Ptni/C Catalysts for Improved Selectivity and Performance in Ethanol Fuel Cells
Notice bibliographique
Résumé
Fossil fuels are currently the primary source of energy, producing a huge amount of greenhouse gases such as CO 2 . In general, greenhouse gases contribute to environmental problems like global warming. For this reason, it is necessary to improve and increase the use of renewable and clean energy sources with low CO 2 production. In recent years, the direct ethanol fuel cell (DEFC) has been considered as an attractive power source with high potential for vehicles and electronic devices. Ethanol is used as a renewable energy resource because it is easy to handle and store, has low toxicity, and is produced in large quantities from agricultural waste and biomass. Moreover, ethanol has advantages over methanol and hydrogen. Its theoretical energy density is around (8.0 kWh kg -1 ), which is higher than methanol (6.1 kWh kg -1 ) and its volumetric density is 6.28 kWh L -1 , which is higher than hydrogen (0.18 kWh L -1 ) and methanol (4.82 kWh L -1 ) [ 1, 2 ]. In spite of that, many problems have impeded DEFC uses, including low current densities, incomplete ethanol oxidation, low faradic efficiencies, and crossover through the membrane. To overcome these problems, many anode catalysts have been developed to increase the activity, selectivity, and efficiency of DEFCs. Studying the effects of alloying Pt catalysts with nickel on the oxidation of ethanol has gained interest. Nickel, is a more electropositive metal than Pt, and has been found to enhance its activity toward the ethanol oxidation reaction. A bifunctional, Langmuir–Hinshelwood mechanism, in which a more electropositive metal provides more OH - species on the surface of the catalyst and drives the oxidation of the adsorbed CO (CO ads ) intermediate to produce CO 2 , was used to explain the behavior of the PtNi catalyst’s activity [ 3 ]. Sulaiman et al studied the effects of shape-controlled octahedral PtNi/C nanoparticles on the activity of ethanol oxidation. Activities of commercial Pt/C, conventional Pt 2 Ni/C alloy, and octahedral Pt 2.3 Ni/C nanoparticles toward ethanol oxidation were measured by cyclic voltammetry. The results showed that the octahedral PtNi/C nanocatalyst was 4.6 and 7.7 times more active than conventional PtNi/C and commercial Pt/C catalysts, respectively [ 4 ]. Furthermore, Altarawneh et al evaluated the octahedral PtNi/C for use in DEFCs by measuring its selectivity and performance. The selectivity of this catalyst was significantly higher than commercial Pt/C at low potential. At 0.20 V, the faradaic yield of CO 2 at PtNi/C was 73%, while at Pt/C it was 55%. [ 5 ]. The primary objective of our research is to understand the effects of PtNi/C catalyst composition, structure, and shape on the activity, performance, and selectivity for the complete oxidation of ethanol to carbon dioxide in DEFCs. PtNi/C catalysts were synthesized in various solvents by using a polyol method. The prepared catalysts were characterized by X-ray powder diffraction (XRD), thermal gravimetric analysis (TGA), and energy dispersive X-ray spectroscopy (EDX) to investigate the composition, metal loading, and crystal structure. Electrochemical analysis was carried out by cyclic voltammetry and chronoamperometry in order to study the activity of these catalysts toward the oxidation of ethanol. Moreover, a commercial PtNi/C catalyst was evaluated using the same methods and its results were compared with our catalysts’ results. Furthermore, the product distribution, selectivity for CO 2 formation, and efficiency were investigated for some of our PtNi/C catalysts and the commercial PtNi/C in 5 cm 2 fuel cell. 1. An, T.S. Zhao, and Y.S. Li, Renewable and Sustainable Energy Reviews ., 50 , 1462–1468 (2015). 2. Wang, S. Zou, and W. B. Cai, Journal of Catalysts ., 5 , 1507-1534 (2015). 3. Soundararajan, J. Park, K. Kim, and J. Ko, Current Applied Physics ., 12 , 854−859 (2012). 4. E. Sulaiman, S.Q. Zhu, Z.L. Xiang, Q.W. Chang, and M.H, Shao. ACS Catalysis ., 7, 5134–5141 (2017). 5. R. Altarawneh, T. Brueckner, B. Chen, and P. Pickup, Journal of Power Sources ., 400 , 369–376 (2018).
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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 | 0,000 |
| 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 ».