A Comprehensive Review of the Development of Perovskite Oxide Anodes for Fossil Fuel-Based Solid Oxide Fuel Cells (SOFCs): Prospects and Challenges
Bibliographic record
Abstract
Solid oxide fuel cells (SOFCs) represent a pivotal technology in renewable energy due to their clean and efficient power generation capabilities. Their role in potential carbon mitigation enhances their viability. SOFCs can operate via a variety of alternative fuels, including hydrocarbons, alcohols, solid carbon, and ammonia. However, several solutions have been proposed to overcome various technical issues and to allow for stable operation in dry methane, without coking in the anode layer. To avoid coke formation thermodynamically, methane is typically reformed, contributing to an increased degradation rate through the addition of oxygen-containing gases into the fuel gas to increase the O/C ratio. The performance achieved by reforming catalytic materials, comprising active sites, supports, and electrochemical testing, significantly influences catalyst performance, showing relatively high open-circuit voltages and coking-resistance of the CH4 reforming catalysts. In the next step, the operating principles and thermodynamics of methane reforming are explored, including their traditional catalyst materials and their accompanying challenges. This work explores the components and functions of SOFCs, particularly focusing on anode materials such as perovskites, Ruddlesden–Popper oxides, and spinels, along with their structure–property relationships, including their ionic and electronic conductivity, thermal expansion coefficients, and acidity/basicity. Mechanistic and kinetic studies of common reforming processes, including steam reforming, partial oxidation, CO2 reforming, and the mixed steam and dry reforming of methane, are analyzed. Furthermore, this review examines catalyst deactivation mechanisms, specifically carbon and metal sulfide formation, and the performance of methane reforming and partial oxidation catalysts in SOFCs. Single-cell performance, including that of various perovskite and related oxides, activity/stability enhancement by infiltration, and the simulation and modeling of electrochemical performance, is discussed. This review also addresses research challenges in regards to methane reforming and partial oxidation within SOFCs, such as gas composition changes and large thermal gradients in stack systems. Finally, this review investigates the modeling of catalytic and non-catalytic processes using different dimension and segment simulations of steam methane reforming, presenting new engineering designs, material developments, and the latest knowledge to guide the development of and the driving force behind an oxygen concentration gradient through the external circuit to the cathode.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".