Incorporating Co and Y into Amorphous Ni-Based Alloys to Stabilize Hydrous β-NiOOH for Efficient Electrocatalytic Water Oxidation
Notice bibliographique
Résumé
The use of novel anion exchange membranes (AEM) are of interest in a wide variety of electrochemical systems. On particular interest is in alkaline water electrolysers since it eliminates the aqueous KOH electrolyte and can provide improved form factors and much higher current densities that rival proton exchange membrane (PEM) electrolysers.1 The use of AEM water electrolysis also enables the use of less expensive earth-abundant non-platinum group metals (PGM) materials, such as nickel-based alloys as electrocatalysts.1 Conventional Ni electrocatalysts for the oxygen evolution reaction (OER) still display large overpotentials and slower reaction kinetics. The addition of secondary metals, such as Fe and Co, are commonly added to enhance the OER performance but suffer from stability issues. 2–4 The leaching of Co is noted to be much less severe which allows for more long-term electrocatalytic benefits to Ni by way of stabilizing the β-NiOOH phase over γ-NiOOH.4–6 As a result, Co is a very desired alloying element but a reduction in the amount used is required as Co is quickly becoming limited in supply due to it being essential for many renewable energy applications.7 Recent studies have shown that Y has catalytic synergy with Co by accepting excess electrons to facilitate OH- absorption and improve the formation of active intermediates.8,9 These findings indicate Y can enhance the OER activity of Co and reduce the Co concentration required. In this work, amorphous Ni79.2-xCoxNb12.5Y8.3 (x = 0 and 5 at.% Co) nanoparticles were synthesized using cryogenic mechanical alloying followed by surfactant-assisted high energy ball milling (SA-HEBM).10 This two-stage ball milling process provided a novel processing route for the production of nanostructured / amorphous materials with a wide range of possible compositions not achievable through rapid solidification, electrodeposition, or chemical reduction techniques. The resulting structures were characterized through x-ray diffraction and electron microscopy. The electrocatalytic activity and stability of amorphous nanoparticles on the alkaline oxygen evolution reaction were investigated through prolonged cyclic voltammetry and Tafel measurements. Cyclic voltammagrams demonstrated stable and reproducible curves for amorphous alloys up to 10000 cycles while crystalline Ni and Ni95Co5 showed signs of deactivation with cycling. Initially the addition of Co to crystalline Ni resulted in enhanced OER catalytic performance, but the performance drastically reduced beyond 500 cycles. A similar increase in performance was observed when adding Co to amorphous Ni79.2Nb12.5Y8.3, except the activity and stability was maintained throughout the 10000 cycles. The pairing of X-ray photoelectron spectroscopy (XPS) revealed no signs of overcharging in amorphous Ni74.2Co5Nb12.5Y8.3 and that the Y and Co were integrated into the Ni oxy-hydroxide structure. In contrast, XPS analysis of amorphous Ni79.2Nb12.5Y8.3 showed signs of overcharging which resulted in Y segregating from the surface to form Y2O3. From these results it is found that the presence of Co in amorphous Ni-based alloys stabilizes β-NiOOH and allows Y to remain incorporated for providing synergistic benefits. The presence of Co and Y in amorphous Ni-based materials is shown to enhance the OER activity and provide excellent long-term cycling stability. These features, along with the high surface area achieved through SA-HEBM, provide a cost-effective and simple method for producing stable and active amorphous electrocatalysts for the oxygen evolution reaction in AEM water electrolysis. V. R. Stamenkovic, D. Strmcnik, P. P. Lopes, and N. M. Markovic, Nat. Mater., 16, 57–69 (2016). F. Lyu, Q. Wang, S. M. Choi, and Y. Yin, Small, 15, 1804201 (2019). I. Roger, M. A. Shipman, and M. D. Symes, Nat. Rev. Chem., 1, 1–13 (2017). D. Y. Chung et al., Nat. Energy, 5, 222–230 (2020). T. N. Lambert et al., Chem. Commun., 51, 9511–9514 (2015). K. M. Cole, D. W. Kirk, and S. J. Thorpe, J. Electrochem. Soc., 165, J3122–J3129 (2018). X. Sun, H. Hao, Z. Liu, F. Zhao, and J. Song, Resour. Conserv. Recycl., 149, 45–55 (2019). M. Kim, B. Lee, H. Ju, S. W. Lee, and J. Kim, Adv. Mater., 31, 1901977 (2019). G. Zhang, B. Wang, L. Li, and S. Yang, Small, 15, 1904105 (2019). S. Ghobrial, K. M. Cole, D. W. Kirk, and S. J. Thorpe, Electrocatalysis, 10, 680–689 (2019). Figure 1
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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) | 0,000 | 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) | 0,001 | 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 ».