Investigating Phase and Electrical Properties of Calcium-Doped Yttrium Iron Garnet
Bibliographic record
Abstract
Literature studies have shown that Ca0.5Y2.5Fe5O12-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 (> 1012 Ω cm at room temperature) and less-explored oxide ion conductivity of its parent phase yttrium iron garnet (Y3Fe5O12, 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 CaxY3-xFe5O12-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 Y3Fe5O12 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 Gd3Fe5O12- and Y3Fe5O12-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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".