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Record W2784494775 · doi:10.1149/ma2018-01/30/1798

MOF-Based Nano-Cuboids Electrocatalyst for OER-HER Reactions

2018· article· en· W2784494775 on OpenAlexaff
Wook Ahn, Moon Gyu Park, Dong Un Lee

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectrocatalystCatalysisZeolitic imidazolate frameworkMetal-organic frameworkTransition metalHeteroatomMaterials scienceNickelChemical engineeringImidazolateNanotechnologyCarbon fibersCobaltInorganic chemistryChemistryElectrochemistryElectrodeAdsorptionOrganic chemistryComposite numberMetallurgyPhysical chemistryComposite material

Abstract

fetched live from OpenAlex

Recently, metal organic framework (MOF) derived catalysts, typically synthesized using precursors consisting of transition metals and organic linkers, have emerged as promising active and inexpensive electrocatalysts due to their intrinsic advantages of high porosity, three-dimensional structures, and compositional flexibility. In particular, MOFs with organic ligands containing carbon, nitrogen, and sulfur atoms coordinated to transition metal centers have been reported to form three dimensional and uniformly porous structures, resulting in considerably increased active surface area and enhanced physical properties.[1-5] These MOFs, often composed of transition metal atoms such as nickel, cobalt, and iron, and heteroatoms such as nitrogen, sulfur, and phosphorus, are characterized by strong interactions between them[6,7], which can serve as electrocatalytically active sites for HER and OER. The advantages of MOF-derived active materials in advanced energy conversion and storage applications have been recently highlighted as efficient electrocatalysts for fuel cells, metal-air batteries, and electrolyzers. For example, Gadipelli et al. recently reported a design route for the synthesis of MOF-derived electrocatalysts, in which zeolitic imidazolate framework (ZIF) was used as the template. The resulting MOF catalyst containing active Co-N-C species demonstrated efficient ORR and OER activities. Yu et al. reported an active OER electrocatalyst based on porous carbon coated nickel phosphides (NiP) prepared using Ni-based PBA nanoplates as a template. The structural advantages of MOFs allowed NiP catalyst to demonstrate superior electrocatalytic activity towards OER compared to NiO and Ni(OH)2 counterparts. Despite these electrocatalyst developments, however, bi-functional MOF-derived electrocatalysts active towards both HER and OER for water-splitting application have rarely been reported to the best of our knowledge. In this study, we introduce novel MOF containing Ni-Co-Fe transition metal centers, denoted NCF-MOF, as a dual-function water-splitting catalyst for enhancing HER and OER activities. The morphology of the catalyst is revealed to exhibit nano-cuboid structure with multiple meso- and micro-sized pores prepared via a facile synthesis procedure. As MOF catalyst precursors, transition metal-based PBA nanocubes with a chemical formula Mx II[My III(CN)6]z▪H2O, where MII and MIII are divalent and trivalent transition metal cations, respectively, have selected to obtain unique structure and composition of NCF-MOF multi-hollow nano-cuboids. Specifically, PBA nanocube precursors containing nickel, cobalt, and iron have been utilized to maintain the general nano-cuboidal structure, while optimizing the composition of transition metal centers for efficient OER and HER activities. This makes NCF-MOF one of the most promising non-precious electrocatalysts for water-splitting applications in various ways; (i) significantly extended active surface area with high porosity, (ii) formation of active nitrogen species during facile synthesis, and (iii) optimized electronic structure of transition metals for electrocatalysis via oxidation state control. These main electrocatalytic contributors that affect OER and HER have been successfully obtained through careful selection of PBA precursors and the facile synthesis procedure. Furthermore, excellent electrochemical stability has been realized NCF-MOF catalyst which is also attributed to high uniformity of porous nano-cuboidal structure which allow rapid charge transfer and transport of active species. The dual-function of the catalyst and its stability has been confirmed by three-electrode half-cell evaluations, as well as nickel-foam loaded active electrodes for practical demonstrations as efficient and stable References [1] A. Mahmood, W. Guo, H. Tabassum and R. Zou, Adv. Energy Mater., 2016. [2] Z. Li, M. Shao, L. Zhou, R. Zhang, C. Zhang, M. Wei, D. G. Evans and X. Duan, Adv. Mater., 2016, 28, 2337-2344. [3] B. Y. Xia, Y. Yan, N. Li, H. B. Wu, X. W. Lou and X. Wang, Nat. Energy, 2016, 1, 15006. [4] X. Y. Yu, L. Yu, H. B. Wu and X. W. Lou, Angew. Chem. Int. Ed., 2015, 54, 5331-5335. [5] L. Han, X. Y. Yu and X. W. Lou, Adv. Mater., 2016, 28, 4601-4605. [6] T. Y. Ma, S. Dai, M. Jaroniec and S. Z. Qiao, J. Am. Chem. Soc., 2014, 136, 13925-13931. [7] X. F. Lu, P. Q. Liao, J. W. Wang, J. X. Wu, X. W. Chen, C. T. He, J. P. Zhang, G. R. Li and X. M. Chen, J. Am. Chem. Soc., 2016, 138, 8336-8339. 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 score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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
Published2018
Admission routes1
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