Pore Engineering for Directional CO<sub>2</sub> Enrichment in Urea Electrosynthesis
Bibliographic record
Abstract
Electrochemical synthesis of urea from CO 2 and nitrate offers a sustainable pathway to address both carbon emissions and nitrogen pollution. However, achieving high C–N coupling selectivity remains challenging due to competing hydrogen evolution reactions and insufficient CO 2 utilization. Herein, we implement a nanopore-structure engineering strategy to precisely tailor pore length and surface chemistry in metal-free porous carbon frameworks. Oxygen-functionalized surfaces augment CO 2 binding affinity via dipole–quadrupole interactions, while elongated pores induce directional CO 2 enrichment by establishing a H 2 O-deficient nanoenvironment that prolongs the residence time of CO 2 through capillary gating. This dual modulation of gas–liquid–solid interactions enhances urea selectivity and suppresses hydrogen evolution, yielding a 28% increase in Faradaic efficiency and 12% improvement in urea yield. Our findings propose a novel nanopore-level design concept that shall support the rational development of porous carbon supports across gas–liquid–solid electrocatalytic systems.
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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 | 0.000 | 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 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".