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 CO 2 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 CO 2 electroreduction mechanisms on perovskite La(Sr)FeO 3-δ and conventional Ni/SDC using Density Functional Theory (DFT). To study the effects of interface oxygen vacancy on CO 2 electrolysis on Ni/SDC, surface models with and without interface oxygen vacancy were considered. In addition, the most stable La(Sr)FeO 3-δ surface model under SOEC operation conditions with 4 oxygen vacancies was also built. CO 2 reduction reaction is most favorable for the strongest CO 2 adsorption on Ni/SDC (111) surface, while on La 0. 5 Sr 0. 5 FeO 2.75 (001) surface, this reaction is most favorable for moderate CO 2 adsorption. The adsorption configurations of CO 2 and CO that would make CO 2 electrolysis most likely to occur were determined for each of the surface models.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".