Charge Storage Properties of Ferrimagnetic BaFe12O19 and Polypyrrole–BaFe12O19 Composites
Bibliographic record
Abstract
This investigation is motivated by an interest in multiferroic BaFe12O19 (BFO), which combines advanced ferrimagnetic and ferroelectric properties at room temperature and exhibits interesting magnetoelectric phenomena. The ferroelectric charge storage properties of BFO are limited due to high coercivity, low dielectric constant, and high dielectric losses. We report the pseudocapacitive behavior of BFO, which allows superior charge storage compared to the ferroelectric charge storage mechanism. The BFO electrodes show a remarkably high capacitance of 1.34 F cm−2 in a neutral Na2SO4 electrolyte. The charging mechanism is discussed. The capacitive behavior is linked to the beneficial effect of high-energy ball milling (HEBM) and the use of an efficient dispersant, which facilitates charge transfer. Another approach is based on the use of conductive polypyrrole (PPy) for the fabrication of PPy-BFO composites. The choice of new polyaromatic dopants with a high charge-to-mass ratio plays a crucial role in achieving a high capacitance of 4.66 F cm−2 for pure PPy electrodes. The composite PPy-BFO (50/50) electrodes show a capacitance of 3.39 F cm−2, low impedance, reduced charge transfer resistance, enhanced capacitance retention at fast charging rates, and good cyclic stability due to the beneficial effect of advanced dopants, HEBM, and synergy of the contribution of PPy and BFO.
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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 | 0.000 | 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".