High Performance Anion Exchange Membrane Water Electrolyzer Using Monolayer Nickel-Iron Layered Double Hydroxide As Anode Catalysts
Notice bibliographique
Résumé
Much efforts have been devoted to developing electrocatalysts applicable to anion exchange membrane water electrolyzer (AEMWE). AEMWE operates in basic condition, which allows non-noble metal-based catalysts to be used, while its membrane electrode assembly (MEA) design allows higher current density compared to conventional alkaline water electrolyzer (AWE). Among many candidates for oxygen evolution reaction (OER), NiFe layered double hydroxide (LDH)-based electrocatalysts show the highest activity in an alkaline medium. Unfortunately, the poor electrical conductivity of NiFe-LDH limits its potential as an electrocatalyst, which was often solved by hybridization with conductive carbonaceous materials. However, we find that using carbonaceous materials for anode has detrimental effects on the stability of AEMWE at industrially relevant current densities. In this work, a facile monolayer structuring is suggested to overcome low electrical conductivity and improve mass transport without using carbonaceous materials. Bulk NiFe-LDH (B-NiFe-LDH) with multiple cationic layers was synthesized by following a conventional co-precipitation method, while monolayer NiFe-LDH (M-NiFe-LDH) was prepared using a similar method, but with formamide present in solvent. While Fe 2p and O 1s did not show noticeable difference, M-NiFe-LDH had larger Ni 3+ peak than B-NiFe-LDH, indicating that M-NiFe-LDH has more Ni species in NiOOH environment rather than Ni(OH) 2 environment. Here, more NiOOH phase in M-NiFe-LDH caused higher conductivity, leading to higher specific activity. The effect of electrical conductivity was further investigated by mixing the catalysts with various amounts of carbon materials. When carbon black (Vulcan XC-72) was loaded together with B-NiFe-LDH, the OER activity increased from the absence of carbon up to carbon-to-catalyst weight ratio of 0.1. Further addition of carbon did not increase the current density. On the other hand, the OER activity barely changed upon carbon addition for M-NiFe-LDH. As only Ni 3+/4+ species are known to have OER activity, facile electron transfer from Ni 2+ sites to Ni 3+/4+ is important. Mixing carbon materials with B-NiFe-LDH provided conductive networks into previously “electron-unreachable” regions, which was also confirmed by the increase in the size of Ni oxidation peaks upon carbon addition. On the other hand, the contact between glassy carbon and M-NiFe-LDH catalyst was sufficient to have efficient electron transfer without carbon. The M-NiFe-LDH deposited on Ni foam (NF) showed much better AEMWE performance than B-NiFe-LDH, due to better electrical conductivity and higher hydrophilicity. When the M-NiFe-LDH was loaded on carbon paper (CP) instead of Ni foam, water electrolysis performance was enhanced, but stability was greatly lowered. Similar to the M-NiFe-LDH, the CP substrate showed the higher initial performance than the NF substrate for B-NiFe-LDH, but the B-NiFe-LDH/CP stopped operating eventually even at milder conditions. Overall, using M-NiFe-LDH/NF electrode, the high energy conversion efficiency of 72.6% and an outstanding stability at a current density of 1 A cm -2 over 50 h could be achieved without carbonaceous material. This work highlights electrical conductivity and hydrophilicity of catalysts in membrane-electrode-assembly (MEA) as key factors for high performance AEMWE.
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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 | 0,001 | 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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».