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Characterization of Phase Formation in Al-20%Mg<sub>2</sub>Si-2%Cu Metal Matrix Composite

2017· article· en· W2756327517 on OpenAlexaff
Nur Azmah Nordin, Tuty Asma Abu Bakar, Esah Hamzah, Saeed Farahany, Ali Ourdjini

Bibliographic record

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2017
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceEutectic systemComposite numberLamellar structureIntermetallicMicrostructurePhase (matter)Composite materialMetal matrix compositeMetalScanning electron microscopeIn situMetallurgyAlloy

Abstract

fetched live from OpenAlex

Advantage of Al-Mg2Si metal matrix composite (MMC) is due to the particulate reinforced Mg2Si in the Al matrix that has improved mechanical properties of the in situ composite. In particular, the composite has been chosen as the structural material for automotive and aerospace components. The hypereutectic Al-Mg2Si composite should be comprised of two morphologies, namely primary Mg2Si and pseudo-eutectic Al-Mg2Si phase. However, as-received commercial Al-20Mg2Si-2Cu in situ composite contained a wide range of elements that affect the resultant microstructure of the in situ composite. In fact, four different morphologies have been identified in the in situ composites. The first phase is dark facet primary Mg2Si particles, surrounded by pseudo-eutectic Al-Mg2Si phase in lamellar structure. Along the eutectic boundary is the formation of needle-like Al5FeSi intermetallic and the phase is surrounded by Al5Mg8Si6Cu2+Al2Cu as last phase nucleated. Optical micrograph, SEM imaging, EDX analysis and elemental mapping have revealed these phases correspond to shape of morphologies and respective molecular compound.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.029
GPT teacher head0.283
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2017
Admission routes1
Has abstractyes

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Same venueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomenaSame topicAluminum Alloys Composites PropertiesFrench-language works237,207