Metallic Porous Electrodes Enable Efficient Bicarbonate Electrolysis
Bibliographic record
Abstract
We demonstrate here that a porous free-standing silver foam cathode in an electrolytic flow cell mediates efficient electrolysis of 3.0 M bicarbonate solutions into CO. These results have direct implications for carbon capture schemes where OH- solutions react with CO2 to form bicarbonate-rich solutions that need to be treated to recycle the sorbent and recover the CO2. Our study shows a viable path for replacing the high-temperature thermal process currently used to recover CO2 from these carbon capture solutions by using electricity to drive the conversion of bicarbonate into CO2 and subsequently into CO. The use of free-standing porous silver electrodes was found to yield electrolysis performance parameters (e.g., a Faradaic efficiency for CO production, FECO, of 78% at 100 mA cm2; <3% performance loss after 80 h operation) that are superior to results obtained in bicarbonate electrolyzers that utilize conventional carbon-based gas diffusion electrodes (GDEs) designed for gaseous CO2 fed electrolyzers. These performance metrics are comparable to any electrolytic flow cell fed directly with a CO2 feedstock, with the added benefit of not requiring an energy-intensive pressurization step that would be necessary for the electrolysis of gaseous CO2. These findings represent a potentially important step in closing the carbon cycle.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".