MétaCan
Menu
Back to cohort

Microstructural Characterization and Mechanical Properties Investigation of Nemalloy HE700 alloy: Effect of Pre-Solidified Grains

2023· article· en· W4323645346 on OpenAlexaff
Tariq Aziz, Kumar Sadayappan, A.B. Phillion, Sumanth Shankar

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsMcMaster University Medical CentreMcMaster University
Fundersnot available
KeywordsMaterials scienceEutectic systemAlloyMicrostructureMetallographyCastingMetallurgyUltimate tensile strengthCharacterization (materials science)PrecipitationLiquid metalComposite materialDie castingNanotechnology

Abstract

fetched live from OpenAlex

Abstract Structural plate castings of Nemalloy HE700 alloy, an Al-Fe eutectic alloy system with Zn and Mg as precipitation strengtheners were produced through high vacuum high pressure die casting (HVHPDC) and designed as an alternative to existing structural automotive materials. Cast materials are subject to the existence of pre-solidified grains (PSG) within the microstructure that originate from external solidification in the liquid melt and cause defects in the final cast components. In the case of HPDC, these PSG emerge in the shot sleeve and are injected through the gating system, influencing liquid metal flow behaviour and solidification characteristics. The extent of PSG and their distribution were manipulated through the altering of process route parameters such as shot delay intervals. Quantitative metallography and the effect of PSGs on the uniaxial tensile properties for the Nemalloy HE700 alloy are presented in this publication.

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 score0.027
Threshold uncertainty score0.722

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 communication0.0000.001
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 head0.012
GPT teacher head0.194
Teacher spread0.182 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Materials Science and EngineeringSame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207