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Record W3025639549 · doi:10.1149/ma2020-01462647mtgabs

Nanostructured Mixed Transition Metal Spinel Oxide Thin Films As Efficient Electrocatalysts – Composition, Structure and Properties

2020· article· en· W3025639549 on OpenAlexaff
Sreena Thekkoot, Rehana Islam, Sylvie Morin

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCopper-based nanomaterials and applications
Canadian institutionsYork University
Fundersnot available
KeywordsX-ray photoelectron spectroscopyMaterials scienceSpinelCyclic voltammetryTransition metalOxideChemical engineeringThermal decompositionScanning electron microscopeElectrochemistryInorganic chemistryElectrodeCatalysisChemistryPhysical chemistryMetallurgyComposite material

Abstract

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Transition metal oxides have received renewed attention with their demonstrated usefulness as cathodes in dye-sensitized solar cells and as anodes in fuel cell [1,2]. In addition, careful choice of the synthesis method and experimental conditions allow for the tailoring of the film nanostructure and surface area. However, it is clear from the literature [3,4] and our own work [5,6] that the experimental parameters used for the oxide material preparation can greatly affect its electrocatalytic properties and this often makes it difficult to compare material performances. We have prepared various spinel oxides, namely Cu x Co 3-x O 4 (0 ≤ x ≤ 1), Ni 1-x Cu x Co 2 O 4 (0 ≤ x ≤ 0.75) and Fe y Ni x-y Co 3-x O 4 (for y = 0.1 and 0.15 and x = 1 and 0.5, respectively), on FTO glass using the thermal decomposition method. The films were analyzed, using several structural, chemical and electrochemical methods such as x-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX), cyclic voltammetry and X-ray photoelectron spectroscopy (XPS). The oxygen evolution reaction (OER) and electroreduction of hydrogen peroxide reaction were used as model reactions to determine the electrocatalytic activity of the electrodes. The SEM analysis shows that the prepared thin films are quite porous and uniform. EDX analysis shows that a good correlation exists between stoichiometric and the resulting composition of the films. Cu x Co 3-x O 4 materials shows a tendency for more copper to be incorporated in the films, while for Ni 1-x Cu x Co 2 O 4 , an excess of Co and a deficiency of Cu is observed. The formation of the spinel structure is confirmed by XRD analysis. For Cu x Co 3-x O 4 , an increase of the lattice parameter with increasing copper content was observed. This supports the incorporation of the copper in the spinel structure. However, the increase of the lattice-parameter was not linear due to the formation of copper oxide at higher copper concentrations. For the Ni 1-x Cu x Co 2 O 4 series, the X-ray data also support the existence of the spinel structure. Using the film's real surface area, as determined by capacitance measurements, it is possible to compare the properties of materials of different roughness. The addition of Cu to Co 3 O 4 to form Cu x Co 3-x O 4 resulted in an increase in roughness for x values from 0.25 to 1. When Ni is added to form the ternary oxides, the roughness more than doubles. For spinel oxides containing iron, nickel and cobalt, the roughness is much lower, i.e., around 80. X-ray Photoelectron Spectroscopy was used extensively to understand cation site occupancy, composition and oxidation state of the metal ions in the ternary oxide materials. Our XPS data shows some differences between the bulk and surface compositions of our materials. The high-resolution spectra for the Co, Cu and Ni 2p peaks indicate the existence of different Co 2+ /Co 3+ , Cu + /Cu 2+ and Ni 2+ /Ni 3+ ratio for these materials. However, the amount of iron was often too small to be detected by XPS in iron containing samples with y ≤ 0.15. In general, the surface of the materials was found to be enriched with copper and deficient in cobalt. Larger Co 2+ /Co 3+ ratios are usually associated with better electrocatalytic properties towards OER. This points to the octahedral surface sites being the active sites. The analysis of O 1s spectra indicates that it is composed of three components that can be assigned to lattice oxygen, adsorbed oxygen containing species such as hydroxides and surface bonded water. During the presentation, our results will be compared to the morphology, structure, surface and bulk compositions, and electrochemical properties of spinel oxide films of similar compositions reported in the literature. References [1] W. Wang, X. Xu, Y. Liu, Y. Zhong, Z. Shao Adv. Energy Mater. 2018 , 8, 1800172 (1-24) [2] S. P.S. Shaikh, A. Muchtar, M. R. Somalu Renew. Sustain. Energy Rev 2015 , 51, 1-8 [3] M. S. Burke, S. Zou, L. J. Enman, J. E. Kellon, C. A. Gabor, E. Pledger, W. Boettcher J. Phys. Chem. Lett. 2015 , 6, 3737−3742 [4] R.L. Doyle, I.J. Godwin, M.P. Brandon, M.E.G. Lyons, Phys. Chem. Chem. Phys. 2013 , 15, 13737-13783. [5] S. Raju Thekkout, “Nanostructured mixed transition metal spinel oxide as efficient electrocatalysts” M.Sc. Thesis, York University, 2015 . [6] R. Islam, “Nanostructured ternary transition metal spinel oxide as efficient electrocatalysts” M.Sc. Thesis, York University, 2019 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.215
Teacher spread0.203 · 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 teacher head, 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
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