The influence of precipitation on the microstructure, texture, and mechanical properties of high entropy FeNi1.5CrCu0.5 alloy following cold deformation and annealing
Bibliographic record
Abstract
high-entropy alloy produced by vacuum induction melting. For this purpose, the as-cast samples were homogenized at 1080 °C for 12 h followed by two different annealing regimes: one was rapidly quenched in water, while the other was cooled slowly in the furnace to reach 800 °C. This was held for 48 h at this temperature and quenched in water. The homogenized and precipitated samples were then cold-rolled with an 80 % thickness reduction to be heat-treated at 900 °C and 1000 °C. Annealing the cold-rolled specimens at 1000 °C resulted in significant grain refinement in the precipitated sample compared to the homogenized one. The increase in hardness of the precipitated samples can be attributed to the precipitation hardening process. Conversely, recrystallization during cold rolling leads to a slight decrease in hardness and an increase in formability in the precipitated samples. Following recrystallization, the microstructure of the precipitated sample consists of finer grains, with hardness identical to that of the homogenized sample. The shear punch test, as a unique technique for materials' characterization when there is a limitation in the materials' availability, was utilized and showed the variation of strength and formability due to rolling and annealing processes. Also, texture analysis revealed distinct differences between textural components such as Goss and Brass for the homogenized and precipitated samples upon annealing, confirming variations in recrystallization mechanisms.
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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".