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Record W4309878751 · doi:10.1007/s11661-022-06896-8

The Isothermal Oxidation of a New Polycrystalline Turbine Disk Ni-Based Superalloy at 800 °C and Its Modification with Pre-oxidation

2022· article· en· W4309878751 on OpenAlexfundno aff
J. W. X. Wo, H.T. Pang, Alison Wilson, M.C. Hardy, H.J. Stone

Bibliographic record

VenueMetallurgical and Materials Transactions A · 2022
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuperalloyNimonicCrystalliteMaterials scienceIsothermal processOxideMetallurgyInternal oxidationMicrostructureThermodynamics

Abstract

fetched live from OpenAlex

Abstract Ni-based superalloys with enhanced oxidation resistance at high temperatures are crucial for next-generation gas turbine engines. A new polycrystalline Ni-based superalloy (C19) that combines improved microstructural stability with environmental resistance has been developed. Its oxidation resistance has been determined through measurements of the specific mass change and morphological evolution of the formed oxides following furnace exposures at 800 °C in air for up to 1000 hours; the results of which were benchmarked against Nimonic 105. C19 showed hybrid Type II/Type III behavior as a marginal Al 2 O 3 former and performed similarly to established superalloys at 750 °C. The Wagner model for the transition from internal to external oxide formation predicted that C19 should form a continuous Al 2 O 3 scale at higher temperatures. A pre-oxidation treatment at 1100 °C for 1 hour was, therefore, selected and shown to dramatically improve the oxidation resistance during subsequent exposure at 800 °C. Oxide cross-sectional analysis showed that C19 formed a continuous and protective Al 2 O 3 scale after the pre-oxidation treatment, whereas Nimonic 105 retained discontinuous Al 2 O 3 finger-like intrusions beneath a Cr 2 O 3 overscale.

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 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 score0.047
Threshold uncertainty score0.480

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 teacher head, 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

Citations12
Published2022
Admission routes1
Has abstractyes

Explore more

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