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 OpenAlexaff
Shigeru Saito, Toshiyuki Takashima, Katsumi Miyama, Toshio Narita, Linruo Zhao

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.

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 score0.004

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)0.0010.000

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

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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueMATERIALS TRANSACTIONSSame topicIntermetallics and Advanced Alloy PropertiesFrench-language works237,207