Low-Stress Abrasion of Novel Ni-P-Tribaloy Composite Coating
Bibliographic record
Abstract
Degradation of industrial machinery through wear can be mitigated with the deposition of protective coatings to reduce maintenance costs and prolong their service lifespans. Electroless nickel-based composite coatings is one possible method used to provide this protection. The addition of Tribaloy (CoMoCrSi alloy) particles has been found to produce composite coatings with high toughness. In this work, electroless Ni-P-Tribaloy composite coatings were plated on AISI 1018 steel substrates and subjected to low-stress abrasion tests following ASTM G65 standards to investigate the abrasion of the coating. The test was performed at 10 revolution increments, with a 45 N applied load, until coating failure was observed and the measured abrasion was reported as volume loss. The two Ni-P-Tribaloy coating samples lasted for 90 and 100 revolutions, exhibiting a wear rate of 0.170 mm3 per revolution, compared to 0.135 mm3 per revolution for the Ni-P coatings. The abrasive wear mechanism in the Ni-P-Tribaloy coating was found to be plowing of the matrix around the Tribaloy particles, followed by the removal of the particles once they are protruding, which subsequently contributes to the three-body wear of the coating. The particle removal was accelerated at the coating particle-matrix interface. It is concluded that the size of the Tribaloy is a major factor, and we recommend that further studies be carried out using finer particles to improve the wear resistance of the Ni-P-Tribaloy coating.
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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 | 0.001 |
| 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".