(Keynote) Oxygen Reduction and Evolution Reactions on Faceted Mn<sub>x</sub>Co<sub>1-X</sub>Fe<sub>2</sub>O<sub>4</sub> Nanoparticles Prepared By Induction-Coupled Plasma
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Bibliographic record
Abstract
Substantial research efforts are directed toward the development of precious metal-free catalysts for fuel cells, metal-air batteries and electrolyzers, because the deployment of these technologies requires the synthesis of low-cost catalysts with controlled properties in large quantities. Mixed spinel oxides are a promising class of catalytic materials for the oxygen evolution (OER) and oxygen reduction (ORR) reactions, and thus several works have been devoted to the understanding of the structure – composition – activity relationships. Examples include the correlation between activity of spinel oxides and the covalency of the bond formed between the oxygen species and the metal cation in the octahedral sites 1 , or the possible role of metal cations in the tetrahedral sites in the oxygen electrocatalysis 2 . However, studies highlighting the importance of the facet engineering on the electrocatalytic activity of spinel oxides 3 are still rare. Here, we will present our recent work on facetted nanoparticles Mn x Co 1-x Fe 2 O 4 (0 ≤ x ≤ 1) prepared by thermal plasma induction; a one step 4 , cost-effective and scalable method allowing the synthesis of large amounts (up to 30 g h -1 for 50 kW units) of uniform and crystalline nanoparticles 5 . Structural characterization by X-ray diffraction and TEM-EELS analysis showed that the mixed ferrite nanoparticles are formed by individual nanocrystals with well-defined truncated octahedron shape and with {100} and {111} facets mainly exposed, have high crystallinity, a median particle size of 40 nm and a homogeneous composition down to the atomic level. Electrochemical studies conducted in 0.1M KOH using the rotating disk electrode showed the highest activity was found for carbon black + Mn 0.5 Co 0.5 Fe 2 O 4 composite electrode: half-wave potential for oxygen reduction 140 mV more negative than that of 20 wt% Pt/C; 420 mV oxygen evolution overpotential at 10 mAcm -2 (identical to IrO 2 /C). These are among the best performances reported for ferrites considering the size of the nanocrystals. Computational studies using density functional theory used to study the adsorption of oxygen molecule on the {100} and {111} facets of both CoFe 2 O 4 and Mn 0.5 Co 0.5 Fe 2 O 4 demonstrated that the Mn 0.5 Co 0.5 Fe 2 O4 {111} surface appears to have a highest affinity for the O 2 molecule. The sites with lowest adsorption energy on each surface were identified and further analysis of O-O bond length and frequency as well as the Mulliken charge and populations confirmed the activation of the adsorbed O 2 molecule. The energy diagrams of the ORR and OER computed for both Mn 0.5 Co 0.5 Fe 2 O 4 {100} and {111} surfaces also pointed for a higher electrocatalytic activity for the {111} facet. References [1] Y. Zhou, S. Sun, C. Wei, Y. Sun, P. Xi, Z. Feng, Z. J. Xul, Adv. Mater. 31 , 1902509 (2019). [2] A. Bergmann, E. Martinez-Moreno, D. Teschner, P. Chernev, M. Gliech, J. Ferreira de Araujo, T. Reier, H. Dau and P.Strasser, Nature Commun. , 6 8625(2015). [3]J. Xiao, Q. Kuang, S. Yang, F. Xiao, S. Wang, L. Guo, Sci. Rep. , 3 , 1 (2013). 4 J. Chen et al, in preparation. [4] A.Y. Li, N. Dumaresq, A. Segalla, N. Braidy, A. Moores, ChemCatChem. , 11 , 3958,(2019) . Acknowledgements This work was financially supported by the Centre Québécois des Matériaux Fonctionnels (CQMF, program “Projets de recherche collaboratives”) and by Natural Sciences and Engineering Research Council of Canada (NSERC, Discovery Grants of A.C.T and N.B.). N.B. also wish to acknowledge the funding support from Canada Research Chairs program and the Plateforme de Recherche et d’Analyse des Matériaux of Université de Sherbrooke (PRAM). A.C.T. and S.M. acknowledge the support from Compute Canada (www.computecanada.ca) supercomputing facility. J.C. acknowledges the financial support from Fonds de Recherche du Québec – Nature et Technologie (FRQNT, PhD scholarship “Énergie #286570 ” ).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it