Insights into C–N Bond Formation through the Coreduction of Nitrite and CO<sub>2</sub>: Guiding Selectivity Toward C–N Bond
Bibliographic record
Abstract
The coreduction of CO 2 with nitrogen-containing (N-containing) compounds such as nitrite (NO 2 – ) offers a promising pathway for synthesizing valuable C–N molecules like urea. Improving the efficiency of this process relies on the development of electrocatalysts that can effectively steer the electrocatalytic selectivity toward C–N bond formation among various pathways of the coupled CO 2 and NO 2 – reduction reactions. This necessitates the creation of selectivity descriptors that can facilitate rational catalyst design and enable high-throughput screening. In this study, density functional theory (DFT) calculations were employed to conduct a mechanistic investigation on 14 metals, with the aim of developing descriptors to guide or enforce selectivity toward C–N bond formation. The competition between C–N bond formation via various C- and N-containing intermediates, along with their reduction, was examined, leading to the introduction of the C–N Coupling Index to quantify these competitions at different stages of the reaction. It was demonstrated that while most metals favor the reduction of N-containing intermediates, certain metals exhibit a sufficiently low thermodynamic barrier for C–N coupling, aligning with previous experimental observations. Additionally, a negative linear correlation was found between early C–N bond formation barriers via CO 2 and *NO 2 and the adsorbed carboxyl (*COOH) binding energies, indicating that metals with weaker *COOH binding are more favorable for C–N bond formation. Building on these findings, it was demonstrated that pulsed electrolysis is an effective strategy to enhance selectivity toward early-stage C–N bond formation by stabilizing key intermediates while suppressing competing undesirable reaction pathways. In addition, NO 2 – was demonstrated to be a superior nitrogen source for early-stage C–N coupling compared to NO 3 –, particularly when coupled with pulsed electrolysis. Ultimately, this set of selectivity descriptors, combined with pulsed electrolysis, paves the way for the rational design of catalysts that are selective toward C–N bond formation in the coreduction of CO 2 and NO 2 –, and enables the identification of new electrocatalysts through high-throughput screening.
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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 | 0.001 |
| 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".