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Record W2564406664 · doi:10.1155/2016/7691535

Effect of Sr-P Interaction on the Microstructure and Tensile Properties of A413.0 Type Alloys

2016· article· en· W2564406664 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

VenueAdvances in Materials Science and Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMaterials scienceEutectic systemPrecipitationStrontiumUltimate tensile strengthDissolutionMicrostructureSiliconMagnesiumMetallurgyChemical engineering

Abstract

fetched live from OpenAlex

The present study was performed on low magnesium A413.0 type alloys. The results show that strontium (Sr) is mainly concentrated in the silicon particles. Overmodification occurs when Sr precipitates in the form of Al 2 SrSi 2 , which takes place over a wide range of temperatures. The first peak occurs following the precipitation of α -Al, the second peak is merged with the precipitation of eutectic silicon (Si), and the third peak is a posteutectic reaction. Introduction of phosphorus (P) to Sr-modified alloys leads to the formation of (Al,P,Sr) 2 O 5 compound, which reduces the modification effectiveness of Sr. Therefore, in the presence of P, the amount of added Sr should exceed 200 ppm. For the same levels of P, the tensile parameters of well modified alloys (233 ppm Sr) are relatively higher than those partially modified with Sr (about 60 ppm Sr) containing the same amount of P. During solution heat treatment, coarsening of the eutectic Si particles occurs by the growth of some particles at the expense of the dissolution of the smaller ones, as well as by the collision of nearby particles.

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 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 score0.222

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 head0.005
GPT teacher head0.202
Teacher spread0.198 · 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