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Record W4311448437 · doi:10.2464/jilm.72.631

Initial stage of degradation process of alumina-silica refractory by molten Al-5Mg alloy

2022· article· en· W4311448437 on OpenAlexaff
Yosuke Tamura, H. Soda, Alexander McLean, Ishikawa Takaaki, Michio Ishizuka, Masato Kawasaki, Kentaro Mizuno, Tetsuichi Motegi

Bibliographic record

VenueJournal of Japan Institute of Light Metals · 2022
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceRefractory metalsAlloyCrucible (geodemography)Molten metalRefractory (planetary science)MetallurgyMulliteMetalDegradation (telecommunications)CristobaliteLiquid metalInfiltration (HVAC)Composite materialCeramic

Abstract

fetched live from OpenAlex

Initial stages of the refractory degradation process by molten Al-5Mg alloy were investigated by analyzing the degradation structures caused by an interaction with molten metal during heat cycles. The refractory aggregate, found to be poly-crystalline, consisting of cristobalite (SiO2) and mullite (Al6Si2O13), was deteriorated ahead of the surrounding matrix. Metal permeated into the refractory, forming a thin metal layer along the crucible surface below the molten metal line at an early stage of degradation process, which would later serve as the bases for the metal infiltration path through the refractory above the molten metal line. A discontinuous film (thickness<3μm), most likely MgAl2O4, was formed at the “melt / refractory” interface. At the experimental temperature of 1150°C, Mg in the molten metal would build up as Mg gas at MgAl2O4 film/refractory interface and easily diffuse into the aggregate body and react with the aggregate components of SiO2 and Al6Si2O13 to form MgAl2O4 and Al-Mg-Si-O compounds. This was followed by the molten metal infiltration into the refractory while reducing the Al-Mg-Si-O compound to form MgAl2O4. Through the initial degradation process MgAl2O4 would finally form in a successive chain of reactions, resulting in deterioration of the crucible.

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)0.001
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 score0.063
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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 Alloys Composites PropertiesFrench-language works237,207