Nanoflake‐Assembled Hierarchical Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>3</sub>/C Microflowers: Superior Li Storage Performance and Insertion/Extraction Mechanism
Bibliographic record
Abstract
Na3V2(PO4)3 (NVP) has excellent electrochemical stability and fast ion diffusion coefficient due to the 3D Na+ ion superionic conductor framework, which make it an attractive cathode material for lithium ion batteries (LIBs). However, the electrochemical performance of NVP needs to be further improved for applications in electric vehicles and hybrid electric vehicles. Here, nanoflake‐assembled hierarchical NVP/C microflowers are synthesized using a facile method. The structure of as‐synthesized materials enhances the electrochemical performance by improving the electron conductivity, increasing electrode–electrolyte contact area, and shortening the diffusion distance. The as‐synthesized material exhibits a high capacity (230 mAh g−1), excellent cycling stability (83.6% of the initial capacity is retained after 5000 cycles), and remarkable rate performance (91 C) in hybrid LIBs. Meanwhile, the hybrid LIBs with the structure of NVP || 1 m LiPF6/EC (ethylene carbonate) + DMC (dimethyl carbonate) || NVP and Li4Ti5O12 || 1 m LiPF6/EC + DMC || NVP are assembled and display capacities of 79 and 73 mAh g−1, respectively. The insertion/extraction mechanism of NVP is systematically investigated, based on in situ X‐ray diffraction. The superior electrochemical performance, the design of hybrid LIBs, and the insertion/extraction mechanism investigation will have profound implications for developing safe and stable, high‐energy, and high‐power LIBs.
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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".