Impurity-Resistant CO<sub>2</sub> Reduction Using Reactive Carbon Solutions
Bibliographic record
Abstract
Electrolyzers that electrochemically convert aqueous (bi)carbonate solutions (solutions containing captured CO 2, or “reactive carbon solutions”) into commodity chemicals couple CO 2 capture with CO 2 conversion. Industrial exhaust streams contain nitrogen oxides (NO x ) and sulfur oxides (SO x ) that form redox-active anions in reactive carbon solutions that can interfere with downstream CO 2 reduction. We therefore designed experiments to test how impurities produced from the dissolution of NO x (NO 2 – and NO 3 – ) and SO x (SO 3 2– and SO 4 2– ) impact the electrochemical conversion of (bi)carbonate to CO. We found that CO production was unaffected by SO x compounds in a 3.0 M KHCO 3 feedstock, but 2000 ppm of NO x impurities decreased CO selectivity from ∼60% to <5%. This decrease was caused by the preferential reduction of NO 2 – and NO 3 – over CO 2 . Our study establishes tolerance limits for common flue gas impurities in reactive carbon solutions and provides strategies to mitigate toxification effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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 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".