Studies on Electrochemical Performance of Mn- and Y-Codoped CeO<sub>2</sub> under Pure and Impure Hydrogen Fuels
Bibliographic record
Abstract
Currently, research has been focusing on the development of mixed ionic electronic conductors (MIECs) for applications in catalysis, gas separation membranes and solid oxide fuel cells (SOFCs). The present anode Ni/Y-doped ZrO2 (YSZ) is suffering from coking, sulfur poisoning under hydrocarbon fuels. Doped ceria has shown mixed ionic electronic characteristics under reducing atmosphere that could be potentially promising anode for solid oxide fuel cells. Using MIEC electrode materials is expected to enlarge electrochemical reaction zone (ERZ) over the entire electrode-gas interfacial area and alleviate or inhibit anode poisoning. Here, we report synthesis and electrochemical properties of novel nanostructured CYMO (Ce0.8Y0.1Mn0.1O2-δ) prepared by autocombustion method using metal salt precursors. The investigated samples were characterized using several solid state techniques such as powder X-ray diffraction (XRD), scanning electron microscope (SEM), energy dispersive x-ray spectroscopy (EDX), and infrared spectroscopy (IR). The electrochemical performance of the prepared anode was tested using a symmetrical cell CYMO/YSZ/CYMO at 600-800○C in humidified H2 / N2 under open circuit and polarization conditions using ac electrochemical impedance spectroscopy (EIS) and DC method. Area specific resistance (ASR) of 0.3 Ωcm2 at 800oC was observed for CYMO and is comparable to that of Ni-YSZ / Ni-ScSZr (0.185 Ωcm2)1 and La0.65Ce0.1Sr0.25Cr0.5Mn0.5O3-δ (0.2 Ωcm2) .2 Interestingly, a noticeable enhancement in the performance of the symmetrical cell was observed upon exposing the cell to 10 ppm H2S in H2 / N2 (Fig.1). In this talk, a detailed analysis for electrochemical results will be presented.
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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 | 0.001 |
| 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".