Nanostructured Mixed Transition Metal Spinel Oxide Thin Films As Efficient Electrocatalysts – Composition, Structure and Properties
Bibliographic record
Abstract
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 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".