Improving Energy Density and Structural Stability of Manganese Oxide Cathodes for Na-Ion Batteries by Structural Lithium Substitution
Bibliographic record
Abstract
We report excellent cycling performance for P2–Na 0.6 Li 0.2 Mn 0.8 O 2, an auspicious cathode material for sodium-ion batteries. This material, which contains mainly Mn 4+, exhibits a long voltage plateau on the first charge, similar to that of high-capacity lithium and manganese-rich metal oxides. Electrochemical measurements, X-ray diffraction, and elemental analysis of the cycled electrodes suggest an activation process that includes the extraction of lithium from the material. The “activated” material delivers a stable, high specific capacity up to ∼190 mAh/g after 100 cycles in the voltage window between 4.6–2.0 V versus Na/Na + . DFT calculations locate the energy states of oxygen atoms near the Fermi level, suggesting the possible contribution of oxide ions to the redox process. The addition of Li to the lattice improves structural stability compared to many previously reported sodiated transition-metal oxide electrode materials, by inhibiting the detrimental structural transformation ubiquitously observed with sodium manganese oxides during cycling. This research demonstrates the prospect of intercalation materials for Na-ion battery technology that are active based on both cationic and anionic redox moieties.
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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 | 0.001 | 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".