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Solidification of Discontinuous Al<sub>2</sub>O<sub>3</sub> Fiber Reinforced Magnesium (AM60) Matrix Composite

2011· article· en· W2025206496 on OpenAlexafffund
Qiang Zhang, Henry Hu, Jason Lo

Bibliographic record

VenueDefect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forum · 2011
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsNatural Resources CanadaUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNucleationComposite numberComposite materialMagnesiumFiberDifferential scanning calorimetryGrain growthGrain boundaryScanning electron microscopeMicrostructureMetallurgyChemistry

Abstract

fetched live from OpenAlex

Magnesium matrix composites have great potential for aerospace and automotive applications due to its low density and superior specific stiffness. The magnesium composites can often be reinforced by either particles or/and fibers. There were certain studies on solidification behaviors of particle-reinforced magnesium composites in the past. However, development of grain structure during the solidification of fibre-reinforced magnesium is barely investigated. In this work, an Al2O3 fiber reinforced magnesium (AM60) matrix composite (AM60/Al2O3,f) was cast. The solidification behavior of the cast AM60/Al2O3,f composite was investigated by computer-based thermal analysis. Optical and scanning electron microscopy (SEM) and differential scanning calorimetry (DSC) were employed to examine the occurrence of nucleation and grain refinement involved in solidification of the composite. The results show that the addition of Al2O3 fibers leads to the formation of fine grain structure in the matrix of the AM60/Al2O3,f composite. The refinement of grain structure should be primarily attributed to the restriction of grain growth by the limited cellular space formed in the skeleton of the fiber preform structure instead of the nucleation of primary -Mg phase directly on Al2O3 fibers.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.003
Open science0.0020.007
Research integrity0.0010.001
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 head0.020
GPT teacher head0.238
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueDefect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forumSame topicAluminum Alloys Composites PropertiesFrench-language works237,207