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Record 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 on OpenAlexaff
Yu Pei, David P. Wilkinson, Előd Gyenge

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBifunctionalOxygen evolutionCatalysisElectrocatalystManganeseElectrochemistryInorganic chemistryChemistryRedoxElectrolysisElectrolyteOxygenBifunctional catalystMaterials scienceChemical engineeringElectrodeOrganic chemistry

Abstract

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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

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.222
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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