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Record W2563574657 · doi:10.1002/srin.200705860

Corrosion Resistance of Reactive Element Aluminide Diffusion Coatings on a Nickel‐based Superalloy and an Austenitic Stainless Steel

2007· article· en· W2563574657 on OpenAlexaff
Abdel Raouf Elsawy, H. Soda, Alexander McLean

Bibliographic record

Venuesteel research international · 2007
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceMetallurgyAluminideCorrosionSuperalloyNickel aluminideCoatingAlloyChromiaIntermetallicComposite materialNial

Abstract

fetched live from OpenAlex

Continuously cast aluminium alloy wires containing active elements such as yttrium, cerium, lanthanum or silicon were used as evaporation sources for ion vapour deposition on nickel‐based Inconel IN738 and stainless steel 310S substrate materials. The samples were subsequently diffusion heat‐treated to form protective corrosion resistant nickel aluminide and iron aluminide coatings. The coated alloy materials were exposed for prolonged periods to high temperature cyclic oxidation, molten sulphate, and molten carbonate environments to evaluate their resistance to hot oxidation. For IN738, the lanthanum‐modified aluminide coating provided good thermal cyclic oxidation performance while the cerium‐modified coating exhibited effective hot corrosion resistance in a molten sulphate environment. For 310S stainless steel, all of the modified aluminide coatings provided equally good corrosion protection when exposed to molten carbonate attack under an oxidizing atmosphere.

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 score0.004
Threshold uncertainty score0.007

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 head0.044
GPT teacher head0.344
Teacher spread0.301 · 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
Published2007
Admission routes1
Has abstractyes

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