced by the formation of Ni–Saccharin complexes adsorbed on the coating surface that suppress Ni–Cu dendrite growth.
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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) | 0.000 | 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 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".