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Record W4399857788 · doi:10.31399/asm.cp.ht2011p0205

Heat Treatment Development for Rapidly Solidified Heat Resistant Cast Al-Si Alloy

2011· article· en· W4399857788 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the ... ASM Heat Treating Society Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsMcGill UniversityToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceDilatometerMicrostructureAlloyMetallurgyCastingUltimate tensile strengthDissolutionDendrite (mathematics)Die castingThermal stabilityThermal expansion

Abstract

fetched live from OpenAlex

Abstract Current heat treatment standards do not adequately define tempers for thin-walled castings that solidify at high rates. Emerging casting processes, such as vacuum high-pressure die casting, benefit from rapid solidification rates, which result in fine microstructures and reduce the need for prolonged solution treatment times. Studies on rapidly solidified samples with secondary dendrite arm spacing between 35-10 μm were conducted, with solution times ranging from 30 minutes to 9 hours, and various aging parameters were evaluated. Metallurgical analysis revealed that increased microstructure refinement could reduce solution time by up to 50% without compromising the alloy’s mechanical properties. The highest strengths, with an ultimate tensile strength of 330 MPa (47.9 ksi) and a yield strength of 300 MPa (43.5 ksi), were achieved under T6 peak aging conditions. Additionally, thermal analysis and dilatometer results are presented to evaluate phase dissolution during solution treatment, aging kinetics, and dimensional stability.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.035
GPT teacher head0.220
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