Theoretical Investigation of CO<sub>2</sub> Reduction at Ni/SDC and La(Sr)FeO<sub>3-δ </sub>Cathodes in Solid Oxide Electrolysis Cells
Bibliographic record
Abstract
Electrochemical CO2 reduction in solid oxide electrolysis cell (SOEC) is a promising technology to address the global issue of greenhouse emissions. To further advance the development of catalyst, it is necessary to gain theoretical insights into high temperature CO2 electroreduction mechanisms on perovskite La(Sr)FeO3-δ and conventional Ni/SDC using Density Functional Theory (DFT). To study the effects of interface oxygen vacancy on CO2 electrolysis on Ni/SDC, surface models with and without interface oxygen vacancy were considered. In addition, the most stable La(Sr)FeO3-δ surface model under SOEC operation conditions with 4 oxygen vacancies was also built. CO2 reduction reaction is most favorable for the strongest CO2 adsorption on Ni/SDC (111) surface, while on La0. 5Sr0. 5FeO2.75 (001) surface, this reaction is most favorable for moderate CO2 adsorption. The adsorption configurations of CO2 and CO that would make CO2 electrolysis most likely to occur were determined for each of the surface models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".