Improved Electrocatalytic Activity and Durability of NiMn<sub>2</sub>O<sub>4</sub>-CNTs as Reversible Oxygen Reaction Electrocatalysts in Zinc-air Batteries
Bibliographic record
Abstract
Faced with the increasingly serious energy crisis, fuel cells, as a clean and efficient power source, have become the most promising energy conversion devices and attracted significant attention during the last decades. Oxygen reduction reaction (ORR) at the cathode of fuel cells plays a decisive role in determination of the performance, and electrocatalysts with high-performance ORR are essential for practical applications. However, some big technical challenges are still encountered due to their inherently sluggish of cathodic ORR, which usually requires a significant number of noble metal catalyst [1, 2]. To overcome these bottlenecks, great attention has been paid to pursue non-precious metal or metal-free carbonaceous materials. Mesoporous carbon materials have been used for ORR due to their preeminent textural characteristics, high surface area, mechanical stability and mesoporous structure. However, the properties of mesoporous carbon materials base on not only the sizes and loction of the pore, but the heteroatoms doped into the carbon framework. It is believed that the quantity of N-doped and S-doped in carbon will be vastly different, if it was annealed at various reaction temperatures [3]. Herein, we use N and S co-doped mesoporous carbon which is prepared by polyquaternium-7 as a starting material to investigate the reaction with N2 at various temperatures. Nitrogen and sulfur co-doped mesoporous carbons were prepared by homogeneously mixing polyquaternium-7 and ferrous sulphate and silica. After drying overnight, the resulting solid was ground to a fine powder and then calcined at 600, 700, 800, 900 and 1000 for 1 hour in a nitrogen atmosphere. The silica was washed off in excess sodium hydroxide and dried. The excess metal Fe was removed in sulfuric acid at 85 ℃. Finally, the resulting catalytic graphite was pyrolyzed at 600 to 1000 ℃ for 1 hour again. Results of electrochemical characterizations for ORR were studied by cyclic voltammetry (CV) and linear sweep voltammetry (LSV) employing rotating disk electrode (RDE) technique. It is found that the temperature of the heat treatment is a significant parameter in synthesizing the high performance ORR catalysts. References [1] M.J. Wu, J.L. Qiao, K.X. Li, X.J. Zhou, Y.Y. Liu and J.J. Zhang, Green Chem. Vol., 18,2699 (2016) [2] M. Arenz, K.J. Mayrhofer, V. Stamenkovic, B.B. Blizanac, T.Tomoyuki, P.N. Ross and N.M. Markovic, J. Am. Chem. Soc. Vol., 127,6819 (2005) [3] S.B.Yang, L.J. Zhi, K. Tang, X.L. Feng, J. Maier, K. Müllen, Adv. Funct. Mater. 22, 3634 (2012).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".