Microstructural evolution and constitutive model of dual-phase AlCoCrFeNi2.1 eutectic high-entropy alloy during hot deformation
Bibliographic record
Abstract
Practical applications with potential use of eutectic high entropy alloys (EHEAs) involve thermo-mechanical processing. The hot compression behaviors and microstructure evolution of a dual phase AlCoCrFeNi 2.1 EHEA under various thermo-mechanical conditions were investigated. The initial microstructure comprises lamellar FCC/L1 2 (65.5 %) and BCC/B2 (34.5 %) phases, with L1 2 nanoprecipitates (with an average size of 7.9 nm) uniformly dispersed in the dendritic FCC and the B2 particles (with an average size of 35.8 nm) evenly distributed among the BCC phases. The influence of strain rate and temperature on the evolution of the microstructure is revealed. The evolution of microstructure can be interpreted in terms of the interactions between dynamic softening (dynamic recrystallization) and hardening (work hardening). Elevated deformation temperatures (up to 1473 K) and reduced strain rates (0.001 s −1 ) promote dynamic recrystallization grain-coarsening while decreasing dislocation densities. In addition, twin-mediated dynamic recrystallization nucleation was observed at low strain rates (0.001 s −1 ). The Arrhenius mode and Zerilli-Armstrong plastic model were applied to model the dynamic flow behavior of the dual phase AlCoCrFeNi 2.1 , and the constitutive relationship was obtained. These findings provide critical insights for optimizing thermomechanical processing of dual-phase EHEAs in high-temperature structural applications.
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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".