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<i>In Situ</i> Fabrication and Characterization of (NiCr)Al-Al<sub>2</sub>O<sub>3</sub> Nanocomposite by Mechanical Alloying

2012· article· en· W2022700668 on OpenAlex

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

VenueJournal of nano research · 2012
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceNanocrystalline materialNialNon-blocking I/OMicrostructureNichromeTransmission electron microscopyNanocompositeIntermetallicScanning electron microscopeMetallurgyChromiumChemical engineeringComposite materialNanotechnologyAlloy

Abstract

fetched live from OpenAlex

In this research, the formation mechanisms of a (NiCr)Al-Al2O3 nanocomposite were investigated. The structural changes of powder particles during mechanical alloying were studied by X-ray difractometry (XRD) and the morphology and cross sectional microstructure of powder particles were characterized by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The methodology involved mechanical alloying of NiO, Cr, and Al with molar ratios of 3:3:8. During mechanical alloying, NiO was first quickly reduced by aluminum atoms to produce NiAl nanocrystalline and Al2O3. Subsequently, and when a longer milling time was applied, chromium atoms diffused into the NiAl lattice. The heat treatment of this structure led to the formation of the (NiCr)Al intermetallic compound as well as Al2O3 with crystalline sizes of 23 nm and 58 nm, respectively.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.090
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.025
GPT teacher head0.278
Teacher spread0.254 · 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