MétaCan
Menu
Back to cohort
Record W2060916779 · doi:10.1007/s40243-014-0035-4

Processing and characterizations of a novel proton-conducting BaCe0.35Zr0.50Y0.15O3-δ electrolyte and its nickel-based anode composite for anode-supported IT-SOFC

2014· article· en· W2060916779 on OpenAlexaff
Ashok Kumar Baral, Sung-Min Choi, Byung Kook Kim, Jong‐Ho Lee

Bibliographic record

VenueMaterials for Renewable and Sustainable Energy · 2014
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Calgary
FundersMinistry of Education, Science and TechnologyNational Research Foundation of KoreaKorea Institute of Science and TechnologyNational Research Foundation
KeywordsAnodeMaterials scienceProton conductorElectrolyteSolid oxide fuel cellDopantConductivityComposite numberAtmospheric temperature rangeOxideChemical engineeringComposite materialDopingMetallurgyElectrodeOptoelectronicsChemistryThermodynamicsPhysical chemistry

Abstract

fetched live from OpenAlex

This work presents the synthesis and characterizations of a stable and well-sinterable proton conductor BaCe 0.35 Zr 0.50 Y 0.15 O 3-δ in which a transition of conductivity occurred steeply from the order of 10 −3 to 10 −2 S cm −1 and activation energy changed from 0.35 to 0.22 eV in the temperature range from 350 to 400 °C, due to the dissociation of protons from the dopant-proton defect pairs. The anode composite Ni-BaCe 0.35 Zr 0.50 Y 0.15 O 3-δ (40:60 vol%) prepared by liquid condensation process showed comparatively very high electrical conductivity than the existing solid oxide fuel cell (SOFC) anodes, in the temperature range of 350–800 °C. Fabrication (by screen printing and co-firing processes), performance and post-mortem analysis of anode-supported protonic SOFC cell using these materials are discussed elaborately.

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 score0.003

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)0.0000.000

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMaterials for Renewable and Sustainable EnergySame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207