Effects of NbC addition on mechanical and tribological properties of AlCrFeNi medium-entropy alloy
Bibliographic record
Abstract
AlCrFeNi medium-entropy alloy (MEA) without expensive Co has demonstrated superior properties over the well-known AlCoCrFeNi high-entropy alloy. We added NbC particles to the MEA to make NbC-reinforced MEA alloys or MEA-matrix composites, and evaluated their wear resistances and mechanical properties. The materials showed considerably improved performance. To well judge the NbC-MEA for realistic applications, the wear resistance of the NbC-MEA samples was compared with those of a few industrial wear-resistant materials, e.g., high-Cr cast iron (HCCI) and WC-Co composites. It was demonstrated that the MEA samples with 40–60 vol% NbC exhibited markedly higher wear resistance than the reference materials, and the MEA demonstrated high superiority over the widely used Co as the metal-matrix for developing wear-resistant metal-matrix composites (MMCs).
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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) | 0.001 | 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".