Early-Stage Precipitation Phenomena and Composition-Dependent Hardening in Al-Mg-Si-(Cu) Alloys
Bibliographic record
Abstract
Al-Mg-Si-(Cu), i.e. AA6xxx, alloys are widely used light alloys which can be effectively strengthened through precipitation hardening. The final microstructure, and thus properties, of these alloys after common artificial aging treatments are largely determined by the composition-dependent nano-scale clustering and precipitation that occur during the earliest stage of aging. Therefore, multi-length scale analysis of the earliest-stage of precipitation can provide critical knowledge in understanding the basis for the microstructural evolution during aging and attaining the desired microstructures and properties. Here, we investigate the effect of alloy composition on the evolution of early-stage clusters and precipitates during aging at 180°C using high resolution transmission electron microscopy. The results map a sequential evolution of clusters with an FCC structure but different morphology/orientation characteristics. GP-zones with structures other than FCC, also form in the early stages of aging. The composition-dependent kinetics of β” phase precipitation and hardening behavior are discussed in light of the results from differential scanning calorimetry experiments, microhardness measurements, and conventional transmission electron microscopy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".