One‐Step Synthesis of 2‐Ethylhexylamine Pillared Vanadium Disulfide Nanoflowers with Ultralarge Interlayer Spacing for High‐Performance Magnesium Storage
Bibliographic record
Abstract
Abstract Rechargeable magnesium batteries (RMBs) are attractive candidates for large‐scale energy storage owing to the high theoretical specific capacity, rich earth abundance, and good safety characteristics. However, the development of desirable cathode materials for RMBs is constrained by the high polarity and slow intercalation kinetics of Mg2+ ions. Herein, it is demonstrated that 2‐ethylhexylamine pillared vanadium disulfide nanoflowers (expanded VS2) with enlarged interlayer distances exhibit greatly boosted electrochemical performance as a cathode material in RMBs. Through a one‐step solution‐phase synthesis and in situ 2‐ethylhexylamine intercalation process, VS2 nanoflowers with ultralarge interlayer spacing are prepared. A series of ex situ characterizations verify that the cathode of expanded VS2 nanoflowers undergoes a reversible intercalation reaction mechanism, followed by a conversion reaction mechanism. Electrochemical kinetics analysis reveal a relatively fast Mg‐ion diffusivity of expanded VS2 nanoflowers in the order of 10−11–10−12 cm2 s−1, and the pseudocapacitive contribution is up to 64% for the total capacity at 1 mV s−1. The expanded VS2 nanoflowers show highly reversible discharge capacity (245 mAh g−1 at 100 mA g−1), good rate capability (103 mAh g−1 at 2000 mA g−1), and stable cycling performance (90 mAh g−1 after 600 cycles at 1000 mA g−1).
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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".