Study on Electrochemical Stability and Charge Transfer Efficiency for the Development of High-Performance Supercapacitors Using Iron Oxide (Fe2O3) Nanorods
Bibliographic record
Abstract
A novel electrode material for electrochemical supercapacitors is introduced in this study: hydrothermally produced permeable iron oxide (Fe2O3) nanorods (NRs).The Fe2O3 nanorods exhibit exceptional crystallinity and phase purity, and X-ray diffraction (XRD) studies validated their cubic crystalline structure inside an Ia3 space collective.An examination of the morphology of the Fe2O3 NRs uncovered their nanostructured characteristics, such as a rod-shaped structure with an average dimension of about 30 nm.A record specific capacitance of 489 F/g was attained by conducting electrochemical performance studies using Fe2O3 NRs electrodes for supercapacitors at 10 mVs-1scan rate.The effective series resistance (ESR) was determined using electrochemical impedance spectroscopy (EIS).It measured 3.26 Ω, indicating a low resistance and efficient charge transport kinetics.Fe2O3 NRs electrodes exhibited exceptional chemical stability, maintaining excellent capacitance even after 500 charge-discharge cycles at a current density of 6 Ag-1.This study presents a scalable method for creating high-performance supercapacitors using Fe2O3 NRs to improve the development and design of upcoming energy storage devices.
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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) | 0.000 | 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 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".