(Invited) Multi-Element-Doped Ceria-Based Metal Oxides for Advanced Proton Conducting SOFCs
Bibliographic record
Abstract
The ability of solid oxide fuel cells (SOFC) to convert the chemical energy of various kinds of fuels into electricity at high efficiency, and with reduced environmental impacts makes them an attractive technology for current and future plans for clean power generation. State-of-the-art yttria-stabilised ZrO2 (YSZ) electrolyte shows high conductivity (10-2 S/cm) at about 1000 °C [1]. However, the high operating temperature leads to durability and cost issues and hinders its full market implementation. Operating temperature of SOFCs can be lowered by employing ceramic proton conducting electrolytes based on doped- BaCeO3 which exhibits high proton conductivity (10-2 S/cm) in the intermediate temperature (IT, 400-700 °C) range [2]. However, the poor chemical stability of doped-BaCeO3 under SOFC by-products CO2, and H2O limits its use as stable electrolyte [2]. Here we report, perovskite–type Ba0.5Sr0.5Ce1-x-y-z Zr x Gd y Y z O3-δ as proton conductors for IT-SOFCs [3]. A-and B-site of BaCeO3 were doped by more electronegative elements to improve its chemical stability under H2O and CO2 at elevated temperature. In terms of chemical stability and conductivity, Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3-δ seems to be the optimal composition with conductivity of 10-3 S/cm at 700 °C in 3% H2O/H2. Open circuit voltage of 1.15 V at 700 °C for H2-air cell suggests pure ionic (proton) conduction in Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3-δ [3]. The effect of sintering temperature on bulk and grain boundary conductivity of these oxides was investigated using dielectric loss spectroscopy [4]. Moreover, the difference in the relaxation times in the current study suggests that short-range and long-range proton dynamics seems to be differing to previous studies on Y-doped BaZrO3 systems [5]. Additionally, layered perovskite-type Gd0.5Pr0.5BaCo2O5+δ were characterised as cathode for H-SOFCs [6]. Symmetrical cell measurements under air and wet air gave an area specific resistance of 2.4 Ω cm2 and 1.9 Ω cm2 for oxygen reduction reaction at 700 °C [6]. The effect of phase purity and synthesis methods on the electrochemical performance of Ni+Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3 -δ anode composites was investigated through symmetrical cell measurements in 3% H2O/H2. References 1) J. W. Fergus, R. Hui, X. Li, D. P. Wilkinson, J. Zhang, Solid Oxide Fuel Cells: Materials Properties and Performance, CRC Press, New York (2009). 2) K. D. Kreuer, Annu. Rev. Mater. Res. 33 (2003) 333. 3) R. Kannan, K. Singh, S. Gill, T. Fürstenhaupt, V. Thangadurai, Sci. Reports. 3 (2013) 2138. 4) K. Singh, A. Baral, V. Thangadurai, J. Am. Ceram. Soc. 99 (2016) 866. 5) Y. Yamazaki, F. Blanc, Y. Okuyama, L. Buannic L, J. C. Lucio-Vega, C. P. Grey, S. M. Haile, Nat. Mater. 12 (2013) 647. 6) K. Singh, A. K. Baral, V. Thangadurai, Solid State Ionics (2016) DOI:10.1016/j.ssi.2015.12.010.
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 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".