Blocky Sb/C Anodes with Enhanced Diffusion Kinetics for High‐Rate and Ultra‐Long Cyclability Sodium Dual‐Ion Batteries
Bibliographic record
Abstract
Abstract Sodium ion‐based dual ion batteries (SDIBs) have attracted increasing attentions for their high operative voltages and low cost, but their poor long‐term cycling stability and rate capability largely hinder their practical applications. Here, an optimized anode‐antimony/carbon/graphene (Sb/C/G) composite for SDIBs is designed. Sb nanoparticles (NPs) not only can enhance the specific capacity but also facilitate the Na+ diffusion kinetics. The continuous conductive carbon matrix can promote the electron transfer process and accommodate volume changes of Sb NPs during sodiation/desodiation. Therefore, superior electrochemical performance, for example, a high discharge capacity of 376 mA h g−1 with a higher ICE (69.1 %) at current density of 500 mA g−1, an excellent cycling stability (73 mA h g−1 is retained even after 1400 cycles at current density of 1000 mA g−1), and high stable CE of 99.0 %. Our study offers a suitable design for Na+‐based batteries anode structure and accelerates their practical applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".