Deep-Eutectic Solvent as a Solvent and Precursor for the Synthesis of a Carbon-Coated Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3–<i>y</i></sub>O<sub><i>y</i></sub> Material
Bibliographic record
Abstract
Deep eutectic solvents (DES) are well-known as cost-effective and environmentally friendly “designer solvents” for controlling the size and morphology of nanomaterials. In this study, we leverage DES not only as a solvent for the topochemical synthesis of Na 3 V 2 (PO 4 ) 2 F 3– y O y (0 ≤ y ≤ 2) but also as a precursor for a uniform and thin carbon coating. After solvothermal synthesis in a green deep eutectic solvent composed of a mixture of choline chloride, citric acid, and water (3:1:3 molar ratio), XRD refinements and FTIR, XPS, and TEM analyses confirmed the obtention of a pure Na 3 V 2 (PO 4 ) 2 F 3– y O y (0 ≤ y ≤ 2) phase encapsulated in an organic layer derived from a residual deep eutectic solvent. Subsequent sintering at 600 °C under an argon atmosphere produced a homogeneous nitrogen-doped carbon coating without the need for additional carbon sources. Electrochemical tests in galvanostatic conditions demonstrated that this material exhibits excellent performance in terms of capacity retention and rate capabilities, with specific capacities exceeding 110 mAh/g at 2C versus Na metal and 68 mAh/g at 10C in full cells versus hard carbon.
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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) | 0.001 | 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".