Plasticity of Mg–Gd alloys between 4 K and 298 K
Bibliographic record
Abstract
Mechanisms of strength and ductility in textured Mg–Gd binary alloys are investigated under conditions of uniaxial tension and compression at 4.2, 78 and 298 K. The alloys obey solution strengthening relationships between the critical stress and the concentration of the solute c, which scales as , with n assuming values 0.30–0.53 for tension and 0.73–0.87 for compression. The results suggest that Gd solute hardens the compressive yield modes more than the tensile yield modes, with basal slip and extension twinning being the principal yielding mechanisms in tension and compression. Temperature dependence of the yield stress and stress suggests contribution of non-basal slip systems to the yielding of alloys. Twinning accounts for more than 80% of sample strain in the first 7% of compression, resulting in characteristic S-shape flow curves with four hardening stages. The work hardening in Stage A is determined by the extension twins propagating throughout primary grains and interacting with grain boundaries. Slip-twin interactions control the work hardening rate during Stage B, whereas slip–slip interactions determine the work hardening in fully twinned materials during Stage C and D. Under tension twining is less active, the plastic flow is associated with Stage III of work hardening, determined predominantly by slip–slip interactions. Increasing Gd concentration in the alloys leads to the reduction of tension–compression asymmetry, in agreement with results in the literature. Addition of Gd influences the failure and promotes ductile, transgranular fracture mode in Mg–Gd alloys down to the low temperatures. It is argued that Gd improves the cohesion strength of grain boundaries, which suppresses intergranular failure and affects favourably ductility of Mg–Gd 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".