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Record W2600570072 · doi:10.1002/adem.201700064

Effect of Severe Plastic Deformation and Subsequent Silicon Spheroidizing Treatment on the Microstructure and Mechanical Properties of an Al–Si–Mg Alloy

2017· article· en· W2600570072 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

VenueAdvanced Engineering Materials · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsMcMaster University
FundersMinistry of Education, IndiaDeakin University
KeywordsMaterials scienceAlloySevere plastic deformationMicrostructureDuctility (Earth science)ExtrusionMetallurgySiliconDeformation (meteorology)Redistribution (election)Composite materialCreep

Abstract

fetched live from OpenAlex

This study investigated the synergetic effects of severe plastic deformation and subsequent heat treatment on the characteristics of an A356 alloy. The severe deformation by accumulative back extrusion (ABE) at 300 °C substantially refined the α–Al primary phase and Si particles, but did not homogeneously redistribute the Si particles. ABE also improved the strength but did not enhance the ductility. To make a compromise between strength and ductility, a subsequent heat treatment at 540 °C was carried out. It was shown that severe plastic deformation substantially accelerated the silicon spheroidization. Heat treatment increased the ductility of the material from ∼8% (in the deformed condition) to ∼15%. This was discussed with emphasis on restoration of the matrix, spheroidization of the Si particles, and redistribution of the Si particles within the α–Al matrix.

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 score0.001
Threshold uncertainty score0.465

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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