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Record W2336728148 · doi:10.1177/0021998315613126

Metallographic investigation of tensile- and impact-tested aluminum composites

2015· article· en· W2336728148 on OpenAlexafffund
MF Ibrahim, Hany R. Ammar, S. Alkahtani, FH Samuel

Bibliographic record

VenueJournal of Composite Materials · 2015
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialFractographyMicrostructureUltimate tensile strengthPrecipitation hardeningScanning electron microscopePrecipitationPhase (matter)Strengthening mechanisms of materialsToughnessAluminium

Abstract

fetched live from OpenAlex

The present work was performed on two composites: Al-15 vol.% B 4 C and experimental 6063/15% B 4 C. Additions of 0.45% Ti + 0.25% Zr were made to both composites melts. The composites were cast from the respective melts at 730℃ using two metallic molds to produce tensile as well as impact test samples. All samples were solution heat treated for 24 h at 540℃ for both composites, followed by aging at 200℃ for 10 h. Samples for microstructure and fractography were examined using field emission scanning electron microscopy. The results show that the powder injection technique used in this study produces composites with B 4 C uniformly distributed throughout the matrix. The strength and impact toughness of the two composites are controlled by the simultaneous precipitation of Al 3 Zr and Mg 2 Si phase particles depending on the matrix type. Hardening caused by precipitation of Mg 2 Si is more pronounced than that caused by Al 3 Zr phase precipitation. No B 4 C particle debonding was observed due to the presence of Zr-/Ti-rich layers surrounding the B 4 C particles. The cracks mainly propagate through the B 4 C reinforcement particles.

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 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)0.001
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 score0.023
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.225
Teacher spread0.203 · 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 teacher head, 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".

Quick stats

Citations6
Published2015
Admission routes2
Has abstractyes

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