Mechanical properties and wear behaviors of lightweight Al3Ti-based medium-entropy alloys at elevated temperatures
Bibliographic record
Abstract
Al 3 Ti-based medium-entropy alloys (MEAs) with improved high-temperature mechanical properties and wear resistance were fabricated using arc melting method via alloying Al 3 Ti with various amounts of Cr, Mn, Fe and Cu elements. The alloying elements, Cr, Mn, Fe, and Cu, transformed the brittle D0 22 structure into a ductile L1 2 structure, along with the formation of hard B2 and D8a second phases. The resultant combination of improved ductility and strength enhances the mechanical performance of the material. A representative alloy, Al 60 Ti 20 Cr 5 Mn 5 Fe 5 Cu 5 , achieved high yield strength and high hardness of 442 MPa and 270HV2 at even 500 °C. Wear tests showed that the Al 3 Ti-based MEAs distinctly outperformed conventional Al-matrix composite reinforced with 30 wt% of SiC particles at both room temperature and 300 °C. The ordered L1 2 , B2, and D8a phases not only led to good room-temperature strength and hardness, but also contributed to high thermal stability, contrasting with solid solution alloys, resulting in superior high-temperature performance. The results highlight Al 3 Ti-based MEAs as competitive candidates for medium-temperature applications, bridging the gap between aluminum and titanium alloys in engineering applications. • Lightweight Al 3 Ti-based medium-entropy alloys (MEAs) were designed, fabricated and investigated. • Alloying Al 3 Ti with Cr, Mn, Fe, and Cu transformed D022 Al 3 Ti into L12 matrix with B2 and D8a second phases. • Al 3 Ti-based MEAs can be readily tailored for low density, high strength, and reasonable ductility. • Al 3 Ti-based MEAs showed superior wear resistance to those of Al-30 wt% SiCp composite and Ti6Al4V. • Representative Al 60 Ti 20 Cr 5 Mn 5 Fe 5 Cu 5 is promising for mechanical and tribological applications at medium temperatures.
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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 | 0.000 |
| 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 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".