A Holistic Picture of the Phase Construction Process of O3‐Structured NaNi <sub>1/3</sub> Mn <sub>1/3</sub> Fe <sub>1/3</sub> O <sub>2</sub> for Sodium‐Ion Batteries
Bibliographic record
Abstract
Abstract The synthesis process of layered oxide cathode materials is pivotal yet underexplored in sodium‐ion battery (SIB) research. This study systematically investigates the phase construction mechanisms of O3‐structured NaNi 1/3 Mn 1/3 Fe 1/3 O 2 (NMF) through in situ heating XRD, synchrotron‐based STXM, and electrochemical analysis, focusing on decomposition, diffusion, phase transformation, and oxidation steps during the synthesis. Three precursors—co‐precipitated hydroxides, micrometer‐sized metal oxides (MO), and nanometer‐sized oxides (sand‐milled metal oxides, SMMO)—are compared, alongside sodium sources (Na 2 CO 3 , NaOH, NaHCO 3 ). Hydroxide precursors enabled a direct P3‐to‐O3 solid‐solution transition via homogeneous Na‐ion diffusion, yielding uniform structures and superior electrochemical performance (131 mAh g −1 discharge capacity). In contrast, MO precursors exhibited stepwise phase evolution: Mn 2 O 3 initiated P3 formation at 425 °C, Fe 2 O 3 promoted O3 nucleation at 675 °C, and NiO finalized the transition at 800 °C, albeit with residual impurities. Reducing precursor size (SMMO) delayed phase onset temperatures but retained diffusion‐controlled pathways. Sodium source decomposition kinetics critically influenced phase transitions: NaOH accelerated O3 formation at lower temperatures, while NaHCO 3 delayed P3‐O3 conversion. STXM revealed heterogeneous oxidation states in oxide‐derived samples, correlating with sluggish diffusion and inferior cycling stability. This work establishes that precursor uniformity and sodium source selection govern diffusion homogeneity, phase purity, and electrochemical behavior.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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; 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".