Flexible Electrode Design: Fabrication of Freestanding Polyaniline-Based Composite Films for High-Performance Supercapacitors
Bibliographic record
Abstract
Polyaniline (PANI) is a promising pseudocapacitance electrode material. However, its structural instability leads to low cyclic stability and limited rate capability which hinders its practical applications. In view of the limitations, flexible PANI-based composite films are developed to improve the electrochemical performance of electrode materials. We report in the research a facile and cost-effective approach for fabrication of a high-performance supercapacitor (SC) with excellent cyclic stability and tunable energy and power densities. SC electrode containing a very high mass loading of active materials is a flexible film of PANI, tissue wiper-based cellulose, graphite-based exfoliated graphite (ExG), and silver nanoparticles with potential applications in wearable electronics. The optimum preparation weight ratios of silver nitrate/aniline and ExG/aniline used in the research are estimated to be 0.18 and 0.65 (or higher), respectively. Our results show that an ultrahigh capacitance of 3.84 F/cm(2) (240.10 F/g) at a discharge rate of 5 mA can be achieved. In addition, our study shows that the power density can be increased from 1531.3 to 3000 W/kg by selecting the weight ratio of ExG/aniline to be more than 0.65, with a sacrifice in the energy density. The obtained promising electrochemical properties are found to be mainly attributed to an effective combination of PANI, ExG, cushiony cellulose scaffold, and silver as well as the porosity of the composite.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".