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Record W2970361075 · doi:10.1149/09101.0921ecst

Shrinkage Dynamics of Stainless Steel 430-L and Yittrium Stabilized Zirconia and Its Application in Co-Sintering for MS-SOFCs

2019· article· en· W2970361075 on OpenAlexafffund
Sannan Yousaf Toor, Abdalrahman Fayez Alharbi, Eric Croiset

Bibliographic record

VenueECS Transactions · 2019
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsYttria-stabilized zirconiaMaterials scienceShrinkageSinteringCubic zirconiaOxideInertInert gasCeramicMetalAtmosphere (unit)Solid oxide fuel cellComposite materialMetallurgyLayer (electronics)ElectrolyteChemical engineeringChemistryElectrode

Abstract

fetched live from OpenAlex

Metal supported-solid oxide fuel cells (MS-SOFCs), with metal as support in place of conventional ceramic support, are labelled third generation solid oxide fuel cells (SOFCs). In this paper, a detailed study of shrinkage behavior of stainless steel 430 L (SS-430 L) metal support and yittrium stabilized zirconia (YSZ) electrolyte is reported, in particular with regards to the effects of inert atmosphere, reducing atmosphere, and temperature ramping rates. In reducing atmosphere and at higher ramping rates (7.5 °C/min), SS-430 L shrinks earlier and to a higher extent than YSZ. Therefore, upon reaching sintering temperature of 1350°C, the SS-430 L layer is close to its maximum shrinkage, whereas YSZ layer is still sufficiently soft and continues to shrink leading to a flat cell without physical defects. On the other hand, sintering in inert atmosphere is not recommended because higher shrinkage of SS-430 L creates a significant mismatch in shrinkage of metal support and YSZ.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.476

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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 designSimulation or modeling
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
Published2019
Admission routes2
Has abstractyes

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