Phase Stability, Microstructure, and Mechanical Properties of Spark Plasma Sintered Nanocrystalline Boron-Doped AlCoFeMnNi High-Entropy Alloy
Bibliographic record
Abstract
The microstructure and mechanical properties of mechanically alloyed and spark plasma sintered AlCoFeMnNi-xB (x = 0, 0.5, 1, and 5 at. %) high-entropy alloys (HEAs) have been investigated. Boron-doped HEAs were synthesized using mechanical alloying up to 50 h of milling. Synthesized powders were then consolidated at 850, 900, and 950 °C for 10 min under a uniaxial pressure of 40 MPa using spark plasma sintering (SPS). A scanning electron microscope, which was equipped with energy dispersive spectroscopy (EDS), together with an optical microscope (OM) were used to analyze the microstructural evolution. X-ray diffraction analysis was used to differentiate the phases formed in the solution. The mechanical properties of the sintered specimens were analyzed using the shear-punch test (SPT). The fracture surface of the SPT samples was studied using SEM. Thermodynamic calculations revealed that by employing this process, it is possible to produce solid solution HEAs with a duplex FCC + BCC structure. It was shown that boron-doped AlCoFeMnNi high-entropy alloys contain some unique attributes. SPS at 900 °C for a sample with boron up to 0.5 at. % leads to the formation of an alloy with the highest shear strength. A further increase in the boron content in the boron-doped HEAs exhibited a decrease in the maximum shear strength. Finally, the correlations between the microstructural and mechanical characteristics of the sintered boron-containing high-entropy alloys are discussed.
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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".