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Record W4294831009 · doi:10.31399/asm.cp.itsc2006p0827

Preparation of an SOFC LSM/YSZ Composite Cathode by Air Plasma Spraying

2006· article· en· W4294831009 on OpenAlexaff
B.D. White, Olivera Kesler, Nir Ben-Oved, A. Burgess

Bibliographic record

VenueThermal spray · 2006
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsBC Innovation CouncilUniversity of British Columbia
Fundersnot available
KeywordsCathodeMaterials scienceYttria-stabilized zirconiaSolid oxide fuel cellAnodeCubic zirconiaDeposition (geology)Plasma processingCoatingChemical engineeringElectrolyteGraphiteCeramicComposite materialPlasmaElectrodeChemistry

Abstract

fetched live from OpenAlex

Abstract A porous composite cathode containing (La0.8Sr0.2)0.98MnO3 (LSM) and yttria stabilized zirconia (YSZ) for use in a solid oxide fuel cell has been produced by air plasma spraying. Deposition was carried out using axial powder injection for increased deposition efficiency and composition control. A plasma composed of argon and nitrogen was used to decrease processing costs and avoid decomposition of the cathode material during deposition. Preliminary investigations focused on determining the range of plasma conditions under which each of the materials could be successfully deposited separately. A set of conditions was thereby determined that were suitable for the deposition of a composite cathode from pre-mixed LSM and YSZ powders. Graphite pore former was added to the powder mixture in order to achieve sufficient porosity in the final coating. A tape cast YSZ electrolyte was used as the substrate for the deposition of the cathode and also as the mechanical support layer in the finished cell. Following deposition of the cathode, an anode was produced by traditional wet ceramic processing techniques. Plasma sprayed cathode was characterized by SEM, EDX, and XRD, and the electrochemical performance of the full fuel cell was evaluated.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.680

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 communication0.0000.001
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 head0.009
GPT teacher head0.285
Teacher spread0.276 · 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
Published2006
Admission routes1
Has abstractyes

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