Robust Bi Metal–Organic Framework-Derived Catalyst for the Selective Electroreduction of CO<sub>2</sub> to Formate at Current Densities up to 1 A cm<sup>–2</sup> in Gas Diffusion Electrodes
Bibliographic record
Abstract
Electrochemical reduction of CO 2 to useful products requires selective and stable catalysts that can be easily synthesized and are cost-effective. In this work, we investigate the Bi CAU-17 metal–organic framework (MOF) synthesized by a novel and scalable method to generate in situ highly active Bi 2 O 2 CO 3 catalyst for CO 2 electroreduction to formate in either KHCO 3 or KOH electrolytes. The Bi CAU-17-derived catalyst provides high faradaic efficiencies toward formate (FE HCOO – = 85–100%) at current densities up to 1 A cm –2 in a gas diffusion electrode with a low catalyst loading (0.5 mg cm –2 ). Comparative experiments between commercial and in situ generated Bi 2 O 2 CO 3 from Bi CAU-17 showed that the latter has superior catalytic performance at high current densities (>300 mA cm –2 ) and with stable activity after 26 h of continuous electrolysis at 200 mA cm –2 in the pH range 8–14. These results highlight the importance of generating in situ active Bi/Bi–O sites that promote the selective reduction of CO 2 to formate.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".