Magnetic supercapacitors: Charge storage mechanisms, magnetocapacitance, and magnetoelectric phenomena
Bibliographic record
Abstract
Pseudocapacitive (PC) materials are under investigation for energy storage in supercapacitors, which exhibit exceptionally high capacitance, good cyclic stability, and high power density. The ability to combine high electrical capacitance with advanced ferrimagnetic or ferromagnetic properties in a single material at room temperature opens an avenue for the development of advanced magnetically ordered pseudocapacitive (MOPC) materials. This review covers materials science aspects, charge storage mechanisms, magnetocapacitance, and magnetoelectric (ME) phenomena in MOPC materials. Recent studies demonstrate high PC properties of advanced ferrimagnetic materials, such as spinel ferrites and hexagonal ferrites. Of particular importance is the discovery of PC properties of perovskite-type manganites, which exhibit room temperature ferromagnetism and giant negative magnetoresistance. The coupling of high capacitance and magnetization in MOPC provides a platform for strong ME interactions. Various strategies are used for manipulation of electrical capacitance/magnetization of MOPC by a magnetic field/electrode potential. Magnetocapacitance studies show significant increase in capacitance of MOPC under the influence of a magnetic field. Moreover, the application of a magnetic field results in enhanced energy density and power density, reduction of resistance, and improvement of cyclic stability. Such findings offer a potential of a breakthrough in the development of advanced supercapacitors. High magnetocapacitance and ME phenomena are linked to the influence of magnetic fields on electrolyte diffusion, structure of electrical double layer, charge transfer resistance, and variation of conductivity and magnetization of MOPC materials, which facilitate charge/discharge behavior. Various applications of ME effect in MOPC are discussed. Moreover, advantages of magnetocapacitive MOPC are described for applications in electronic and spintronic devices, supercapacitors, and devices for magnetically enhanced capacitive deionization of water.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".