Synergy of Charge Storage Properties of CuO and Polypyrrole in Composite CuO-Polypyrrole Electrodes for Asymmetric Supercapacitor Devices
Bibliographic record
Abstract
This investigation is motivated by interest in the redox properties of CuO for energy storage in supercapacitors and in the fascinating effects of charge transfer in conductive polymer–metal oxide composites on their physical and chemical properties. Various challenges are successfully addressed, such as efficient utilization of capacitive properties of charge storage materials in high active mass loading electrodes; understanding charge storage mechanisms at different electrode potentials; fabrication of anodes with high areal capacitance, which can match the capacitance of advanced cathodes; and fabrication of advanced asymmetric supercapacitor devices with high specific energy. CuO nanoparticles are prepared by hydrothermal synthesis and polypyrrole (PPy) particles are prepared by chemical polymerization for the fabrication of CuO and composite PPy-CuO anodes. An important finding is the synergistic effect of capacitive properties of PPy and CuO, which facilitates the fabrication of anodes with a record high capacitance of 7 F cm –2 in a 0.5 M Na 2 SO 4 electrolyte. The capacitance, impedance, and charge transfer resistance of the composites are optimized by investigating electrodes with different PPy contents. The superior behavior of the composites is linked to the enhanced charge transfer, which results in a low impedance and reduced charge transfer resistance. The composite electrodes show good capacitance retention at fast charge–discharge rates and good cyclic stability. The asymmetric supercapacitor devices show high capacitance of 2.76 F cm –2 in a voltage window of 1.5 V, high energy density of 10.83 Wh kg –1, and good cyclic stability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".