Supramolecular Enhancement of Electrochemical Nitrate Reduction Catalyzed by Cobalt Porphyrin Organic Cages for Ammonia Electrosynthesis in Water**
Bibliographic record
Abstract
Abstract The electrochemical nitrate (NO 3 − ) reduction reaction (NO 3 RR) to ammonia (NH 3 ) represents a sustainable approach for denitrification to balance global nitrogen cycles and an alternative to traditional thermal Haber‐Bosch processes. Here, we present a supramolecular strategy for promoting NH 3 production in water from NO 3 RR by integrating two‐dimensional (2D) molecular cobalt porphyrin ( CoTPP ) units into a three‐dimensional (3D) porous organic cage architecture. The porphyrin box CoPB‐C8 enhances electrochemical active site exposure, facilitates substrate–catalyst interactions, and improves catalyst stability, leading to turnover numbers and frequencies for NH 3 production exceeding 200,000 and 56 s −1 , respectively. These values represent a 15‐fold increase in NO 3 RR activity and 200‐mV improvement in overpotential for the 3D CoPB‐C8 box structure compared to its 2D CoTPP counterpart. Synthetic tuning of peripheral alkyl substituents highlights the importance of supramolecular porosity and cavity size on electrochemical NO 3 RR activity. These findings establish the incorporation of 2D molecular units into 3D confined space microenvironments as an effective supramolecular design strategy for enhancing electrocatalysis.
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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 | 0.000 | 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".