Electrostatic Self-Assembly Enabling Integrated Bulk and Interfacial Sodium Storage in 3D Titania-Graphene Hybrid
Bibliographic record
Abstract
Room-temperature sodium-ion batteries have attracted increased attention for energy storage due to the natural abundance of sodium. However, it remains a huge challenge to develop versatile electrode materials with favorable properties, which requires smart structure design and good mechanistic understanding. Herein, we reported a general and scalable approach to synthesize three-dimensional (3D) titania–graphene hybrid via electrostatic-interaction-induced self-assembly. Synchrotron X-ray probe, transmission electron microscopy, and computational modeling revealed that the strong interaction between titania and graphene through comparably strong van der Waals forces not only facilitates bulk Na + intercalation but also enhances the interfacial sodium storage. As a result, the titania–graphene hybrid exhibits exceptional long-term cycle stability up to 5000 cycles, and ultrahigh rate capability up to 20 C for sodium storage. Furthermore, density function theory calculation indicated that the interfacial Li +, K +, Mg 2+, and Al 3+ storage can be enhanced as well. The proposed general strategy opens up new avenues to create versatile materials for advanced battery systems.
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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".