Effect of carbon nanotube loadings on supercapacitor characteristics
Bibliographic record
Abstract
In order to improve the properties of electrodes based on carbon nanotubes (CNTs), nanocomposite electrodes of CNTs/activated carbon (AC) are prepared. The effect of CNT loadings on the performance of the nanocomposite electrodes is evaluated by electrochemical methods. Scanning electron microscopy images show the CNTs are well dispersed, entwine with the AC, and form a more conductive network in a nanocomposite electrode. When CNT loadings increase from 0 to 10 wt%, the capacitance increases by 15% (89.4 to 102.5 F g−1), and the equivalent series resistance (ESR) decreases by 13% (0.93 to 0.81 Ω). The capacitance improvement has an optimum CNT loading of about 6 to 10 wt%. The decreased ESR with high CNT loadings does not prevent capacitance loss at sweep rates greater than 50 mV s−1. The nanocomposite electrode shows good cycle performance with no capacity loss after 5000 cycles at a scan rate of 500 mV s−1. These results indicate that the CNT-based nanocomposite electrodes would be a promising material for use in supercapacitors. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.004 | 0.001 |
| 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 | 0.001 | 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".