Investigation of energy storage performance and cycling stability of electrochemically synthesized PANI–ZnFe2O4 electrodes
Bibliographic record
Abstract
Conducting polymer-metal oxide hybrids are promising electrode materials for supercapacitors, yet achieving a balance between high capacitance and long-term stability remains challenging. In this work, polyaniline (PANI) - zinc ferrite (ZnFe₂O₄) composites were synthesized by in situ electrochemical polymerization of aniline with controlled deposition duration for ZnFe 2 O 4 -nanoparticle incorporation. Structural and spectroscopic characterization confirmed uniform dispersion of ZnFe 2 O 4 within the polymer matrix and the formation of fibrous nanostructures. Electrochemical analysis revealed a progressive enhancement of redox activity and charge storage with increasing ZnFe 2 O 4 content. The optimized composite exhibited a specific capacitance of up to 1402 F g⁻¹ at 1 A g⁻¹, together with an energy density of 141.9 Wh kg⁻¹ and a power density of 404.9 W kg⁻¹. When assembled into a symmetric supercapacitor, the PANI-zinc ferrite composite retained 97.6% of its initial capacitance after 10,000 charge–discharge cycles. Electrochemical impedance spectroscopy further indicated that structural degradation under accelerated aging is primarily associated with particle and polymer chain cracking/breaking, leading to increased mass transport resistance, thereby reducing the energy storage capability.
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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 | 0.001 |
| 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".