Robust and efficient electroreduction of CO2 to CO in a modified zero-gap electrochemical cell
Bibliographic record
Abstract
• Higher temperature or pressure in the zero-gap electrolyzer enhances mass transport and reaction kinetics. • Low voltage at high current density boosts energy efficiency to 52.6% in alkaline and 49.4% in neutral conditions. • Microenvironment management prevents carbonate accumulation, maintaining 90% FE CO over 100 hours. Excellent energy efficiency and system stability are critical factors guiding the practical application of carbon dioxide reduction reaction (CO 2 RR) systems. This work promotes reduction reaction kinetics in a modified zero-gap electrolyzer by regulating the operation temperature and pressure. The energy efficiency of the CO 2 RR system is enhanced, such as 52.6 % at a current of 1.2 A under alkaline conditions and 49.4 % under neutral conditions, with the characteristics of low voltage and high Faradaic efficiency. In addition, the optimization of the reaction microenvironment effectively alleviates the precipitation issue, enabling the system to operate stably for more than 100 h, with a Faradaic efficiency of more than 90 % for CO generation. Engineering-integrated electrochemistry inspires the future development of CO 2 RR technology.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".