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Record W4407186637 · doi:10.1016/j.tca.2025.179951

Thermal analysis and characterization of cast 6061 aluminum alloy microstructures with elevated iron content

2025· article· en· W4407186637 on OpenAlex

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.

Bibliographic record

VenueThermochimica Acta · 2025
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsHamilton Health SciencesUniversity of Waterloo
Fundersnot available
KeywordsAlloyMicrostructureAluminiumMetallurgyCharacterization (materials science)Materials scienceCast ironThermal analysisThermalNanotechnologyThermodynamics

Abstract

fetched live from OpenAlex

• Iron influences the presence and amount of eutectic melting in 6061 aluminum alloy. • Iron content affects the fraction solid corresponding to α-Al dendrite coherency. • Iron addition of 1 wt% results in earlier dendrite coherency via Al 3 Fe formation. • Slower cooling of alloys containing 1 wt% iron results in increased Al 3 Fe formation. When considering the recycling of aluminum alloys, one of the most pervasive impurity elements is iron. In the aluminum-magnesium-silicon system, the presence of iron can lead to the formation of a number of intermetallic phases in the microstructure, some of which can be quite deleterious due to their associated morphology. Since magnesium and silicon are responsible for the ageing response of 6xxx-series aluminum alloys, it is important to understand the phase formations that occur and consume these elements due to the addition of recycling impurities. Thermal analysis can be a beneficial tool in determining the influence of composition on phase formation, and the various stages of alloy solidification. The present study uses thermal analysis testing and microstructure characterization to assess the influence of iron impurity content on the melting and solidification behaviour of a model 6061 cast aluminum alloy. Using differential scanning calorimetry, the melting of eutectics present in the as-cast microstructures was measured; and coupled with peak deconvolution, the influence of iron on the presence of binary and ternary eutectics involving silicon, Mg 2 Si, α-AlFeSi and Al 3 Fe was determined. During controlled cooling, the influence of iron on temperatures corresponding to critical stages of solidification were determined and it was observed that the addition of 1 wt percent iron to the 6061 aluminum alloy caused a delay in the observed aluminum dendrite coherency, but that an earlier dendrite coherency point was established through the bridging of growing aluminum dendrites via the formation of Al 3 Fe intermetallic phase with aluminum.

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.

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 score0.297
Threshold uncertainty score0.813

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 studies0.0000.000
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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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