MétaCan
Menu
Back to cohort
Record W2131603324 · doi:10.1115/1.1924534

Hot Corrosion of Lanthanum Zirconate and Partially Stabilized Zirconia Thermal Barrier Coatings

2004· article· en· W2131603324 on OpenAlexaff
Basil R. Marple, Joël Voyer, Michel A. Thibodeau, Douglas Nagy, Robert Vaßen

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2004
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsThermal barrier coatingMaterials scienceCubic zirconiaCorrosionYttria-stabilized zirconiaVanadiumZirconateScanning electron microscopeLanthanumMetallurgyCeramicMicrostructureCoatingSulfurOxideChemical engineeringComposite materialInorganic chemistryChemistry

Abstract

fetched live from OpenAlex

The hot corrosion resistance of lanthanum zirconate and 8wt.% yttria-stabilized zirconia coatings produced by thermal spraying for use as thermal barriers on industrial gas turbines or in aerospace applications was evaluated. The two ceramic oxide coatings were exposed for various periods of time at temperatures up to 1000°C to vanadium- and sulfur-containing compounds, species often produced during the combustion of typical fuels used in these applications. Changes in the coatings were studied using a scanning electron microscope to observe the microstructure and x-ray diffraction techniques to analyze the phase composition. The results showed different behaviors for the two materials: the zirconia-based coating being rapidly degraded by the vanadium compounds and resistant to attack by the sulfur materials while the lanthanum zirconate was less damaged by exposure to vanadia but severely attacked in the presence of sulfur-containing species.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.207
Teacher spread0.202 · 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

Citations77
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Engineering for Gas Turbines and PowerSame topicHigh-Temperature Coating BehaviorsFrench-language works237,207