MétaCan
Menu
Back to cohort
Record W4405373801 · doi:10.4028/p-6mkfsi

Cooling, Microstructure and Properties of Permanent Steel Mold Cast Wrought AZ80 Alloy with Varying Casting Wall Sizes

2024· article· en· W4405373801 on OpenAlexaff
Wutian Shen, Anita Hu, Henry Hu

Bibliographic record

VenueMaterials science forum · 2024
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceMicrostructureMetallurgyMoldCastingAlloySand castingComposite material

Abstract

fetched live from OpenAlex

The wrought magnesium alloy AZ80, comprising 8 wt% aluminum, underwent fabrication via permanent steel mold casting (PSMC), involving three distinct stages with wall sizes measuring 6 mm, 10 mm, and 20 mm. The numerical simulation of the solidification showed that the cooling rate of the step casting increased, when the wall size decreased. The as-cast alloy's microstructure underwent scrutiny through optical microscopy and scanning electron microscopy (SEM), complemented by energy dispersive spectroscopy (EDS) analysis. Findings from the microstructure examinations unveiled the presence of primary Mg phase across all three sections of the cast AZ80 alloy, accompanied by micron and nanosized Mg-Al-Zn intermetallic phases, as well as micron-sized Al-Mn intermetallic phases. But the intermetallic contents increased, and the dendrite sizes and the porosity levels decreased, as the wall sizes reduced. The tensile testing results revealed significant findings regarding the ultimate tensile strength (UTS), yield strength (YS), modulus, resilience, and toughness, increased, when the wall sizes decreased to 6 from 20 mm. The negative effect of large casting wall sizes on ductility was demonstrated. Exceptional tensile properties of the thin wall resulted from fine dendritic structure, high intermetallic content, and minimal porosity level.

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 score0.003
Threshold uncertainty score0.006

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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMaterials science forumSame topicAluminum Alloys Composites PropertiesFrench-language works237,207