Reactive Carbon Capture Enables CO<sub>2</sub> Electrolysis with Liquid Feedstocks
Bibliographic record
Abstract
Conspectus The electrochemical reduction of carbon dioxide (CO2RR) is a promising strategy for mitigating global CO 2 emissions while simultaneously yielding valuable chemicals and fuels, such as CO, HCOO –, and C 2 H 4 . This approach becomes especially appealing when integrated with surplus renewable electricity, as the ensuing production of fuels could facilitate the closure of the carbon cycle. Despite these advantages, the realization of industrial-scale electrolyzers fed with CO 2 will be challenged by the substantial energy inputs required to isolate, pressurize, and purify CO 2 prior to electrolysis. To address these challenges, we devised an electrolyzer capable of directly converting reactive carbon solutions (e.g., a bicarbonate-rich eluent that exits a carbon capture unit) into higher value products. This “reactive carbon electrolyzer” operates by reacting (bi)carbonate with acid generated within the electrolyzer to produce CO 2 in situ, thereby facilitating CO2RR at the cathode. This approach eliminates the need for expensive CO 2 recovery and compression steps, as the electrolyzer can then then coupled directly to the CO 2 capture unit. This Account outlines our endeavors in developing this type of electrolyzer, focusing on the design and implementation of materials for electrocatalytic (bi)carbonate conversion. We highlight the necessity for a permeable cathode that allows the efficient transport of (bi)carbonate ions while maintaining a sufficiently high catalytic surface area. We address the importance of the supporting electrolyte, detailing how (bi)carbonate concentration, counter cations, and ionic impurities impact selectivity for products formed in the electrolyzer. We also catalog state-of-the-art performance metrics for reactive carbon electrolyzers (i.e., Faradaic efficiency, full cell voltage, CO 2 utilization efficiency) and outline strategies to bridge the gap between these values and those required for commercial operation Collectively, these findings contribute to the ongoing efforts to realize industrial-scale electrochemical reactors for CO 2 conversion, bringing us closer to a sustainable and closed-loop carbon cycle.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".