Sodium-Rich Na<sub>3+4<i>x</i></sub>MnTi<sub>1–<i>x</i></sub>(PO<sub>4</sub>)<sub>3</sub> Cathode for High-Performance Sodium-Ion Batteries
Bibliographic record
Abstract
The low cost, abundant reserves, and wide distribution of sodium resources compared with lithium support the potential for sodium-ion batteries to be widely used in large-scale electric energy storage systems. Na 3 MnTi (PO 4 ) 3 cathode exhibits a three-electron reaction with a theoretical specific capacity of 176 mAh g –1 and high energy density, which indicates its great potential for applications in sodium-ion batteries. Nevertheless, the Jahn–Teller effect of Mn-based materials and the high Na + diffusion energy barrier represent limitations that necessitate further improvement in the structural stability and reaction kinetics of Na 3 MnTi(PO 4 ) 3 . In this work, we successfully prepared sodium-rich Na 3+4 x MnTi 1– x (PO 4 ) 3 materials by adopting a titanium-deficient and sodium-enhanced synthetic strategy. This synthetic strategy significantly increases the number of active Na2 sites and further activates the redox reaction of Mn, thereby improving the electrochemical performance of the material via the analyses by XRD, electrochemical characterization, and DFT calculations. Among the sodium-rich materials, Na 3.2 MnTi 0.95 (PO 4 ) 3 exhibits excellent electrochemical properties with a high reversible capacity (160.5 mAh g –1, 0.2 C), high rate (148.8 mAh g –1, 10 C), and stable cycling performance (capacity retention of 97.6% at 1 C after 100 cycles). The sodium-rich strategy can facilitate the enhancement of the electrochemical performance of polyanionic materials and accelerate their application in the field of sodium-ion batteries.
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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 | 0.001 | 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".