Computational assessment of solute segregation at twin boundaries in magnesium: A two-factor model and solute effect on strengthening
Bibliographic record
Abstract
This work presents a comprehensive first-principles density functional theory (DFT) study of solute segregation at {101¯1} and {101¯2} twin boundaries (TBs) in Mg. A total of 56 solute elements were investigated. For each solute element, the preferential segregation sites at two TBs were identified and the associated segregation energies were computed. A two-factor model that considers both lattice strain and electronegativity, representing the mechanical and chemical effects respectively, has been proposed to predict the solute segregation energy. The model prediction shows good agreement with the DFT calculation. It was found that the mechanical effect dominates the solute segregation energy. However, depending on the site of segregation, the chemical effect can become sizable to warrant consideration. The degree of solute segregation at TBs at different temperatures was then quantified by calculating the solute concentration at TBs at different temperatures. The effect of solutes in either strengthening or weakening the TB was also evaluated. The results provide a basis for selecting promising solutes in the development of new high-performance Mg 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".