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Record W4294700953 · doi:10.31399/asm.cp.itsc2007p0478

Improvement of Plasma Sprayed Yttria Stabilized Zirconia (YSZ) Electrolytes for Solid Oxide Fuel Cells by Spin Coated Sol Gel Solutions

2007· article· en· W4294700953 on OpenAlexaff
Lars Rose, Z. Tang, A. Burgess, Olivera Kesler

Bibliographic record

VenueThermal spray · 2007
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsBC Innovation CouncilUniversity of British Columbia
Fundersnot available
KeywordsYttria-stabilized zirconiaMaterials scienceElectrolyteChemical engineeringCubic zirconiaAnodeCathodeOxideSolid oxide fuel cellCeramicIonic conductivitySinteringFast ion conductorComposite materialMetallurgyChemistryElectrode

Abstract

fetched live from OpenAlex

Abstract Yttria stabilized zirconia (YSZ) is the most commonly used electrolyte material for solid oxide fuel cells (SOFCs), due to its pure ionic conductivity and chemical stability. Standard electrolyte fabrication techniques for planar fuel cells involve wet ceramic techniques such as tape-casting or screen printing, which require sintering at temperatures above 1300°C. Plasma spraying (PS) may provide a more rapid and cost efficient method of producing SOFCs without requiring high temperature post-deposition heat treatments. However, it is difficult to produce plasma sprayed layers that are both thin (<20µm) and completely dense. It is of utmost importance to have a dense electrolyte to prevent the mixing of cathode and anode reactant gases. This study investigates the use of spin coated sol gel derived YSZ precursor solutions to fill the pores present in plasma sprayed YSZ layers.

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 score0.001
Threshold uncertainty score0.002

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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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