MétaCan
Menu
Back to cohort
Record W4280526064 · doi:10.2464/jilm.72.115

Effects of Electromagnetic Force on Segregation Phenomena of Primary Crystals and Changes in Solidification Structure of Al-10Fe and Al-25Si Alloys

2022· article· en· W4280526064 on OpenAlexaff
Yosuke Tamura, H. Soda, Alexander McLean, Kentaro Mizuno, K. Takahashi

Bibliographic record

VenueJournal of Japan Institute of Light Metals · 2022
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIngotLiquidusMaterials scienceNucleationEutectic systemDirectional solidificationCrucible (geodemography)Condensed matter physicsCrystallographyMicrostructureMetallurgyAlloyThermodynamicsChemistry

Abstract

fetched live from OpenAlex

In this study, solidification structure changes under electromagnetic force (EMF) were examined for Al-10Fe and Al-25Si alloys. One directional EMF was induced by applying DC currents of 100A and 130A with static magnetic fields. Solidification structure was examined using an optical microscope, X-ray computed tomography, and X-ray fluorescence mapping. When EMF was imposed from above the liquidus temperature, primary crystals were not segregated into one side of the ingots and instead were found to be segregated all along the ingot periphery for both Al-10Fe and Al-25Si. A fine hypo-eutectic structure containing Al dendrites was observed in areas devoid of primary crystals in the central parts of the Al-25Si ingots. These segregation phenomena of primary crystals did not occur when EMF was imposed from the point below the liquidus temperature, suggesting that EMF does not exert an effect on free crystals existing in the liquid metal. It also suggests that segregated primary crystals were not moved towards the periphery by EMF. It may prevent nucleating primary crystals from separating from the wall surface, hence enhancing nucleation on the wall and dense growth of crystals from the wall surface, resulting in a highly segregated solidification structure.

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 score0.011
Threshold uncertainty score0.630

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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Japan Institute of Light MetalsSame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207