Evolution of Nanostructure during the Early Stages of Ageing in Al-Zn-Mg-Cu Alloys
Bibliographic record
Abstract
During age-hardening of certain Al-Zn-Mg-Cu alloys, a 90% hardness increase can occur with 75 seconds. The clustering and precipitation of solute element species during this early rapid hardening (RH) period has been investigated through atom probe tomography, transmission electron microscopy, and Vickers hardness measurements. This study has focussed on the effect of copper by analysing three alloys; Al-2.0Zn-1.8Mg-0.7Cu, Al-2.0Zn-1.7Mg-0.2Cu and Al-1.9Zn-1.7Mg (at.%). The early RH reaction in these alloys accounts for up to 70% of the total hardening (peak hardness minus as-quenched hardness) and takes place during the first 60 seconds of ageing. We report preferred solute-solute interactions in the as-quenched materials. This quenched-in nanostructure acts as a template for subsequent solute clustering, the nature of which we have correlated with ageing.
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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) | 0.000 | 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".