Hybrid Device Employing Three-Dimensional Arrays of MnO in Carbon Nanosheets Bridges Battery–Supercapacitor Divide
Bibliographic record
Abstract
It is a challenge to meld the energy of secondary batteries with the power of supercapacitors. Herein, we created electrodes finely tuned for this purpose, consisting of a monolayer of MnO nanocrystallites mechanically anchored by pore-surface terminations of 3D arrays of graphene-like carbon nanosheets ("3D-MnO/CNS"). The biomass-derived carbon nanosheets should offer a synthesis cost advantage over comparably performing designer nanocarbons, such as graphene or carbon nanotubes. High Li storage capacity is achieved by bulk conversion and intercalation reactions, while high rates are maintained through stable ∼20 nm scale diffusion distances. For example, 1332 mAh g(-1) is reached at 0.1 A g(-1), 567 mAh g(-1) at 5 A g(-1), and 285 mAh g(-1) at 20 A g(-1) with negligible degradation at 500 cycles. We employed 3D-MnO/CNS (anode) and carbon nanosheets (cathode) to create a hybrid capacitor displaying among the most promising performances reported: based on the active materials, it delivers 184 Wh kg(-1) at 83 W kg(-1) and 90 Wh kg(-1) at 15 000 W kg(-1) with 76% capacity retention after 5000 cycles.
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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 | 0.001 | 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".