The use of nitriding to enhance wear resistance of cast irons
Bibliographic record
Abstract
This research is focused on using nitriding to enhance the wear resistance of austempered ductile iron (ADI), ductile iron (DI), and gray iron (GI).Three gas nitriding processes, namely "Gas nitriding + nitrogen cooled down to 800 o F" (Blue), "Gas nitriding + cooled down to 300 o F" (Gray), and "Gas nitriding + oil quenched" (Oil) were used.This study was carried out through optical metallography, roughness measurements, microhardness, and SEM.The ball-ondisc wear tests were conducted under lubricated conditions.It was found that COF for all materials in all nitrided conditions was small (<0.045).The best wear performance was seen for ADI processed using the Gray and Oil gas nitriding processes.These processes produced a compound layer thickness of 4-6μm, a low surface roughness (0.8-1.3 μm, Ra) and a high surface microhardness (1800-2200 HV).The wear rate decreased with increasing surface microhardness and decreasing surface roughness.
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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".