The effect of different surface topographies on the corrosion behaviour of nickel
Bibliographic record
Abstract
The electrochemical and corrosion behaviour of a surface is extremely complicated and depends on various chemical, physical and mechanical factors.In this study the effect of different surface roughnesses on the corrosion resistance of nickel in 0.5 M sulphuric acid was investigated.Open circuit potential, corrosion current density, polarization resistance and corrosion rate were measured for surfaces polished with different grits (120, 240, 400, 600 and 1200) of silicon carbide papers.The surface roughness was measured using a profilometry method both before and after corrosion testing.SEM images were taken and compared for all of the samples before and after corrosion tests.The results showed that surface roughness and surface morphology can considerably change corrosion and corrosion rate.A higher corrosion resistance is obtained for surfaces with lower roughnesses.Finally, the results were compared with specimens where a specific surface patterning was obtained using a laser ablation method.
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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".