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Record W4309820333 · doi:10.1149/ma2022-0211722mtgabs

Effect of the End-of-Life (EOL) Content in High-Pressure Vacuum-Assisted Die Cast (HPVADC) Aural2 (AlSi10Mg) on Corrosion Behaviour

2022· article· en· W4309820333 on OpenAlexaff
Joey Kish, Sumanth Shankar

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAlloyMaterials scienceCastabilityCorrosionMicrostructureIntermetallicMetallurgyPolarization (electrochemistry)

Abstract

fetched live from OpenAlex

Al cast alloys are widely used in automotive applications due to their high strength-to-weight ratio. The castability of Al alloy is known to be excellent; the idea of implementing the End-of-Life (EOL) Al alloy parts to fabricate new Al alloys is determined to be feasible. In contrast, the fabrication of Al cast alloys with the EOL content increases the propensity of introducing the impurity element to the Al cast alloys. It is expected to affect the microstructure such as the distribution and morphology of intermetallic particles. The mechanical properties of those alloys, also known as the secondary alloys, are comparable to primary alloys, however, the corrosion behaviour of secondary alloys is not fully characterized and understood. It is anticipated that the corrosion behaviour is affected by the EOL content introduced to the Al cast alloys. In this research, HPVADC Aural2 alloy with different EOL contents (0%, 40%, 75%, and 90%) are subjected to various electrochemical characterization techniques and microstructure characterization. Cyclic polarization measurements were conducted on both skin and core parts of the alloys. The breakdown potential (Eb) of the primary alloy was found to be the lowest, however, the potential difference between the breakdown (Eb) and repassivation (Er) of the primary alloy was significantly smaller than the secondary alloys. Potentiostatic polarization was also performed on both skin and core parts to observe the corrosion modes, and it was determined that both initiation and propagation corrosion modes were inter-granular/inter-dendritic corrosion. Galvanostatic polarization measurements were performed, and the behaviour of the potential responses differed between the primary and the secondary alloys, as well as the core and skin. Scanning Vibrating Electrode Technique (SVET) will be performed on the cross-section, skin, and core region to observe the local anodic/cathodic current density. The passive layer characteristics of each EOL alloy will be investigated by X-ray Photoelectron Spectroscopy (XPS). Microstructure analysis through Light Optical Microscope (LOM) and Scanning Electron Microscopy (SEM) was conducted. The distribution of Si eutectic and Fe-containing intermetallic particles on the secondary alloys was found to be different from the primary alloy; the mean size of intermetallic particles observed on the skin in the secondary alloys was higher than the primary alloy. No significant difference was observed at the core region in terms of intermetallic distribution. The morphology and chemistry of intermetallic particles will be further investigated with Energy Dispersive Spectroscopy (EDS). This research is conducted to characterize the effect of EOL content on their microstructures which is essential to understand the corrosion behaviour of the secondary alloys, ultimately enhancing the utilization of EOL parts in the Al cast alloy manufacturing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.217
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2022
Admission routes1
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