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Enregistrement W2285588678 · doi:10.1149/ma2014-02/2/77

MnO<sub>2</sub>-Based Bifunctional Oxygen Catalyst for Rechargeable Metal/Air Batteries: The Effect of K<sub/> <sup>+</sup> Intercalation

2014· article· en· W2285588678 sur OpenAlexaff
Pooya Hosseini Benhangi, Előd Gyenge, Akram Alfantazi

Notice bibliographique

RevueECS Meeting Abstracts · 2014
Typearticle
Langueen
DomaineEnergy
ThématiqueElectrocatalysts for Energy Conversion
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésBifunctionalOxygen evolutionCatalysisTafel equationOverpotentialInorganic chemistryManganeseChemistryElectrolyteBifunctional catalystIntercalation (chemistry)Noble metalBattery (electricity)Materials scienceChemical engineeringElectrodeElectrochemistryOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

Extensive research has been undertaken to make intermittent clean and renewable energy sources more reliable. Bifunctional oxygen cathodes which can catalyze both ORR (oxygen reduction reaction) and OER (oxygen evolution reaction) are the backbone of rechargeable metal-air batteries as well as regenerative fuel cells [1-3]. Although noble metal family elements and alloys such as Pt , Pt-Au and Pt-Co are known as the best catalysts for ORR in alkaline media, their poor electrocatalytic activity toward OER as well as high price, comparing to non-PGM (non-precious group metal) compounds, limit their usage as a cost effective and active catalyst in bifunctional oxygen cathodes [2, 4]. Manganese oxides have been vastly employed as a robust cost-effective multifunctional and environmental friendly electrode material in battery industry, from primary to rechargeable metal-air batteries, as well as alkaline fuel cells and capacitors [3]. The electrolytic manganese dioxide (γ-MnO2) is known as the most electrochemically active crystallographic form of MnO2 for ORR in alkaline media with tafel slope of 40 mV dec-1 and a low overpotential of -375 mV [1, 5]. However, poor OER electrocatalytic activity of MnOx-based oxides in alkaline media diminish the hope of finding an exclusive bi-functional catalyst for both ORR and OER [1]. Our research is aimed at the development of highly active MnO2-based catalysts for both ORR and OER with long cycle life by adding non-precious metal compounds as co-catalysts and intercalating potassium ions into the catalyst layer. The mechanisms for OER and ORR of the mixed catalysts and the role of K+are investigated by a combination of surface characterization methods and electrochemical techniques. In the present work, LaCoO3 were synthesized via co-precipitation methods. MnO2-based Gas diffusion electrodes (GDE) were then prepared using the method described elsewhere [1]. In order to intercalate the potassium ions into the catalyst layer, a simple yet effective method has been used. The GDEs were kept in in 6M KOH solution at open cicuit potential while rotating the sample at 400 RPM for 6 days at 313 K. Cyclic voltammetry tests were performed in O2 saturated 6 M KOH at 293 K to investigate the electrocatalytic activity of the MnO2-LaCoO3 catalyst for both OER and ORR. The longer-term durability of the electrodes was also investigated by performing 100 repeated OER-ORR voltammetric cycles. Electron energy loss spectroscopy (EELS) has been also used to further analyze the catalyst layer and study the Mn valance changes during both OER and ORR. X-ray photoelectron spectroscopy (XPS) was also used to confirm the existence of intercalated K+ions in the catalyst layer. Interestingly, huge enhancement is observed in the OER/ORR performance of the activated catalyst comparing to the fresh electrodes without any K+ activation. Fig 1-a and 1-b show the OER and ORR voltammograms, respectively, of the fresh and activated MnO2-LaCoO3 GDEs as well as fresh MnO2 electrodes. The OER overpotential for MnO2-LaCoO3 decreases to 193 from 367 mV after intercalating potassium ions in the catalyst layer (Fig. 1-a). In the ORR region, activated MnO2-LaCoO3 electrodes still provides the lowest ORR overpotential of -321 mV (Fig. 1-b), which is far better than the ORR behavior reported in the literature for Core-Corena Bifunctional Catalyst (CCBC), needle-like MnOx thin film, CoMn2O4 and even nanostructured Mn oxide thin film [1]. Moreover, the activated catalyst performs almost without any degradation in OER region while suffering up to 61% decrease in the ORR current density at -250 mV (vs MOE) after 100 cycles of severe durability tests. Our results indicate that even 12 hrs of activation in 6 M KOH could enhance the electrocatalytic activity of the degraded catalyst after severe cycling to some point, mentioned before as “healing effect” [1]. The EELS analysis reveals that the Mn valance decreases during severe cycling from about 4 to 2.7 for the cycle No. 1 and 100, respectively. This confirms that the loss in the ORR electrocatalytic activity of the activated sample after 100 cycles is associated with the transformation of MnO2 to Mn3O4during severe cycling. References: [1] P.H. Benhangi, A. Alfantazi, E. Gyenge, Electrochimica Acta, 123 (2014) 42-50. [2] J. Ludwig, J. Power Sources, 155 (2006) 23-32. [3] A. Serov, A. Aziznia, P.H. Benhangi, K. Artyushkova, P. Atanassov, E. Gyenge, Journal of Materials Chemistry A, (2013). [4] Y. Chabre, J. Pannetier, Prog. Solid State Ch., 23 (1995) 1-130. [5] E.L. Gyenge, J.-F. Drillet, J. Electrochem. Soc., 159 (2012) F23-F34.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,008
Tête enseignante GPT0,210
Écart entre enseignants0,202 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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