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Record W1558327082 · doi:10.1002/9780470291337.ch24

Fuel Cell Interconnecting Coatings Produced by Different Thermal Spray Techniques

2008· book-chapter· en· W1558327082 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCeramic engineering and science proceedings · 2008
Typebook-chapter
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThermal sprayingMaterials scienceCeramicMicrostructureScanning electron microscopeSolid oxide fuel cellGas dynamic cold spraySolution precursor plasma sprayElectrical resistivity and conductivityPlasma torchPorosityMetallurgySpray nozzleOxideNozzleThermal barrier coatingComposite materialPlasmaCoatingChemistryMechanical engineering

Abstract

fetched live from OpenAlex

Doped LaCrO3 ceramic material is commonly used to produce interconnect coatings for solid oxide fuel cells (SOFCs). Three different thermal spray methods are used in this work to deposit La0.9Sr0.1CrO3 interconnect coatings: high velocity oxy-fuel (HVOF) using a modified nozzle and two different atmospheric plasma spray (APS) torches. One of them is a commercial torch that uses Ar/H2 as plasma forming gases and the other is a new torch design that uses gas mixtures based in CO2. The spray parameters of each torch were set by studying the in-flight temperature and velocity of the particles as a function of the stand-off distance using a substitute powder (ZrO2-TiO2-Al2O3 composite) with similar physical properties to La0.9Sr0.1CrO3. The process parameters that produced coatings with the lowest porosity were employed to deposit La0.9Sr0.1CrO3 coatings on zirconium oxide substrates. Scanning electron microscopy (SEM) and X-ray diffraction analysis techniques were used to characterize the coatings produced by the three different torches. The microstructure features and crystalline phases present in the coatings are explained in terms of the process parameters and correlated with preliminary measurements of electrical resistivity of the as-sprayed coatings. In some cases, post-deposition heat treatments are studied in order to decrease the electrical resistivity.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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