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Record W4229855741 · doi:10.1149/ma2019-02/40/1858

Investigating Phase and Electrical Properties of Calcium-Doped Yttrium Iron Garnet

2019· article· en· W4229855741 on OpenAlexaff
Zheyu Zhang, Kalpana Singh, Venkataraman Thangadurai

Bibliographic record

VenueECS Meeting Abstracts · 2019
Typearticle
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsYttriumMaterials scienceAnalytical Chemistry (journal)Ionic conductivityYttrium iron garnetElectrical resistivity and conductivityOxideIonic bondingDopingPhase (matter)StoichiometryDiffractometerInorganic chemistryMineralogyIonChemistryPhysical chemistryMetallurgyCondensed matter physicsElectrodeScanning electron microscopeElectrolyte

Abstract

fetched live from OpenAlex

Literature studies have shown that Ca 0.5 Y 2.5 Fe 5 O 12-δ can be a promising cathode material for intermediate temperature solid oxide fuel cell (IT-SOFC) 1 . As it exhibits higher electrical and ionic conductivity compared to several other kinds of rare-earth garnets 2 . However, given the high resistivity (> 10 12 Ω cm at room temperature) and less-explored oxide ion conductivity of its parent phase yttrium iron garnet (Y 3 Fe 5 O 12 , YIG), the effect of calcium doping on the electronic and ionic properties has not been fully studied yet 3 . In this work, polycrystalline samples of Ca-doped YIG, with general chemical formula Ca x Y 3-x Fe 5 O 12-δ (x=0, 0.1, 0.3, 0.5 and 0.7), were prepared and phase characterized by powder X-ray diffractometer. The oxygen non-stoichiometry was determined by iodometric titration at room temperature and thermogravimetric analysis (TG) at elevated temperatures. Total electrical conductivity was measured by four-probe DC method, and ionic conductivity was calculated by using a modified Hebb-Wagner polarization method. As a result, the ionic transference number was calculated and discussed in relation to its potential applications. Reference: Zhong, W., Ling, Y., Rao, Y., Peng, R. & Lu, Y. Calcium doped Y 3 Fe 5 O 12 as a new cathode material for intermediate temperature solid oxide fuel cells. J. Power Sources 213, 140–144 (2012). Kharton, V. V. et al. Ionic Transport in Gd 3 Fe 5 O 12 - and Y 3 Fe 5 O 12 -Based Garnets. J. Electrochem. Soc. 150, J33 (2003). Lehmann-Szweykowska, A., Wojciechowski, R. J., Gehring, G. A. & Tobijaszewski, I. Quasiparticles in Calcium Doped Yttrium-Iron Garnets. Acta Phys. Pol. A 91, 423–426 (1997).

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 score0.142
Threshold uncertainty score0.488

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 communication0.0000.000
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 head0.023
GPT teacher head0.232
Teacher spread0.209 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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