Electrochemical Characterization of Vanadium Nitride as Pseudocapacitive Electrode for Aqueous Electrochemical Capacitor
Bibliographic record
Abstract
Whereas most of the supercapacitors on the market are designed with activated carbon electrodes, current research is focused toward the development of alternative materials exhibiting high energy and power densities and long term cycling efficiency. Some transition metal oxides such as RuO 2 1 or MnO 2 2 exhibit high specific capacity while there density is up to 8 times higher than the density of activated carbon. These interesting features are explained by fast and reversible redox reactions taking place in the near surface of the active material particles. This phenomenon is referred to as pseudocapacitance. The main drawbacks are the high cost of RuO 2 , and the poor electronic conductivity of MnO 2 thus considerably limiting the power capability of an electrode using such a material. In 1998, Lui et al. reported similar pseudocapacitive behavior of a molybdenum nitride electrode in acidic electrolyte 3 and only a single article was published with reference to this topic. 4 . In 2006, nitride compounds regained some interest concerning energy storage after Choi et al. reported an impressive capacity of 1340 F/g for a vanadium nitride electrode in alkaline electrolyte 5 . Considering its attractive capacity but also its high electronic conductivity, VN has been intensively studied since that time concerning new syntheses and processes involving xerogel 6 , nanotubes coating 7 and TiN/VN core/shell nanostructure 8 . Choi et al. suggested that the pseudocapacitive behavior of the vanadium nitride electrode can be explained by an equilibrium reaction implicating OH - ions adsorption and reversible redox reactions of an oxidized surface resulting from VN oxidation. However, only few studies were aimed at understanding the charge storage mechanism. Indeed, while Pande et al. confirmed the role of OH - anions in the reversible redox process 9 , large differences in specific capacity and stability are reported in the literature. These differences can be attributed to the large diversity within the synthesis method, which often used oxides as a precursor to oxy-nitrides rather than nitrides. However, as demonstrated by the observation of an unexplained irreversible anodic process in different studies 6,10 , a lack of understanding in the different charge storage mechanisms involved exists. In this communication, the synthesis of a model material VN deposited as thin film will be described, followed by electrochemical investigations accompanied with in-situ and ex-situ characterizations. The main goal of this work is to get some insight in the different reactions involved in the charge storage mechanism and to determine the suitable conditions of utilization of VN so as to obtain a highly stable active electrode material. (1) Zheng, J. P.; Cygan, P. J.; Jow, T. R. J. Electrochem. Soc. 1995 , 142 , 2699–2703. (2) Lee, H. Y.; Goodenough, J. B. J. Solid State Chem. 1999 , 144 , 220–223. (3) Liu, T.-C.; Pell, W. G.; Conway, B. E. J. Electrochem. Soc. 1998 , 145 , 1882–1888. (4) Roberson, S. L.; Finello, D.; Davis, R. F. J. Appl. Electrochem. 1999 , 29 , 75–80. (5) Choi, D.; Blomgren, G. E.; Kumta, P. N. Adv. Mater. 2006 , 18 , 1178–1182. (6) Zhou, X.; Chen, H.; Shu, D.; He, C.; Nan, J. J. Phys. Chem. Solids 2009 , 70 , 495–500. (7) Ghimbeu, C. M.; Raymundo-Piñero, E.; Fioux, P.; Béguin, F.; Vix-Guterl, C. J. Mater. Chem. 2011 , 21 , 13268–13275. (8) Dong, S.; Chen, X.; Gu, L.; Zhou, X.; Wang, H.; Liu, Z.; Han, P.; Yao, J.; Wang, L.; Cui, G.; Chen, L. Mater. Res. Bull. 2011 , 46 , 835–839. (9) Pande, P.; Rasmussen, P. G.; Thompson, L. T. J. Power Sources 2012 , 207 , 212–215. (10) Glushenkov, A. M.; Hulicova-jurcakova, D.; Llewellyn, D.; Lu, G. Q.; Chen, Y. Chem. Mater. 2010 , 22 , 914–921.
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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 | 0.001 | 0.002 |
| 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".