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Effect of Sc and Zr alloying on microstructure and precipitation evolution of as cast Al–B<sub>4</sub>C metal matrix composites

2012· article· en· W2041651092 on OpenAlex
Junjie Lai, Z Zhang, X.-G. Chen

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials Science and Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMicrostructurePrecipitationPrecipitation hardeningMatrix (chemical analysis)Composite materialMetalOptical microscopeMetallurgyScanning electron microscope

Abstract

fetched live from OpenAlex

Additions of Sc and Zr were introduced into Al–15 vol.-B 4 C composites, and eight experimental composites with different Sc and Zr levels were prepared via a conventional cast process. Optical microscopy, SEM and TEM were applied for observing the as cast microstructures, including the interfaces between the Al matrix and the B 4 C as well as the evolution of the precipitates. It was found that Sc involved the interfacial reactions with B 4 C that partially consumed the Sc. On the other hand, no major Zr reaction products were found in the interfaces, and the major part of Zr remained in the matrix for precipitation strengthening. The Sc addition yielded considerable precipitation strengthening in the as cast and peak aged conditions. The combination of Sc and Zr significantly enhanced the precipitation strengthening. Nanoscale precipitates Al 3 Sc and Al 3 (Sc,Zr) were found in the as cast microstructure and contributed to the significant increase of matrix hardness.

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 score0.005
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.003
GPT teacher head0.211
Teacher spread0.208 · 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