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Cast joining of cast iron to aluminium casting matrix

2011· article· en· W2021472883 on OpenAlex
Elmira Moosavi‐Khoonsari, F. Jalilian, F. Paray, D. Emadi, R. A. L. Drew

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

VenueMaterials Science and Technology · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsMaterials scienceCast ironCoatingAlloyInsert (composites)Indentation hardnessMetallurgyAluminiumMicrostructureComposite material

Abstract

fetched live from OpenAlex

The present study focused on reinforcing Al–Si–Cu alloy with a cast iron insert and using Zn– xAl–3Si–0·5Mg (wt-) intermediate alloys by the cast joining technique to take advantage of lightness and stiffness of the hybrid structure. The experimental set-up consisted of coating the insert using hot dipping method followed by immersing the coated insert into the Al melt and allowing the system to cool down to the room temperature. The quality of Al–Fe joints in terms of morphology, thickness, chemistry and microhardness was evaluated as a function of coating composition and immersion time in the Al melt. Characteristics of reaction layer at the coating/insert interface and its effects on the joint properties were determined using microstructural analysis and thermodynamic calculations. Combination of a suitable coating containing 27 wt-Al and optimised process parameters, including 1 min immersion time, resulted in the formation of an Al–Fe joint with promising characteristics.

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 score0.051
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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