High‐Power Lithium‐Ion Capacitor using LiMnBO<sub>3</sub>‐Nanobead Anode and Polyaniline‐Nanofiber Cathode with Excellent Cycle Life
Bibliographic record
Abstract
LiMnBO3 nanobeads (LMB-NB) with uniform size and distribution were synthesized using a urea-assisted microwave/solvothermal method. The potential application of LMB-NBs as an anode for a lithium-ion hybrid capacitor (Li-AHC) was tested with a polyaniline-nanofiber (PANI-NF) cathode in a nonaqueous LiPF6 (1 M)-ethylene carbonate/dimethyl carbonate electrolyte. Cyclic voltammetry (CV) and charge-discharge (C/DC) studies revealed that the PANI-NF/LMB-NB cell showed an exceptional capacitance behavior between 0-3 V along with a prolonged cycle life. A discharge capacitance of about 125 F g(-1) , and energy and power densities of about 42 Wh kg(-1) and 1500 W kg(-1) , respectively, could be obtained at a current density of 1 A g(-1) ; those Li-AHC values are higher relative to cells containing various lithium intercalation materials in nonaqueous electrolytes. In addition, the PANI-NF/LMB-NB cell also had an outstanding rate performance with a capacitance of 54 F g(-1) and a power density of 3250 W kg(-1) at a current density of 2.25 A g(-1) and maintained 94% of its initial value after 30000 cycles. This improved capacitive performance with an excellent electrochemical stability could be the result of the morphological features and inherent conductive nature of the electroactive species.
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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 | 0.001 |
| 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".