Electro-Deposition and Dissolution of MnO<sub>2</sub>on a Graphene Composite Electrode for Its Utilization in an Aqueous Based Hybrid Supercapacitor
Bibliographic record
Abstract
The electro-deposition and dissolution of MnO2 is studied for its potential utilization in hybrid supercapacitors. A commercially available graphene powder is used as high surface area substrate and capacitive type electrode. An aqueous electrolyte composed of 0.5 M H2SO4 + 0.5 M MnSO4 is used. The deposition-dissolution reaction of MnO2 is shown to provide the bulk of the charge storable in the battery type electrode. Furthermore, the potential window of stability of this electrode reaction is compatible with the aqueous electrolyte. Two complete systems were assembled and tested for their charge/discharge behavior. It is shown that energy and power densities of 25 Wh kg-1 and 980 W kg -1, respectively, can be achieved for at least 5000 cycles. Limitations of the system in terms of cycle numbers and electrolyte volume are discussed in more detail. The electrolyte volume to electrode mass ratio is shown to be a critical factor in determining the charge/discharge cycle number of the device. This is believed to be due to the fact that the efficiency of the MnO2 electro-dissolution/deposition process is less than 100%. This, in turn, could result in gradual pH changes and a lower Mn2+ concentration in the electrolyte during continues charging and discharging. This eventually results in lowering the energy and power density of the system. However, it is shown that an energy density of 25 Wh kg-1 is achievable, thus being comparable with similar hybrid systems. © 2012 The Electrochemical Society. All right reserved.
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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 | 0.000 |
| 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".