Synergistic Perovskite Titanate Coating and Lattice Doping Toward Air‐Stable and Long‐Life O3‐Type NaNi <sub>1/3</sub> Fe <sub>1/3</sub> Mn <sub>1/3</sub> O <sub>2</sub> Cathodes
Bibliographic record
Abstract
ABSTRACT O3‐type layered oxides are promising cathode materials for sodium‐ion batteries but suffer from structural instability, sluggish kinetics, and moisture sensitivity. This work proposes a synergistic modification of O3‐NaNi 1/3 Fe 1/3 Mn 1/3 O 2 (NFM). Among various perovskite titanates (CaTiO 3 , SrTiO 3 , BaTiO 3 ) investigated, CaTiO 3 proves to be the most effective modifier. DFT calculations reveal that Ca 2+ doping uniquely strengthens the Na‐O interaction, fundamentally enhancing the air stability. The conformal CaTiO 3 coating serves as a robust physical barrier against humid air, significantly suppressing the formation of surface carbonates and residual alkali. Simultaneously, Ca 2+ and Ti 4+ are doped into Na and transition metal (TM) sites, respectively, which enlarges the Na + layer spacing (from 3.701 to 3.812 Å), strengthens the TM─O framework, and mitigates irreversible phase transitions. As a result, the modified NFM@CTO06 cathode exhibits outstanding electrochemical performance, demonstrating a high capacity retention of 85.1% after 300 cycles at 1 C. Furthermore, it demonstrates reduced voltage hysteresis, enhanced Na + diffusion kinetics, and significantly improved air stability. This surface‐to‐bulk strategy offers a feasible approach toward practical high‐energy‐density sodium‐ion batteries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".