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Record W4410472031 · doi:10.1016/j.matlet.2025.138784

Effect of solution heat treatment on the microstructure of hot-rolled Al-Mg-Si 6xxx alloy microalloyed with Sc and Zr

2025· article· en· W4410472031 on OpenAlexafffund
S. Gashtiazar, E. M. Elgallad, Behrouz Abnar, Mousa Javidani, Alexandre Maltais, X.-G. Chen

Bibliographic record

VenueMaterials Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsRio Tinto (Canada)Université du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaRio Tinto
KeywordsMaterials scienceMicrostructureAlloyMetallurgyHot rolled

Abstract

fetched live from OpenAlex

Developing high-strength, thermally stable Al-Mg-Si 6xxx alloys with Sc and Zr is challenging due to mismatched heat treatment requirements between Al-Mg-Si and Al-Sc-Zr systems. This study investigated how solution treatment temperature affects the balance between Mg-Si precipitates and Al 3 (Sc,Zr) dispersoids—key contributors to strength and thermal stability—in an Al-0.67Mg-0.67Si-0.5Cu-0.08Sc-0.08Zr alloy. Two solution treatments were conducted at 500 and 530 °C for 15 min. Solutionizing at 500 °C reduced β″ precipitation compared to that at 530 °C but maintained fine Al 3 (Sc,Zr) dispersoids, which coarsened and dissolved at 530 °C. Thus, the 500 °C treatment can offer a more favorable balance of strength and thermal stability for dual-property optimization in Sc- and Zr-modified 6xxx alloys.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.184
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2025
Admission routes2
Has abstractyes

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