Direct modeling of the electrochemistry in the three-phase boundary of solid oxide fuel cell anodes by density functional theory: a critical overview
Bibliographic record
Abstract
The first principles modeling of electrochemical reactions has proven useful for the development of efficient, durable and low cost solid oxide full cells (SOFCs). In this account we focus on recent advances in modeling of structural, electronic and catalytic properties of the SOFC anodes based on density functional theory (DFT) first principle calculations. As a starting point, we highlight that the adequate analysis of cell electrochemistry generally requires modeling of chemical reactions at the metal/oxide interface rather than on individual metal or oxide surfaces. The atomic models of Ni/YSZ and Ni/CeO2 interfaces, required for DFT simulations of reactions on SOFC anodes are discussed next, together with the analysis of the electronic structure of these interfaces. Then we proceed to DFT-based findings on charge transfer mechanisms during redox reactions on these two anodes. We provide a comparison of the electronic properties of Ni/YSZ and Ni/CeO2 interfaces and present an interpretation of their different chemical performances. Subsequently we discuss the computed energy pathways of fuel oxidation mechanisms, obtained by various groups to date. We also discuss the results of DFT studies combined with microkinetic modeling as well as the results of kinetic Monte Carlo simulations. In conclusion we summarize the key findings of DFT modeling of metal/oxide interfaces to date and highlight possible directions in the future modeling of SOFC anodes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".