Vertically Grown Few‐Layer MoS<sub>2</sub> Nanosheets on Hierarchical Carbon Nanocages for Pseudocapacitive Lithium Storage with Ultrahigh‐Rate Capability and Long‐Term Recyclability
Bibliographic record
Abstract
Abstract Molybdenum disulfide (MoS2) is an intensively studied anode material for lithium‐ion batteries (LIBs) owing to its high theoretical capacity, but it is still confronted by severe challenges of unsatisfactory rate capability and cycle life. Herein, few‐layer MoS2 nanosheets, vertically grown on hierarchical carbon nanocages (hCNC) by a facile hydrothermal method, introduce pseudocapacitive lithium storage owing to the highly exposed MoS2 basal planes, enhanced conductivity, and facilitated electrolyte access arising from good hybridization with hCNC. Thus, the optimized MoS2/hCNC exhibits reversible capacities of 1670 mAh g−1 at 0.1 A g−1 after 50 cycles, 621 mAh g−1 at 5.0 A g−1 after 500 cycles, and 196 mAh g−1 at 50 A g−1 after 2500 cycles, which are among the best for MoS2‐based anode materials. The specific power and specific energy, which can reach 16.1 kW and 252.8 Wh after 3000 cycles, respectively, indicate great potential in high‐power and long‐life LIBs. These findings suggest a promising strategy for exploring advanced anode materials with high reversible capacity, high‐rate capability, and long‐term recyclability.
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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 | 0.000 | 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".