MétaCan
Menu
Back to cohort
Record W4252044295 · doi:10.2320/matertrans.m2014350

Formation of Inter-Diffusion Layer between NiCrAlY Coating and Nb Substrate during Vacuum Heat-Treatment

2015· article· en· W4252044295 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

VenueMATERIALS TRANSACTIONS · 2015
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceLayer (electronics)Diffusion layerIsothermal processDiffusionElectron microprobeCoatingSubstrate (aquarium)MicrostructureVacuum arcMetallurgyPhase (matter)Deposition (geology)Composite materialAnalytical Chemistry (journal)CathodeThermodynamicsChemistryChromatography

Abstract

fetched live from OpenAlex

The formation of the inter-diffusion layer between NiCrAlY coating and Nb substrate during vacuum heat treatment was investigated. A NiCrAlY coating was applied on Nb substrate by cathode arc deposition. Vacuum heat treatments were carried out at 800, 900, and 1000°C for 2 h. SEM, EPMA, EDS, and XRD were performed to analyze the microstructure of the inter-diffusion layer and the results were interpreted using the 1002°C isothermal ternary Nb-Ni-Cr phase diagram. It was found that at 800°C the inter-diffusion layer has a single NbNi3 layer; at 900°C the inter-diffusion layer consists of an outer NbNi3 layer, a thin intermediate NbCr2(HT) layer, and an inner Nb7Ni6 layer; at 1000°C the inter-diffusion layer has three well-developed layers of an outer NbNi3 layer, an inner Nb7Ni6 layer, and an intermediate layers comprising NbCr2(HT) and NbNi3. A small amount of Cr exists in both the NbNi3 and the Nb7Ni6 phases as solid solution, and a large amount of Ni in the NbCr2(HT) phase as solid solution.

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 score0.020
Threshold uncertainty score0.399

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 studies0.0000.000
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 head0.035
GPT teacher head0.233
Teacher spread0.198 · 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