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Metallurgical parameters controlling matrix/B<sub>4</sub>C particulate interaction in aluminium–boron carbide metal matrix composites

2013· article· en· W1998514339 on OpenAlexaff
M. F. Ibrahim, Hany R. Ammar, A. M. Samuel, Mahmoud S. Soliman, F. H. Samuel

Bibliographic record

VenueInternational Journal of Cast Metals Research · 2013
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNational Plan for Science, Technology and Innovation
KeywordsMaterials scienceBoron carbideAlloy6063 aluminium alloyAluminiumMetallurgyScanning electron microscopeComposite materialCastingBoronMetalMetal matrix compositeCarbideField emission microscopy

Abstract

fetched live from OpenAlex

Two base matrixes of Al–15 vol.-%B4C and 6063–15 vol.-%B4C metal matrix composites (MMCs) were produced using a powder injection technique. Alloying element additions of 0·5 wt-%Ti, 0·35 wt-%Zr and 0·35 wt-%Sc were added to the base matrixes to produce various alloy compositions of Al–15 vol.-%B4C and 6063–15 vol.-%B4C MMCs. The production route of the MMCs used in the current project was the molten metal processing technique using powder injection. For the purpose of investigating the reinforcement (B4C)/matrix (Al) interaction, five alloy compositions of pure Al–15 vol.-%B4C and 6063–15 vol.-%B4C with various additions of Ti, Zr and Sc were produced. A metallic L shaped mould was used for casting the aluminium MMCs. Reinforcement/matrix interface interactions in the produced composites were investigated, using a field emission gun scanning electron microscope and energy dispersive X-ray techniques, as a function of alloying element addition.The powder injection technique used in the present work was proven to be very effective in producing Al–B4C MMCs and 6063–B4C MMCs with B4C concentrations of 15 vol.-%. The produced MMCs show a uniform distribution of the reinforcement of B4C in the aluminium matrix. In the alloys free from Ti, Zr and Sc, the B4C particles decompose into other products such as AlB2, Al4C3, Al3BC and/or Al3B48C2 due to the reaction between the reinforcement and the aluminium matrix. In alloys containing Zr and Ti, the B4C particles react with these elements forming Zr and Ti rich phases, which accumulate in layers that encircle the reinforcement particles and act as protective layers that protect the B4C particles from decomposition by preventing their reaction with the aluminium matrix. Sc displays the same positive effect as Ti and Zr in forming protective layers of Sc rich phases surrounding the B4C particles and protects them from decomposition. Scandium, however, is not recommended as an alloying element in this case due to its high cost, and as its effect could be attained using cheaper elements such as Ti and Zr.

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 score0.004

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 head0.041
GPT teacher head0.336
Teacher spread0.295 · 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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Citations19
Published2013
Admission routes1
Has abstractyes

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