Microstructure Optimization of Mg-Alloys by the ECAP Process Including Numerical Simulation, SPD Treatments, Characterization, and Hydrogen Sorption Properties
Bibliographic record
Abstract
Both numerical simulation and hardness measurements were used to determine the mechanical and microstructural behavior of AZ31 bulk samples when submitted to the Equal Channel Angular Pressing (ECAP) technique. Billets of this representative of Mg-rich alloys were submitted to different numbers of passes for various ECAP modes (anisotropic A, isotropic BC). The strain distribution, the grain size refinement, and the micro-hardness were used as indicators to quantify the effectiveness of the different processing routes. Structural characterizations at different scales were achieved using Scanning Electron Microscopy (SEM), micro-analysis, metallography, Small Angle Neutron Scattering SANS, X-Ray Diffraction (XRD), and texture determination. The grain and crystallite size distribution and orientation as well as defect impacts were determined. Anelastic Spectroscopy (AS) on mechanically deformed samples have shown that the temperature of ECAP differentiate the fragile to ductile regime. MgH2 consolidated powders were checked for using AS to detect potential hydrogen motions and interaction with host metal atoms. After further optimization, the different mechanically-treated samples were submitted to hydrogenation/dehydrogenation (H/D) cycles, which shows that, for a few passes, the BC mode is better than the A one, as supported by theoretical and experimental microstructure analyses. Accordingly, the hydrogen uptake and (H/D) reactions were correlated with the optimized microstructure peculiarities and interpreted in terms of Johnson-Avrami- Mehl-Kolmogorov (JAMK) and Jander models, successively.
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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".