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Record W4407711378 · doi:10.1142/s3082805825500037

Atomistic modelling of the thermo-mechanical behaviour of GDZ/YSZ interphase region in bilayer thermal barrier coatings

2025· article· en· W4407711378 on OpenAlexafffund
Tongyu Wu, Ruiqi Shang, S. I. Kundalwal, S. A. Meguid

Bibliographic record

VenueNano Micro Mechanics Review · 2025
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInterphaseBilayerMaterials scienceThermal barrier coatingYttria-stabilized zirconiaThermalComposite materialNanotechnologyChemical physicsChemistryThermodynamicsMembranePhysicsLayer (electronics)Cubic zirconiaCeramic

Abstract

fetched live from OpenAlex

Current gas turbine engines use Yttria-Stabilized Zirconia (YSZ) as the top coat for heat shielding in HP turbines as well as combustors. Unfortunately, YSZ suffers from many drawbacks once the temperature reaches 1200[Formula: see text]C. This limits the long-term application temperature of YSZ, and a few top coat replacements have been suggested and examined. In our study, we make two major changes to the top coat. The first is to use Gadolinium Zirconate (Gd 2 Zr 2 O 7 or GDZ) which enjoys better thermal properties. The second is to combine it with YSZ in a bilayer configuration, thus, making use of the combined beneficial effects of thermal shielding and mechanical strength of these top coats. In spite of the fact that GDZ/YSZ has been suggested by other authors, no work has been devoted to study the role played by the GDZ–YSZ interphase region, possible interdiffusion, its thermal properties and interphase region strength. In this study, we developed comprehensive atomistic models of the GDZ/YSZ interface using molecular dynamics (MD) with emphasis on thermo-mechanical properties of the GDZ/YSZ interphase region. This allowed us to examine the evolution of the GDZ/YSZ interphase region and compute the interface bond strength with temperature.

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)0.001
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 score0.088
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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