Electrochemical Characterization of Polyaniline in Nonaqueous Electrolyte and Its Evaluation as Electrode Material for Electrochemical Supercapacitors
Bibliographic record
Abstract
In this study, the performance of a polyaniline (PANI) based supercapacitor where electroactive PANI films were prepared on carbon paper electrodes from a nonaqueous solution with an organic acid as the proton source was investigated. The use of nonaqueous media as electrolyte led to an increase of the electroactivity window from 0.75 V in aqueous media up to 1.0 V. Low frequency capacitance, evaluated by electrochemical impedance spectroscopy, of about 150 F/g is reported. Scanning electron microscopy indicated a highly porous material for deposited charges greater than 1 C/cm 2 . Constant current charge/discharge cycling of a symmetric supercapacitor based on PANI in nonaqueous medium was performed in a two-electrode cell configuration and a loss of about 60% of the discharge capacity was demonstrated after 1000 cycles. Tetramethylammonium methanesulfonate was also used instead of tetraethylammonium tetrafluoroborate as supporting electrolyte in acetonitrile for the charge/discharge testing of the PANI-PANI capacitor. Energy and power densities of approximately 3.5 Wh/kg and 1300 W/kg, respectively, were developed by this supercapacitor for a cell voltage of 1 V and a discharge time of 20 s. On the other hand, an asymmetrical supercapacitor with polypyrrole and polyaniline used as positive and negative electrodes, respectively, displayed slightly improved performance. Indeed, an energy density of 5 Wh/kg and a power density of 1200 W/kg were reported for discharge time of about 20 s with 1 M as electrolyte. © 2000 The Electrochemical Society. All rights reserved.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".