Designing Nanoparticles for Optimized Pseudocapacitive Energy Storage
Bibliographic record
Abstract
Power harvesting from intermittent renewable energy sources requires high charge storage capacity without compromising charging speed. These properties are achievable within hybrid capacitors by enhancing the pseudocapacitive (Faradaic) charge storage relative to the double-layer (non-Faradaic) charge storage, via the overlapping of equally-spaced redox reactions to reach a near ideal voltammetry profile. In this work, we examine how the structure of nanoparticles may be utilized to tune the pseudocapacitive response. This is accomplished by utilizing Gerischer-Hopfield electron transfer theory to capture the effects of redox species solvation through the solvent reorganization energy. Our model translates the total-energy picture by Marcus-Hush theory into single-particle picture for electron transfer in Faradaic charge storage processes, thereby arriving at a general phenomenological description of how pseudocapacitive properties can be engineered at the nanoscale. We also explore the design limitations of such nanoparticle-derived pseudocapacitance through a fundamental consideration of electron transfer energetics and kinetics. In general, our analysis is intended to aid the development enhanced pseudocapacitive properties in hybrid capacitor systems.
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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 | 0.001 | 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".