Orientation-dependence of incipient plasticity in a coarse-grained Mg revealed by nanoindentation pop-ins
Bibliographic record
Abstract
• We employed nanoindentation across a broad spectrum of crystallographic orientations in a Mg-2wt% Gd alloy to elucidate the influence of orientation on the onset of plasticity, i.e., pop-in events. • We demonstrated orientation-dependent pop-in events in a Mg alloy, providing new insights into how various slip systems—including basal 〈a〉, prismatic 〈a〉, and pyramidal 〈c + a〉—activate to induce incipient plasticity within different grains. • We reported a successive pop-in phenomenon, for the first time in Mg, in grains near (0001) orientations, which we attribute to the formation of basal-pyramidal dislocation locks. The nanoindentation pop-in behaviors of 13 grains with diverse crystallographic orientations were analysed using a coarse-grained Mg-2 wt.% Gd alloy. Within nanoscale stressed volumes within all grains, the converted shear stresses for the first pop-in, calculated using the indentation Schmid factor, ranged from 1 to 1.3 GPa, consistent with theoretical predictions for dislocation nucleation in Mg. The estimated activation volume of the first pop-in was approximately 27–40 ų (involving about ∼2 atoms), aligning with reported atomistic simulations of the surface dislocation semi-loop nucleation. While indented near the ⟨c⟩-axis, grains exhibit higher first pop-in loads and successive pop-ins, implying the possibility of a cross-slip nucleation mechanism to accommodate ⟨c⟩-axis deformation.
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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".