Go with CO: A Case for Targeting Carbon Monoxide As a Reactive Carbon Capture Product
Why this work is in the frame
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Bibliographic record
Abstract
This study is relevant to reactive carbon capture using aqueous alkaline capture solutions, where captured CO 2 is electrochemically released from a capture solution and then upgraded into commodity chemicals in an electrolyzer. The commercial viability of this form of reactive carbon capture demands that the electrolyzer effluent that is returned to the capture unit be sufficiently alkaline to effectively capture CO 2 from air or a point source. Here, we introduce “electron-alkalinity efficiency” (EA%) to correlate OH – production to electrons consumed during the electrolysis of CO 2 . We show that the maximum EA% value for CO production is 100%, but is less than 50% for the production of HCOO –, CH 4, and C 2 H 4 . This outcome implies that the electrolytic production of CO yields the highest CO 2 capture efficiency. To support this claim, we modeled a 1-m 2 electrolyzer producing CO at a current density of 200 mA cm –2, 100% Faradaic efficiency for CO, and 100% CO 2 utilization, resulting in an OH – production rate of 75 mol h –1 . No other CO 2 reduction products (HCOO –, CH 4, and C 2 H 4 ) generate this level of alkalinity without operating at far more extreme current densities or larger scales. We therefore recommend to “go with CO” for reactive carbon capture.
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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 it