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Enregistrement W3117757939 · doi:10.1149/ma2020-02582873mtgabs

Insights into Electrochemical Behavior of Manganese Oxides in Catalyzing the Oxygen Reduction and Evolution Reactions and the Effect of Operation Conditions

2020· article· en· W3117757939 sur OpenAlexaff
Yu Pei, David P. Wilkinson, Előd Gyenge

Notice bibliographique

RevueECS Meeting Abstracts · 2020
Typearticle
Langueen
DomaineEnergy
ThématiqueElectrocatalysts for Energy Conversion
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésBifunctionalOxygen evolutionCatalysisElectrocatalystManganeseElectrochemistryInorganic chemistryChemistryRedoxElectrolysisElectrolyteOxygenBifunctional catalystMaterials scienceChemical engineeringElectrodeOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

To address the needs for clean energy, the regenerative fuel cell (RFC) and rechargeable metal-air batteries are considered as very promising approaches. Notwithstanding the abundant investigation in the past decades, their viability is still limited by the sluggish oxygen reactions on the oxygen electrode and the scarcity of conventional noble metal electrocatalysts (e.g. Pt, Ir, Ru, and their oxides) for the oxygen reduction (ORR) and oxygen evolution reactions (OER). For enhancing the bifunctional catalytic activity on the oxygen electrode, manganese oxides-based materials are under the spotlight due to their bifunctional electrocatalysis performance for both fuel cell (FC) and water electrolysis (WE) working modes in alkaline media at a low cost. However, the multivalent and diverse polymorphism of MnOx can lead to a series of complex electrochemical reactions that present different oxygen catalytic activities towards ORR and OER. To date, only a limited amount of study has been done on ultrafine manganese-based core-shell bifunctional oxygen catalysts and there remains the insufficient understanding of the ORR/OER catalysis mechanism as well as the redox pathway of the Mn sites. To address the knowledge gap in the literature, we have investigated the oxygen catalysis bifunctionality and the Mn site electrochemical behavior of Mn/Mn3O4 core-shell structural nanomaterial, and compared this to the commonly used β-MnO2, γ-MnO2 commercial catalysts in 5 M potassium hydroxide electrolyte. The crystalline structures of these commercial samples were characterized by X-ray diffraction (XRD). It should be noted that in the case of the nano core-shell structural sample, besides the diffraction from the Mn (core) and the Mn3O4 (shell) planes, the diffraction pattern also possesses intensive ramsdellite diffraction peaks. Its surface defects (oxygen vacancies), amorphous shell structure and hybrid Mn oxidation states lead to a facilitated potassium uptake in the MnOx polyhedrons1, suppression of Mn dissolution by the K-MnOx bonding structure reinforcement2, and higher oxygen adsorption capacity3 with an enlarged surface adsorption energy4. With the help of cyclic voltammetry of different types of manganese oxide, we have uncovered a series of electrochemical and chemical reactions involved with the change of Mn oxidation states. The difference in the crystallographic structure between different samples is revealed in their electrochemical response (Fig. 1 and Fig. 2). In terms of potassium uptake, it is favoured in ramsdellite crystalline through their wide 1 X 2 tunnels and in the Mn3O4 amorphous area by absorption instead of the narrow 1 X 1 tunnels in pyrolusite crystalline. This crystallographic dissimilarity results in different Mn site oxidation and reduction pathways. After initial cycling, some parallel behaviors among these oxides can be observed. In addition, we also investigated the effect of the operating voltage range. In comparison to the ORR or OER operating mode, when the voltage range was extended to cycle between the ORR and OER potential range, the Mn/Mn3O4 electrodes delivered enhanced O2 and HO2 - reduction activities along with boosted OER performance. With respect to O2 in the electrolyte, the dissolved O2 not only acts as a reactant for the ORR reaction but also influences the OER activity. Notwithstanding the oxygen molecule may block the active sites on the bulk catalysts (e.g., β-MnO2 and γ-MnO2) and thereby diminish their OER capability by half, the Mn/Mn3O4 shows double the OER current density in O2 saturated 5 M KOH electrolyte. These interesting results require a better understanding of the Mn site oxidation and reduction pathways along with oxygen reaction catalysis. The influence of operational conditions should also be considered in the protocol for bifunctional catalytic activity assessment. Among the investigated samples, the structural crystalline ramsdellite shows better electrochemical behavior and performance in comparison to the pyrolusite material. In particular, the core-shell structural Mn/Mn3O4 offers a potential approach to meet the needs of the practical reversible oxygen reactions in the RFC without losing OER catalytic activity or the need to purge the electrolyte between charge and discharge. References P. H. Benhangi, A. Alfantazi, and E. Gyenge, Electrochim. Acta, 123, 42–50 (2014). G. Fang et al., Adv. Funct. Mater., 29, 1808375 (2019). S. Yan, Y. Xue, S. Li, G. Shao, and Z. Liu, ACS Appl. Mater. Interfaces, 11, 25870–25881 (2019). B. C. Han, C. R. Miranda, and G. Ceder, Phys. Rev. B - Condens. Matter Mater. Phys., 77, 075410 (2008). Figure 1

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 seuil0,002

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 Opus0,006
Tête enseignante GPT0,222
Écart entre enseignants0,216 · 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
Publié2020
Routes d'admission1
Résumé présentoui

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