Valence Engineering via Polyoxometalate‐Induced on Vanadium Centers for Efficient Aqueous Zinc‐Ion Batteries
Bibliographic record
Abstract
Abstract Layered vanadium‐based compounds have attracted attention as cathode materials for aqueous zinc‐ion batteries (AZIBs) because of their low cost, high theoretical specific capacity, and abundant vanadium valence states. However, the slow migration of Zn 2+ ions and their poor cycling stability hinder their practical application in AZIBs. Herein, using a one‐pot solvothermal method, the polyoxometalates (POMs) were inserted into the aluminum vanadate interlayer spacing, and a series of novel 3D nanoflower cathode materials (HAVO‐MMo 6 ‐ X ) were successfully fabricated. The unique electron‐rich structure of the POMs accelerated the migration of Zn 2+ on the cathode to obtain a high specific capacity. Owing to the synergistic pillar effect of POMs and HAVO, the interlayer spacing of HAVO‐FeMo 6 ‐50 increased to approximately 14.33 Å. X‐ray absorption fine structure spectroscopy was used to analyze the coordination environments of the cathode materials. A combination of in situ and ex situ characterization techniques demonstrated the storage mechanism of Zn 2+ during the charge/discharge process. Furthermore, the experimental results and DFT calculations indicated that the introduction of POMs had the dual function of improving conductivity and reducing the Zn 2+ migration barrier. Thus, this work provides a new perspective on the synergistic interaction between POMs and metal compounds and offers insights into the design of functionally rich nanomaterials.
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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) | 0.000 | 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 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".