Differential effects of Ti addition on microstructure and corresponding mechanical and tribological properties of AlCr3Fe3NiTix high-entropy alloys
Bibliographic record
Abstract
High-entropy alloys (HEAs), particularly those with an A2+B2 dual-phase structure, offer balanced strength and toughness, leading to superior and well-adjustable wear resistance. The effect of titanium, known to promote the formation of hard intermetallic phases and enhance mechanical properties, on A2+B2 dual-phase HEAs remains less understood. In this work, selecting a representative AlCr 3 Fe 3 Ni alloy with A2+B2 phases as the base alloy, we systematically investigated the phase evolution induced by various amounts of Ti addition and their differential effects on the sliding wear and solid-particle erosion of AlCr 3 Fe 3 NiTi x HEAs (x = 0–1.5, molar ratio). Microstructural analysis reveals that Ti addition promotes the formation of AlNi 2 Ti-type L2 1 and (Fe,Cr) 2 Ti-type C14 Laves phases, both of which strengthen the alloys at the expense of plasticity. However, a low Ti content (i.e., x = 0.2) helps improve both yield strength and plasticity, due to the solid-solution strengthening effect and refinement of grain size. Micro-indentation and scratching tests demonstrate that the C14 Laves phase exhibits the highest hardness but the lowest toughness, whereas the A2+B2 dual-phase structure possesses the highest toughness but the lowest hardness. The L2 1 phase displays intermediate properties between the two. Sliding wear and dry-sand erosion tests reveal that moderate Ti additions enhance wear resistance through solid-solution strengthening, hard-phase reinforcement, and oxidation-induced surface protection. However, erosion resistance deteriorates with increasing Ti content, primarily due to lowered toughness under impact conditions. This study elucidates the dual roles of Ti-induced hard yet brittle phases, i.e., beneficial for sliding wear resistance but detrimental to erosion performance in impact-involving environments requiring higher toughness. The findings provide valuable insights into structure-property relationships for the design of advanced structural and tribo-materials.
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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".