Insight Into Pre‐Intercalation of Layered Vanadium Oxide Cathodes: From Precise Control of the Interspace to Related Electrochemical Performance and Beyond
Bibliographic record
Abstract
ABSTRACT Pre‐intercalation is the mainstream approach to inhibit the unpredicted structural degradation and the sluggish kinetics of Zn‐ions migrating in vanadium oxide cathode of aqueous zinc‐ion batteries (AZIBs), which has been extensively explored over the past 5 years. The functional principles behind the improvement are widely discussed but have been limited to the enlargement of interspace between VO layers. As the different types of ions could change the properties of vanadium oxides in various ways, the review starts with a comprehensive overview of pre‐intercalated vanadium oxide cathode with different types of molecules and ions, such as metal ions, water molecules, and non‐metallic cations, along with their functional principles and resulting performance. Furthermore, the pre‐intercalated vanadium cathodes reported so far are summarized, comparing their interlayer space, capacity, cycling rate, and capacity retention after long cycling. A discussion of the relationship between the interspace and the performance is provided. The widest interspaces could result in the decay of the cycling stability. Based on the data, the optimal interspace is likely to be around 12 Å, indicating that precise control of the interspace is a useful method. However, more consideration is required regarding the other impacts of pre‐intercalated ions on vanadium oxide. It is hoped that this review can inspire further understanding of pre‐intercalated vanadium oxide cathodes, paving a new pathway to the development of advanced vanadium oxide cathodes with better cycling stability and larger energy density.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".