Sodium Hybrid Capacitor: A Next Generation Energy Storage System
Bibliographic record
Abstract
Sodium ion batteries are emerging candidate for next generation high energy application including electrical vehicles and grid storage.[1] Rather than the similar working principle, the wide availability and low cost of sodium made them a suitable and an interesting candidate for large energy applications. The research for sodium ion batteries is majorly on improving their poor kinetics due to their large ionic radii resulting in low energy and power density.[2]The possible solution could be designing a hybrid capacitor which greatly improves the energy density and power density simultaneously because of their fast kinetics. In this work, we have developed and fabricated a new high performing 3 V sodium hybrid capacitor (NHC) using NASICON structured Na3V2(PO4)3 – (NVP) and a carbon derived from bio resource in an organic electrolyte. Two reactions occurs simultaneously, (i) intecalaction / deintercalation of sodium ions in NVP which brings high energy density, (ii) adsorption/ desorption of anion in the bio carbon giving high power density. An energy density of 118 Wh kg−1 has been achieved at a specific power of 95 W kg−1, retaining 60 Wh kg−1 of energy at high specific power of 850 W kg−1. A superior and an extremly outstanding stability of 95% is achieved after 10,000 cycles. The obtained results are one of the highest ever reported and it outperforms the present lithium hybrid capacitor by all means (energy density, power density, stability). The results will be presented and discussed in detail. References: 1) N. Yabuuchi,M. Kajiyama, J. Iwatate, H. Nishikawa, S. Hitomi, R. Okuyama, R. Usui, Y. Yamada, S. Komaba, Nat.Mater. 2012, 11, 512. 2) V. Etacheri, R. Marom, R. Elazari, G. Salitra, D. Aurbach, Energy Environ. Sci. 2011, 4, 3243. Figure 1
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".