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Aging characteristics of the Al-Si-Cu-Mg cast alloy modified with transition metals Zr, V and Ti

2016· article· en· W2314924384 on OpenAlex
Frank Czerwiński, S.K. Shaha, W. Kasprzak, J. Friedman, D.L. Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsToronto Metropolitan UniversityNatural Resources Canada
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceAlloyIsothermal processMetallurgyEutectic systemCastingSofteningComposite materialThermodynamics

Abstract

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The hypoeutectic Al-7Si-1Cu-0.5Mg base alloy was modified with different contents of Zr, V and Ti. The wedge-shape samples with varying solidification rates during casting were subjected to isochronal aging at temperatures up to 500 °C. Moreover, as-cast and solution treated alloys were subjected to long-term isothermal aging at 150°C. As a reference, the A380 alloy, seen as commercial standard for the automotive application target, was used. The modified alloys exerted different aging characteristics than the A380 grade with higher peak hardness and lower temperature of alloy softening. Besides, the influence of the applied solidification rates on hardness after aging was less pronounced in modified alloys than in the A380 grade. For three combinations of Zr, V and Ti tested with contents of individual elements ranging from 0.14 to 0.47%, no essential differences in aging characteristics were recorded. The results are discussed in terms of the role of chemistry and heat treatment in generating precipitates contributing to the thermal stability of Al based alloys.

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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 score0.010
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.177
Teacher spread0.167 · 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