Ultrahigh Rate and Long‐Life Sodium‐Ion Batteries Enabled by Engineered Surface and Near‐Surface Reactions
Bibliographic record
Abstract
Abstract To achieve the high‐power sodium‐ion batteries, the solid‐state ion diffusion in the electrode materials is a highly concerned issue and needs to be solved. In this study, a simple and effective strategy is reported to weaken and degrade this process by engineering the intensified surface and near‐surface reactions, which is realized by making use of a sandwich‐type nanoarchitecture composed of graphene as electron channels and few‐layered MoS 2 with expanded interlayer spacing. The unique 2D sheet‐shaped hierarchical structure is capable of shortening the ion diffusion length, while the few‐layered MoS 2 with expanded interlayer spacing has more accessible surface area and the decreased ion diffusion resistance, evidenced by the smaller energy barriers revealed by the density functional theory calculations. Benefiting from the shortened ion diffusion distance and enhanced electron transfer capability, a high ratio of surface or near‐surface reactions is dominated at a high discharge/charge rate. As such, the composites exhibit the high capacities of 152 and 93 mA h g −1 at 30 and 50 A g −1 , respectively. Moreover, a high reversible capacity of 684 mA h g −1 and an excellent cycling stability up to 4500 cycles can be delivered. The outstanding performance is attributed to the engineered structure with increased contribution of surface or near‐surface reactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".