Ambient Synthesis of Vanadium‐Based Prussian Blue Analogues Nanocubes for High‐Performance and Durable Aqueous Zinc‐Ion Batteries with Eutectic Electrolytes
Bibliographic record
Abstract
Abstract Prussian blue analogues (PBAs) have been widely studied in aqueous zinc‐ion batteries (AZIBs) due to the characteristics of large specific surface area, open aperture, and straightforward synthesis. In this work, vanadium‐based PBA nanocubes were firstly prepared using a mild in situ conversion strategy at room temperature without the protection of noble gas. Benefiting from the multiple‐redox active sites of V 3+ /V 4+ , V 4+ /V 5+ , and Fe 2+ /Fe 3+ , the cathode exhibited an excellent discharge specific capacity of 200 mAh g −1 in AZIBs, which is much higher than those of other metal‐based PBAs nanocubes. To further improve the long‐term cycling stability of the V‐PBA cathode, a high concentration water‐in‐salt electrolyte (4.5 M ZnSO 4 +3 M Zn(OTf) 2 ), and a water‐based eutectic electrolyte (5.55 M glucose+3 M Zn(OTf) 2 ) were designed to successfully inhibit the dissolution of vanadium and improve the deposition of Zn 2+ onto the zinc anode. More importantly, the assembled AZIBs maintained 55 % of their highest discharge specific capacity even after 10000 cycles at 10 A g −1 with superior rate capability. This study provides a new strategy for the preparation of pure PBA nanostructures and a new direction for enhancing the long‐term cycling stability of PBA‐based AZIBs at high current densities for industrialization prospects.
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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) | 0.000 | 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".