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Record W2766017728 · doi:10.1080/00325899.2017.1391504

Microstructural behaviour of spark plasma sintered composites containing bimodal micro- and nano-sized Al <sub>2</sub> O <sub>3</sub> particles

2017· article· en· W2766017728 on OpenAlexaff
Behzad Sadeghi, M. Shamanian, F. Ashrafizadeh, Pasquale Cavaliere, Mohsen Sanayei, Jerzy A. Szpunar

Bibliographic record

VenuePowder Metallurgy · 2017
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
Fundersnot available
KeywordsSpark plasma sinteringMaterials sciencePowder metallurgyComposite materialAluminiumNano-SPARK (programming language)SinteringMatrix (chemical analysis)MetalAluminium powderMetallurgy

Abstract

fetched live from OpenAlex

Spark plasma sintering (SPS) has been recognised, in the recent past, as a very useful method to produce metal matrix composites with enhanced properties if compared with traditional powder metallurgy techniques. Obviously, the materials final properties are strongly related to the reinforcement types and percentages as well as to the processing parameters employed during synthesis. The present paper analyses the effect of microscopic and nanometric alumina particles, blended to pure aluminium in different combinations, on the final properties of metal matrix composites produced via SPS. A strong variation in the microstructural behaviour has been observed by varying the nano to micro alumina particles percentage blended with aluminium ones.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.014
GPT teacher head0.215
Teacher spread0.200 · 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".

Quick stats

Citations32
Published2017
Admission routes1
Has abstractyes

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