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Record W4303832620 · doi:10.3390/ma15196903

Effect of Bi and Ca on the Solidification Parameters of Sr-Modified Al-S-Cu (Mg) Alloys

2022· article· en· W4303832620 on OpenAlexaff
Shimaa El‐Hadad, A. M. Samuel, F. H. Samuel, H. W. Doty, Victor Songméné

Bibliographic record

VenueMaterials · 2022
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à MontréalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsEutectic systemMaterials sciencePorosityIntermetallicAlloyScanning electron microscopeMetallurgyCastingShrinkageThermalAnalytical Chemistry (journal)Composite materialChemistryThermodynamics

Abstract

fetched live from OpenAlex

The effect of tramp elements, mainly Bi and Ca, on the thermal characteristics of Sr-modified Al–Si–Cu and Al–Si–Cu–Mg alloys has been investigated using thermal analysis, X-ray radiography, and field emission scanning electron microscopy (FESEM) techniques. The high affinity of Bi to interact with Sr results in an increase in the Al-Si eutectic temperature, and hence an increase in the size of eutectic silicon particles. In contrast, the Ca–Sr interaction seems to have no significant effect on the alloy thermal behavior. The effect of these interactions on porosity formation has been discussed. Hot zones may be formed in thin cavities, in particular, near the bottom of the mold, leading to formation of unexpected coarse porosity, mostly shrinkage type. The study also highlights the significance of other parameters on porosity formation, such as no melt degassing, SrO, Al2O3 (strings or bifilms), as well as the presence of iron-based intermetallics.

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 score0.002
Threshold uncertainty score0.304

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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