The Correlation of Texture and Microstructure to the Corrosion Resistance of Tin Coatings
Bibliographic record
Abstract
The influence of current density and temperature on the macrotexture, the orientation and size of grains, and the corrosion resistance of tin deposits was studied. Tin coatings with two different textures, (100) and (301) fiber textures were produced by electrodeposition at 20°C by varying current density. At a lower current density of 100A/m2, (301) fibre was obtained. At the current densities of 100 and up to 400 A/m2, only (100) fibre texture was observed. An increase in current density leads to a decrease in grain size. At the same current density, the grain size of tin coatings increases with increased temperature. The influence of temperature (20, 40, 60 and 80 °C) on texture is relatively negligible. The corrosion resistance of tin coatings increases with a decrease in grain size. The corrosion resistance of tin coating with (301) fibre is higher than that of tin coating with (100) fibre texture. The results suggest that texture and microstructure play an important role in controlling corrosion rate of tin based 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 | 0.000 | 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".