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Record W4281662823 · doi:10.4028/p-045ngi

Effect of Sr and Ni Addition on Microstructure, Tensile Behavior and Electrical Conductivity of Squeeze Cast Al-6Si-3Cu Al Alloy

2022· article· en· W4281662823 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

VenueKey engineering materials · 2022
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceAlloyUltimate tensile strengthMicrostructureElectrical resistivity and conductivityIntermetallicMetallurgyConductivityComposite materialDispersion (optics)Electrical engineering

Abstract

fetched live from OpenAlex

Mechanical strengths and electrical conductivity are the very important engineering properties of lightweight aluminum (Al) alloys used in automobiles, especially for battery-powered electric vehicles (BEV). However, the main issue is that the mechanical properties and the electrical conductivity of Al alloys are mutually exclusive. This study aims to simultaneously improve both the tensile properties and the electrical conductivity of the squeeze as-cast Al-6wt% Si-3wt% Cu by modifying its microstructure with the addition of nickel (Ni) and strontium (Sr). In comparison to those of the alloy free of Sr and Ni, the additions of 0.03 wt.% Sr and 0.5 wt.% Ni in the Al-6Si-3Cu alloy significantly improved the ultimate tensile strength, yield strength and electrical conductivity. This was because the addition of Ni element, as a transition element, collaborated with Cu to form fine intermetallic Al-Cu-Ni phases for dispersion strengthening. Also, the modification of the Si morphology from micron needles to nanoparticles by the Sr addition enhanced both the strengths and electrical conductivity of the developed alloy.

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 score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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