Effects of Al or Mo Addition on Microstructure and Mechanical Properties of Fe-Rich Nonequiatomic FeCrCoMnNi High-Entropy Alloy
Bibliographic record
Abstract
In this work, a Fe-rich nonequiatomic Fe40Cr15Co15Mn10Ni20 high-entropy alloy was successfully prepared based on phase analysis and cost reduction. Fe40Cr15Co15Mn10Ni20 high-entropy alloy with a single-phase face-centered cubic (FCC) structure was strengthened by the addition of 11 at.% Al or 10 at.% Mo, and the variations of phase and mechanical properties of the strengthened alloys were subsequently investigated. It has been found that the addition of 11 at.% Al led to the formation of FCC and body-centered cubic (BCC) dual-phase structure in the Fe40Cr15Co10Mn4Ni20Al11 alloy, while its yield strength (σ0.2) and tensile strength increased from 158 ± 4 MPa and 420 ± 20 MPa to 218 ± 7 MPa and 507 ± 16 MPa, respectively, as compared to the single-phase FCC structure Fe40Cr15Co15Mn10Ni20 alloy. The addition of 10 at.% Mo introduced intermetallic compounds of μ and σ phases, which resulted in improved yield strength of 246 ± 15 MPa for the Fe40Cr15Co10Mn5Ni20Mo10 alloy. However, the alloy exhibited premature brittle fracture due to the existence of a large number of intermetallic compounds, which led to deteriorated tensile strength of 346 ± 15 MPa. The findings of this work suggest that the introduced secondary phases by the addition of Al and Mo can effectively strengthen the high-entropy alloy; however, the number of intermetallic compounds should be controlled to achieve a combination of high strength and good ductility, which provides a reference for the follow-up study of nonequiatomic high-entropy alloys.
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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".