New Approach to Improve the DMFC Performance By Nafion-Functionalized Graphene Oxide Matrix Membranes Using the Electrochemical Exfoliation of Graphite As a Source of the Graphene Oxide
Notice bibliographique
Résumé
Direct Methanol Fuel Cell (DMFC) is one of the most attractive and effective source of energy for portable applications. Methanol, which is used as fuel, is a manageable liquid with excellent energy storage densities. Beside the advantages of the DMFC, some main issues are still present in the performance of this fuel cell. One of the major disadvantages is the methanol crossover, which is attributed to the transport along with water molecules. Nafion is the most common materials used as electrolyte membrane in fuel cells. It is a perfluorosulfonic acid polyetectrolyte polymer which has an excellent chemical stability and high proton conductivity. However, Nafion allows the methanol permeation from anode to cathode leading to a mixed potential and the reduction of methanol concentration at the anode side with the consequent decreasing of the fuel cell performance. Therefore, finding a membrane able to hinder the methanol permeation while maintaining the proton conductivity has been heavily researched [1, 2]. To minimize the methanol crossover problems in Nafion membranes, many researches focused on fillers to modify the Nafion membrane and create a barrier for the methanol or improve the water/methanol selectivity. Zeolites, zirconium, SiO2 or polypyrrole are some of the materials which were tested. Another approach to modify the Nafion membrane is developing mixed matrix membranes where the filler materials are incorporated in situ in the membrane along with the polymer[2]. Graphene oxide (GO) has unique properties for membranes applications because of its 2D structure and interesting mechanical and thermal stability. Moreover, abundant oxygen-containing functional groups provide amphiphilic nature and allow convenient chemical functionalization, which makes this material and its derivatives promising inorganic filler for composite membranes. Different studies have been carried out for The University of Manchester to prove that incorporating CVD Graphene and GO into the different layers of the PEM fuel cell MEAs, improves the overall performance of the fuel cell [3,4]. This work presents a new functionalized GO-Nafion mixed matrix membrane in order to enhance the DMFC performance by decreasing the methanol crossover. The GO is produced by Electrochemical Exfoliation of Graphite (EGO) as an alternative to the traditional Hummer’s method. EGO has been presented as a green and cost-effective approach for producing high quality of graphene in high yield using simple equipment [5-7]. Further functionalization of GO will improve the compatibility of the graphene-based material with the Nafion and allowing less methanol crossover and higher proton conductivity. References: [1] Wei Jia, Beibei Tang, and Peiyi Wu. Novel Slighthly Reduced Graphene Oxide Based Proton Exchange Membrane with Constructed Long-Range Ionic Nanochennels via Self-Assembling of Nafion. Applied Materials & Interfaces, 9, 22620-22627 (2017). [2] Hung-Chung Chien, Li-Duan Tsai, Chiu-Ping Huang, Chi-yun Kang, Jiunn-Nan Lin, Feng-Chih Chang. Sulfonated Graphene Oxide/Nafion Composite Membranes for High-Performance Direct Methanol Fuel Cells. International Journal of Hydrogen Energy, 28, 13792-13801 (2013) [3] Stuart M. Holmes, Orabhuraj Balakrishnan, Vasu. S. Kalangi, Xiang Zhang, Marcelo Lozada-Hidalgo, Pulickel M Ajayan, Rahul R. Nair. 2D Crystals Significantly Enhance the Performance of a Working Fuel Cell. Advance Energy Materials, 7, (2017). [4] S. Al-Batty, C. Dawson, S. P. Shanmukham, E. P. L. Roberts and S. M. Holmes. Improvement of direct methanol fuel cell performance using a novel mordenite barrier layer. J Mater. Chem. A, 2016, 4, pp. 10850-10857. [5] Richard Gondosiswanto, Xunyu Lu, and Chuan Zhao. Preparation of Metal-Free Nitrogen-Doped Graphene via direct electrochemical exfoliation of graphite in ammonium nitrate. Australian Journal of Chemistry, 68 (2015) 830-835. [6] Xunyu Lu and Zhao. Controlled electrochemical intercalation, exfoliation and in-situ nitrogen doping of graphite in nitrate-based proton ionic liquids. Physical Chemistry Chemical Physics,15 (2013), 30005-200009. [7] Khaled Parvez, Ahong-shuai Wu, Tongjin Li, Xianjie Liu, Robert Graft, Xinliang Feng, and Klaus Mullen. Exfoliation of Graphite into Graphene in Aqueous solution of Inorganic Salts. Journal of the American Chemical Society, 136, (2014), 6038-6091.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».