Model Operational Matrix for the Betterment of Ruthenium As a Catalyst for the Electrochemical Nitrogen Reduction Reaction to Ammonia in Aqueous Electrolytes
Notice bibliographique
Résumé
Ammonia (NH 3 ), as a green energy carrier, potential transportation fuel and chemical for fertilizer synthesis, plays an indispensable role in the agricultural, plastic, pharmaceutical and textile industries 1 . Industrially, NH 3 manufacturing is dominated by the Haber–Bosch (HB) process, which consumes more than 2% of the global energy supply, and releases 1.87 tons of greenhouse gas, carbon dioxide (CO 2 ), per 1 ton of NH 3 2 . This energy-intensive process is also inefficient and relatively low conversion ratio are achieved due to unfavorable chemical equilibrium 3 . Hence, it is of great significance to develop alternative routes for more efficient N 2 fixation under milder conditions. Recently, a worldwide gold rush has been triggered, and many pioneering methods are being investigated to convert N 2 to NH 3 , including biological catalysis 4 , photocatalysis 5,6 and electrocatalysis 2,7 . Particularly, electrochemical reduction of N 2 to NH 3 is thermodynamically predicted to be more energy efficient than the HB process by about 20% 7,8 . An electrochemical process could also provide the benefit of reducing greenhouse gas emission as the source of H 2 is the electrolysis of water molecules instead of natural gas. With this scenario, ammonia would be synthesized in a carbon-neutral manner if renewable electrical energy is used. In the electrochemical N 2 reduction reaction (NRR) system, though electrocatalysts are the paramount components, a rational cell design, synthesize and operation conditions are very vital 4 . Most of recent studies have looked on a single parameter (or two) such as catalyst morphology, catalyst deposition and loading, nitrogen reduction potential or type, temperature, pressure and components of cell and electrolytes. However, the fact that NRR and catalyst deposition is a multistep process, sampled parameters study might not provide sufficient information about the actual electrocatalytic process. Therefore, our group tried to determine the best working conditions and ways of designing NRR experiments in order to draw conclusions on the process efficiency in terms of charge used and NH 3 yield. In the present study, electrochemically deposited Ru metal catalysts have been investigated. It is found that in ambient reaction conditions and in highly concentrated electrolytes, a Faradic Efficiency as high as 1.2 % can be reached by optimizing the Ru deposition morphology and deposition time (loading), as well as the NRR potential, nature of cation/anion exchange membranes and size of the counter cations in the electrolyte. This is a 4-fold improvement compared to the maximum efficiency reported 4 with the same catalyst (< 0.3 %). References: 1. H. Wang et al., Angew. Chemie Int. Ed. , 57 , 12360–12364 (2018) https://doi.org/10.1002/anie.201805514. 2. C. J. M. van der Ham, M. T. M. Koper, and D. G. H. Hetterscheid, Chem. Soc. Rev. , 43 , 5183–5191 (2014) http://dx.doi.org/10.1039/C4CS00085D. 3. H. Cheng, P. Cui, F. Wang, L.-X. Ding, and H. Wang, Angew. Chemie , 131 , 15687–15693 (2019) https://doi.org/10.1002/ange.201910658. 4. X. Guo, H. Du, F. Qu, and J. Li, J. Mater. Chem. A , 7 , 3531–3543 (2019) http://dx.doi.org/10.1039/C8TA11201K. 5. B. M. Comer et al., J. Am. Chem. Soc. , 140 , 15157–15160 (2018) https://doi.org/10.1021/jacs.8b08464. 6. Y. Wan, J. Xu, and R. Lv, Mater. Today , 27 , 69–90 (2019) https://www.sciencedirect.com/science/article/pii/S136970211930001X#f0015. 7. V. Smil, Enriching the earth : Fritz Haber, Carl Bosch and the transformation of world food production , Cambridge (Mass.) : MIT press, (2004) http://lib.ugent.be/catalog/rug01:000891228. 8. M. Wang et al., Nat. Commun. , 10 , 341 (2019) https://doi.org/10.1038/s41467-018-08120-x.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».