Tribological Investigation of Plasma-Based Coatings for Use in Quasi-Monolithic Engine Cylinder Bores
Bibliographic record
Abstract
This study evaluates the tribological characteristics of quasi-monolithic engine cylinder coatings and piston rings using a custom-built linear reciprocating tribometer. The coatings were deposited on an Al-Si alloy cylinder bore using the Plasma Transfer Wire Arc (PTWA) and Electrolytic Jet Plasma Oxidation (EJPO) processes. The coatings’ tribological performances were investigated in the boundary lubrication regime. The performance of conventional chrome-coated cast iron piston rings was tested and compared to that of EJPO- and PTWA-coated engine cylinder samples that were extracted from a cast Al-Si engine block. Scanning electron microscopy and profilometry were used to compare the evolution of wear and the prevalent wear mechanism. This paper also presents the verification and repeatability analysis of a custom-built tribometer against a standard industry-calibrated tribometer. The wear test results showed that the EJPO coating had 0.05% to 10.35% lower wear rates than its PTWA counterpart throughout a wide range of loading conditions and sliding distances. The variation in the counter-face behavior is likely due to the different surface topographic parameters such as skewness, kurtosis, and porosity.
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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) | 0.000 | 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".