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Record W4205149636 · doi:10.3390/cryst12010073

LaNi0.6Co0.4−xFexO3−δ as Air-Side Contact Material for La0.3Ca0.7Fe0.7Cr0.3O3−δ Reversible Solid Oxide Fuel Cell Electrodes

2022· article· en· W4205149636 on OpenAlexaff
Kalpana Singh, Paul Kwesi Addo, Venkataraman Thangadurai, Jesús Prado‐Gonjal, Beatriz Molero-Sánchez

Bibliographic record

VenueCrystals · 2022
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of CalgaryAlberta Energy
Fundersnot available
KeywordsMaterials scienceOxidePerovskite (structure)TECConductivitySolid oxide fuel cellElectrodeElectrochemistryElectrical resistivity and conductivityChemical engineeringMetallurgyElectrical engineeringChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The goal of the current work was to identify an air-side-optimized contact material for La0.3Ca0.7Fe0.7Cr0.3O3−δ (LCFCr) electrodes and a Crofer22APU interconnect for use in reversible solid oxide fuel cells (RSOFCs). LaNi0.6Co0.4−xFexO3 (x = 0–0.3) perovskite-type oxides were investigated in this work. The partial substitution of Co by Fe decreased the thermal expansion coefficient values (TEC) closer to the values of the LCFCr and Crofer 22 APU interconnects. The oxides were synthesized using the glycine–nitrate method and were characterized using X-ray thermodiffraction and 4-probe DC electrical conductivity measurements. Based on the materials characterization results from the Fe-doped oxides investigated here, the LaNi0.6Co0.2Fe0.2O3−δ composition was selected as a good candidate for the contact material, as it exhibited an acceptable electrical conductivity value of 395 S·cm−1 at 800 °C in air and a TEC value of 14.98 × 10−6 K−1 (RT-900 °C).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.233
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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.013
GPT teacher head0.270
Teacher spread0.256 · 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.

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

Citations5
Published2022
Admission routes1
Has abstractyes

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