Development of Novel Corrosion Resistant Electroless Ni-P Composite Coatings for Pipeline Steel
Bibliographic record
Abstract
ABSTRACT This paper describes the deposition of various Ni-P composite coatings over an AISI 1012 steel sample through an electroless coating process. The composite coatings were prepared using various ternary additives namely carbon nanotubes, titanium, and alumina. Coated samples were characterized over alongside surface and cross-sections using energy dispersive spectroscopy. Corrosion behaviors of composite coatings were characterized using potentiodynamic polarization. Mechanical and tribological attributes were evaluated using Vickers hardness and nano-indentation, respectively. Among the candidate additives, Titanium reached the maximum incorporation (upto 30 wt.%). Alumina particles showed competing compromise between surface smoothness and deposition rate. Carbon nanotubes improved lubrication effects by reducing co-efficient of friction (checked using universal micro tribometer). Alumina manifested the highest hardness and the least corrosion rate in comparison to the candidate additives.
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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".