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 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".