Honeycomb‐Structured MoSe<sub>2</sub>/rGO Composites as High‐Performance Anode Materials for Sodium‐Ion Batteries
Bibliographic record
Abstract
Abstract Sodium‐ion batteries are a promising substitute for lithium batteries due to the abundant resources and low cost of sodium. Herein, honeycomb‐shaped MoSe2/reduced graphene oxide (rGO) composite materials are synthesized from graphene oxide (GO) and MoSe2 through a one‐step solvothermal process. Experiments show that the 3D honeycomb structure provides excellent electrolyte penetration while alleviating the volume change during electrochemical cycling. An anode prepared with MoSe2/rGO composites exhibits significantly improved sodium‐ion storage properties, where a large reversible capacity of 215 mAh g−1 is obtained after 2700 cycles at the current density of 30.0 A g−1 or after 5900 cycles at 8.0 A g−1. When such an anode is paired with Na3V2(PO4)3 to form a full cell, a reversible specific capacity of 107.5 mAh g−1 can be retained after 1000 cycles at the current of 1.0 A g−1. Transmission electron microscopy, X‐ray photoelectron spectroscopy and in situ X‐ray diffraction (XRD) characterization reveal the reversible storage reaction of Na ions in the MoSe2/rGO composites. The significantly enhanced sodium storage capacity is attributed to the unique honeycomb microstructure and the use of ether‐based electrolytes. This study illustrates that combining rGO with ether‐based electrolytes has tremendous potential in constructing high‐performance sodium‐ion batteries.
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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".