Wear mechanism transitions in FeCoNi and CrCoNi medium-entropy alloys from room temperature to 1000 °C
Bibliographic record
Abstract
• The hardness, wear rates and characterizations at 1000 °C are new records for MEAs. • The roles of Fe and Cr and their oxides in wear are discussed. • A new wear transition mechanism is revealed with deformable glaze layer. Many machine components are operated in dry sliding, elevated temperature, and oxidizing environments, leading to material failure or loss of functionality. Despite previous wear studies on conventional alloys, wear-related properties in high-entropy alloys (HEAs) and medium-entropy alloys (MEAs) up to 1000 °C are rarely reported. Here we systematically study the high-temperature hardness, wear behaviours and mechanisms of two popular MEAs, FeCoNi and CrCoNi, from room temperature to 1000 °C. We find that the wear resistance of FeCoNi surpasses that of CrCoNi at room temperature, 600 °C, and 800 °C. Contrarily, the wear resistance of CrCoNi surpasses that of FeCoNi at 400 °C and 1000 °C. By characterizing wear tracks, we identify that these wear-mechanism transitions are associated with alloy elements, oxidation rates, and oxide types. At room temperature, FeCoNi forms a spinel oxide layer with a lower wear rate than CrCoNi. At 400 °C, the wear rates of FeCoNi and CrCoNi are comparable because of temperature softening. At 600 °C and 800 °C, FeCoNi shows Co 3 O 4 as the main constituent of the glaze layer, enhancing wear resistance compared to CrCoNi. At 1000 °C, such glaze layer in FeCoNi undergoes severe plastic deformation, reducing its wear resistance; the Cr 2 O 3 oxide layer formed in CrCoNi remains hard and less deformable, contributing to its higher wear resistance. This study provides a fundamental understanding of the effect of principal elements on the wear performance in FeCoNi and CrCoNi-related MEAs and HEAs.
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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 | 0.001 | 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".