Ammonia Thermal Treatment Toward Topological Defects in Porous Carbon for Enhanced Carbon Dioxide Electroreduction
Bibliographic record
Abstract
Abstract The design of specific active sites for the carbon dioxide electro-reduction reaction (CO 2 RR), is crucial for determining product selectivity and catalysis performance. Here, we present an efficient NH 3 thermal treatment for thoroughly removing the pyrrolic-N and pyridinic-N dopants from 3D N-enriched graphene analogue particles, to create high density of topological defects as active sites for CO 2 RR. [1] Firstly we found that NH 3 showed a pronounced effect of eliminating specific N-containing moieties at elevated temperatures, superior to Ar. The identification of topological defects (pentagonal carbon polygon and 585 defect) was investigated by near-edge X-ray absorption fine structure measurements and local density of states analysis, and its formation mechanism was revealed by reactive molecular dynamics simulations.The as-prepared catalysts exhibited excellent performance in flooded half-cell experiments in 0.1 M KHCO 3 reaching current densities of 2.8 mA cm -2 and 4.4 mA cm -2 with FE CO of 92.7% and 89.2% at -0.6 V and -0.7 V v.s. RHE, respectively at room temperature and atmosphere pressure. These results are among the best performances reported for metal-free catalysts. [2,3,4,5] Density functional theory calculations revealed that the edged pentagonal sites (penta-1 and 585-1 defects) are the dominating active centers with the lowest free energy barriers of CO 2 RR for CO production. [6,7] References [1] Zhu J.; Huang J.; Mei W. et al, Angew. Chem. Int. Ed. 2019 , 58 , 3859-3864 [2] Wu, J.; Liu, M.; Sharma, P. P. et al, Nano Lett. 2016, 16 (1), 466-70 [3] Wu, J.; Yadav, R. M.; Liu, M. et al, ACS Nano 2015, 9 (5), 5364-5371. [4] Daiyan, R.; Tan, X.; Chen, R. et al, Acs Energy Lett. 2018, 3 (9), 2292-2298. [5] Kumar, B.; Asadi, M.; Pisasale, D. et al, Nat. Commun. 2013, 4 , 2819. [6] Banhart F., Kotakoski J., Krasheninnikov A.V. ACS Nano, 2011 , 5 , 29-41. [7] Dong, Y.,zhang Q.J. et al, Ammonia Thermal Treatment toward Topological Defects in Porous Carbon for Enhanced Carbon Dioxide Electroreduction. (submitted) Figure 1
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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".