Morphology Dependent N<sub>2</sub> Reduction on Cu<sub>2</sub>O: Combined Experimental and Computational Study for Efficient Ammonia Electrocatalytic Synthesis
Bibliographic record
Abstract
Abstract Tailoring morphology to alter catalyst performance offers a promising approach to enhance electrocatalytic nitrogen reduction reaction (NRR) for ammonia electrosynthesis. In this work, the structure‐dependent performance of Cu 2 O nanocrystals with distinct cubic and octahedral morphologies is investigated. Experimental results demonstrate the structure‐dependent activity, wherein Cu 2 O with nanooctahedral morphology shows enhanced NRR performance achieving NH 3 yield of 182.1 µg h −1 mg cat −1 and Faradaic efficiency (FE) of 35.8% at −0.5 V versus RHE, surpassing its cubic counterpart. To gain mechanistic insights, density functional theory calculations are performed with Hubbard correction (DFT + U). The results indicate thermodynamically favorable nitrogen reduction pathway on the exposed (111) facets of Cu 2 O. Furthermore, charge transfer analysis provides insights into the redistribution of electron density during NRR. The synergy between experimental results and theoretical insights highlights the importance of morphological tuning in designing efficient Cu 2 O‐based catalysts for electrocatalytic ammonia synthesis.
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 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".