Computational Discovery of New C─C Coupling Electrocatalysts for CO <sub>2</sub> Electroreduction
Bibliographic record
Abstract
Abstract Catalyst development is key in advancing low‐temperature CO 2 electroreduction systems on the path to energy‐efficient and low‐carbon intensity fuels and chemicals. Much focus lies today on transition metals and their modification, yet a promising avenue remains unexplored—perovskite oxides. Owing to perovskite oxides’ distinct electronic structures and reactivity patterns, the systematic screening of these materials can enable identification of new activity regimes and point to mechanisms and active sites distinct from those in traditional transition metal catalysts. Herein, a data‐driven search is applied to evaluate the stability of a large library of ≈1500 ABO 3 perovskites at the relevant pH and electrode potentials of CO 2 electroreduction. This study identifies 31 stable candidates and chooses the ATaO 3 family of perovskites to synthesize and investigate for its electrochemical performance. Strikingly, C─C coupling is observed with a C 2 Faradaic Efficiency (FE) of 10% at 100 mAcm −2 with KTaO 3 . This study finds the size of the A element in ATaO 3 to be critical in C─C coupling, and computational reaction pathway analysis shows a CO * ─ * CHO coupling‐driven mechanism for C 2 production. The findings in this study suggest routes to materials design for electrocatalytic C─C coupling on non‐copper surfaces.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".